Springer Handbook of Automation

Historical perspectives are given about the impressive progress in automation. Automation, including robotics, has evolved by becoming useful and affordable. Methods have been developed to analyze and design better automation, and those methods have also been automated. The most important issue in automation to make every effort to paying attention to all the details.

Automation is a way for humans to extend the capability of their tools and machines. Self-operation by tools and machines requires four functions: Performance detection; process correction; adjustments due to disturbances; enabling the previous three functions without human intervention. Development of these functions evolved in history, and automation is the capability of causing machines to carry out a specific operation on command from external source. In chemical manufacturing and petroleum industries prior to 1940, most processing was in batch environment. The increasing demand for chemical and petroleum products by World War II and thereafter required different manufacturing setup, leading to continuous processing and efficiencies were achieved by automatic control and automation of process, flow and transfer. The increasing complexity of the control system for large plants necessitated applications of computers, which were introduced to the chemical industry in the 1960s. Automation has substituted computer-based control systems for most, if not all, control systems previously based on human-aided mechanical or pneumatic systems to the point that chemical and petroleum plant systems are now fully automatic to a very high degree. In addition, automation has replaced human effort, eliminates significant labor costs, and prevents accidents and injuries that might occur. The Purdue enterprise reference architecture (PERA) for hierarchical control structure, the hierarchy of personnel tasks, and plant operational management structure, as developed for large industrial plants, and a frameworks for automation studies are also illustrated.

The meaning of the term

automation

is reviewed through its definition and related definitions, historical evolution, technological progress, benefits and risks, and domains and levels of applications. A survey of 331 people around the world adds insights to the current meaning of automation to people, with regard to:

What is your definition of automation?

Where did you encounter automation first in your life?

and

What is the most important contribution of automation to society?

The survey respondents include 12 main aspects of the definition in their responses; 62 main types of first automation encounter; and 37 types of impacts, mostly benefits but also two benefit–risks combinations: replacing humans, and humansʼ inability to complete tasks by themselves. The most exciting contribution of automation found in the survey was to

encourage/inspire creative work; inspire newer solutions.

Minor variations were found in different regions of the world. Responses about the first automation encounter are somewhat related to the age of the respondent, e.g., pneumatic versus digital control, and to urban versus farming childhood environment. The chapter concludes with several emerging trends in bioinspired automation, collaborative control and automation, and risks to anticipate and eliminate.

Automatic control

control

automatic

, particularly the application of feedback, has been fundamental to the development of automation. Its origins lie in the level control, water clocks, and pneumatics/hydraulics of the ancient world. From the 17th century onwards, systems were designed for temperature control, the mechanical control of mills, and the regulation of steam engines. During the 19th century it became increasingly clear that feedback systems were prone to instability. A stability criterion was derived independently towards the end of the century by Routh in England and Hurwitz in Switzerland. The 19th century, too, saw the development of servomechanisms, first for ship steering and later for stabilization and autopilots. The invention of aircraft added (literally) a new dimension to the problem. Minorskyʼs theoretical analysis of ship control in the 1920s clarified the nature of three-term control, also being used for process applications by the 1930s. Based on servo and communications engineering developments of the 1930s, and driven by the need for high-performance gun control systems, the coherent body of theory known as

classical control

emerged during and just after WWII in the US, UK and elsewhere, as did cybernetics ideas. Meanwhile, an alternative approach to dynamic modeling had been developed in the USSR based on the approaches of Poincaré and Lyapunov. Information was gradually disseminated, and

state-space

or

modern control

techniques, fuelled by Cold War demands for missile control systems, rapidly developed in both East and West. The immediate post-war period was marked by great claims for automation, but also great fears, while the digital computer opened new possibilities for automatic control.

Society and information from the evolutionary early beginnings. The revolutionary novelties of our age: the possibility for the end of a human being in the role of draught animal and the symbolic representation of the individual and of his/her property by electronic means, free of distance and time constraints. As a consequence, changing human roles in production, services, organizations and innovation; changing society stratifications, human values, requirements in skills, individual conscience. New relations: centralization and decentralization, less hierarchies, discipline and autonomy, new employment relations, less job security, more free lance, working home, structural unemployment, losers and winners, according to age, gender, skills, social background. Education and training, levels, life long learning, changing methods of education. Role of memory and associative abilities. Changes reflected in linguistic relations, multilingual global society, developments and decays of regional and social vernaculars. The social-political arena, human rights, social philosophies, problems and perspectives of democracy. The global agora and global media rule. More equal or more divided society. Some typical society patterns: US, Europe, Far East, India, Latin America, Africa.

The increasing diffusion of automation in all sectors of the industrial world gives rise to a deep modification of labor organization and requires a new approach to evaluate industrial systems efficiency, effectiveness, and economic convenience. Until now, the evaluation tools and methods at disposal of industrial managers are rare and even complex. Easy-to-use criteria, possibly based on robust but simple models and concepts, appear to be necessary. This chapter gives an overview of concepts, based on the economic theory but revised in the light of industrial practice, which can be applied for evaluating the impact and effects of automation diffusion in enterprises.

Automation has significant impacts on the economy and the development and use of technology. In this chapter, the impacts of automation on precision, which also directly influences science, technology, and the economy, are discussed. As automation enables improved precision, precision also improves automation.

Following the definition of precision and the factors affecting it, the relationship between precision and automation is described. This chapter concludes with specific examples of how automation has improved the precision of manufacturing processes and manufactured products over the last decades.

The present chapter addresses automation as a major means for gaining and sustaining productivity advantages. Typical market environment factors for plant and mill operators are identified, and the analysis of current technology trends allows us to derive drivers for the automation industry.

A section on current trends takes a closer look at various aspects of integration and optimization. Integrating process and automation, safety equipment, but also information and engineering processes is analyzed for its benefit for owners during the lifecycle of an installation. Optimizing the operation through advanced control and plant asset monitoring to improve the plant performance is then presented as another trend that is currently being observed. The section covers system integration technologies such as IEC61850, wireless communication, fieldbuses, or plant data management. Apart from runtime system interoperability, the section also covers challenges in engineering integrated systems.

The section on the outlook into future trends addresses the issue of managing increased complexity in automation systems, takes a closer look at future control schemes, and takes an overall view on automation lifecycle planning.

Any work on prediction of the future is based on an extrapolation of current trends, and estimations of their future development. In this chapter we will therefore have a look at the trends that drive the automation industry and identify those developments that are in line with these drivers.

Like in all other areas of the industry, the future of automation is driven by market requirements on one hand and technology capabilities on the other hand. Both have undergone significant changes in recent years, and continue to do so.

In the business environment, globalization has led to increased worldwide competition. It is not only Western companies that use offshore production to lower their cost; it is more and more also companies from upcoming regions such as China and India that go global and increase competition. The constant strive for increased productivity is inherent to all successful players in the market.

In this environment, automation technology benefits from the rapid developments in the information technology (IT) industry. Whereas some 15 years ago automation technology was mostly proprietary, today it builds on technology that is being applied in other fields. Boundaries that have clearly been defined due to the incompatibility of technologies are now fully transparent and allow the integration of various requirements throughout the value chain. Field-level data is distributed throughout the various networks that control a plant, both physically and economically, and can be used for analysis and optimization.

To achieve the desired return, companies need to exploit all possibilities to further improve their production or services. This affects all automation levels from field to enterprise optimization, all lifecycle stages from plant erection to dismantling, and all value chain steps from procurement to service.

In all steps, on all levels, automation may play a prominent role to optimize processes.

In this chapter autonomous dynamical systems, stability, asymptotic behavior, dynamical systems with inputs, feedback stabilization of linear systems, feedback stabilization of nonlinear systems, and tracking and regulation are discussed to provide the foundation for control theory for automation.

Analysis and design of control systems is a complex field. In order to develop appropriate concepts and methods to cover this field, mathematical models of the processes to be controlled are needed to apply. In this chapter mainly continuous-time linear systems with multiple input and multiple output (MIMO systems)

multiple-input and multiple- output (MIMO)

are considered. Specifically, stability, performance, and robustness issues, as well as optimal control strategies are discussed in detail for MIMO linear systems. As far as system

transfer function

representations are concerned, transfer function matrices, matrix fraction

matrix fraction description

state-space model

descriptions, and state-space models are applied in the discussions. Several interpretations of all stabilizing controllers are shown for stable and unstable processes. Performance evaluation is supported by applying

H

2

and

H

∞

norms. As an important class for practical applications, predictive controllers are also discussed. In this case, according to the underlying implementation technique, discrete-time process models are considered. Transformation methods using state variable feedback are discussed, making the operation of nonlinear dynamic systems linear in the complete range of their operation. Finally, the sliding control concept is outlined.

Novel direct adaptive robust state and output feedback controllers are presented for the output tracking control of a class of nonlinear systems with unknown system dynamics and disturbances. Both controllers employ a variable-structure radial basis function (RBF)

radial basis function (RBF)

network that can determine its structure dynamically to approximate unknown system dynamics. Radial basis functions are added or removed online in order to achieve the desired tracking accuracy and prevent to network redundancy. The raised-cosine RBF is employed to enable fast and efficient training and output evaluation of the RBF network. The direct adaptive robust output feedback controller is constructed by utilizing a high-gain observer to estimate the tracking error for the controller implementation. The closed-loop systems driven by the variable neural direct adaptive robust controllers are actually switched systems.

Stochastic learning automata are probabilistic finite state machines which have been used to model how biological systems can learn. The structure of such a machine can be fixed or can be changing with time. A learning automaton can also be implemented using action (choosing) probability updating rules which may or may not depend on estimates from the environment being investigated. This chapter presents an overview of the field of learning automata, perceived as a completely new paradigm for learning, and explains how it is related to the area of

cybernetics

.

An introduction to the fundamental issues and limitations of communication and networking in automation is given. Digital communication fundamentals are reviewed and networked control systems together with teleoperation are discussed. Issues in both wired and wireless networks are presented.

Artificial intelligence

(AI)

artificial intelligence (AI)

focuses on getting machines to do things that we would call intelligent behavior. Intelligence – whether artificial or otherwise – does not have a precise definition, but there are many activities and behaviors that are considered intelligent when exhibited by humans and animals. Examples include seeing, learning, using tools, understanding human speech, reasoning, making good guesses, playing games, and formulating plans and objectives. AI focuses on how to get machines or computers to perform these same kinds of activities, though not necessarily in the same way that humans or animals might do them.

Virtual reality of human activities (e.g., in design, manufacturing, medical care, exploration or military operations) often concentrates on an automated interface between virtual reality (VR) technology and the theory

virtual reality (VR)

and practice of these activities. In this chapter we focus mainly on the role of VR technology in developing this interface. Although the scope and range of applications is large, two illustrative areas (production/service applications and medical applications) are explained in some detail to offer some insight into the magnitude of the benefits and existing challenges.

This chapter deals with general concepts on the automation of mobility and autonomous navigation. The emphasis is on the control and navigation of autonomous vehicles. Thus, after an introduction with historical background and basic concepts, the chapter briefly reviews general concepts on vehicle motion control by using models of the vehicle, as well as other approaches based on the information provided by humans. Autonomous navigation is also studied, involving not only motion planning and trajectory generation but also interaction with the environment to provide reactivity and adaptation in the autonomous navigation. These interactions are represented by means of nested loops closed at different frequencies with different bandwidth requirements. The human interactions at different levels are also analyzed, taking into account transmission of control commands and feedback of sensory information. Finally, the chapter studies multiple mobile systems by analyzing coordinated navigation of multiple autonomous vehicles and cooperation paradigms for autonomous mission execution.

A survey of the history of how humans have interacted with automation is presented. Starting

automation

human role

with the early introduction of automation into the Industrial Revolution to the modern applications that occur in unmanned air vehicle systems, many issues are brought to light. Levels of automation are quantified and a preliminary list delineating what tasks humans can perform better than machines is presented. A number of application areas are surveyed that have or are currently dealing with positive and negative issues as humans interact with machines. The application areas where humans specifically interact with automation include agriculture, communications systems, inspection systems, manufacturing, medical and diagnostic applications, robotics, and teaching. The benefits and disadvantages of how humans interact with modern automation systems are presented in a trade-off space discussion. The modern problems relating to how humans have to deal with automation include trust, social acceptance, loss of authority, safety concerns, adaptivity of automation leading to unplanned unexpectancy, cost advantages, and possible performance gained.

The question of what can and what cannot be automated challenged engineers, scientists, and philosophers even before the term

automation

was defined. While this question may also raise ethical and educational issues, the focus here is scientific. In this chapter the limits of automation and mechanization are explored and explained in an effort to address this fundamental conundrum. The

evolution computer languages

evolution of computer languages to provide domain-specific solutions to automation design problems is reviewed as an illustration and a model of the limitations of mechanization. The current state of the art and a general automation principle are also provided.

Many technical processes and products in the area of mechanical and electrical engineering show increasing integration of mechanics with digital electronics and information processing. This integration is between the components (hardware) and the information-driven functions (software), resulting in integrated systems called mechatronic systems. Their development involves finding an optimal balance between the basic mechanical structure, sensor and actuator implementation, and automatic information processing and overall control. Frequently formerly mechanical functions are replaced by electronically controlled functions, resulting in simpler mechanical structures and increased functionality. The development of mechatronic systems opens the door to many innovative solutions and synergetic effects which are not possible with mechanics or electronics alone. This technical progress has a very strong influence on a multitude of products in the areas of mechanical, electrical, and electronic engineering and is increasingly changing the design, for example, of conventional electromechanical components, machines, vehicles, and precision mechanical devices.

Sensors are essential devices in many industrial applications such as factory automation, digital appliances, aircraft/automotive applications, environmental monitoring, and system diagnostics. The main role of those sensors is to measure changes of physical quantities of surroundings. In general, sensors are embedded into sensory devices with a circuitry as a part of a system. In this chapter, various types of sensors and their working principles are briefly explained as well as their technical advancement to recent smart microsensors is introduced. Specifically, the individual sensor issue is also extended to emerging networked sensors and their applications from recent research activities. Through this chapter, readers can also understand how multisensors or networked sensors can be configured and how they can collaborate with each other to provide higher performance and reliability within networked sensor systems.

It has been believed for a long time since the birth of the industrial robot that the only task it could perform was to play back simple motions that had been taught in advance. At the beginning of the 21st century, the industrial robot was born again as the industrial intelligent robot, which performs highly complicated tasks like skilled workers on a production site, mainly due to the rapid advancement in vision and force sensors. The industrial intelligent robot has recently been a key technology to solve issues that todayʼs manufacturing industry is faced with, including the decreasing number of skilled workers and demands for reducing manufacturing costs and delivery time. In this chapter, the latest technology trends in its element technologies such as vision and force sensors are introduced with some of its applications such as the robot cell, which has succeeded in drastically reducing machining costs.

Automation is in most cases done through the use of hardware and software. Software-related costs account for a growing share of total development costs for automation systems. In the automation field, containment of software costs can be done either through the use of model-based tools (e.g., Matlab) or through a higher level of reuse. This chapter argues that both technologies have their place. The first strategy can be used for the design of software for a large number of identical installations or for the implementation of only part of the software (i.e., the control algorithms). The second strategy is advantageous in the case of industrial automation systems targeting niche markets where systems tend to be one-of-a-kind and where they can be organized in

families

of related applications. In many applications, a combination of the two approaches will produce the best results. Both approaches are treated in the paper. The main focus of the chapter is on developing software for automation. As such software will often be implemented for slightly different processes, it is highly appropriate that the production process is at least partly automated. As space is limited, this chapter can not cover all aspects of the design and implementation of software for automation, but we claim that the methods discussed here integrate very well with traditional methods of software and systems engineering. Experience from contributions to various research projects recently performed at Swiss Federal Technical university (ETH) are also summarized.

The world is becoming increasingly linked, integrated, and complex. Globalization, which arrives

autonomic

automation

in waves of increasing and decreasing usage, results in a permanently dynamic environment. Global supply networks, logistics processes, and production facilities try to follow these trends and – if possible – anticipate the volatile demand of the market. This challenging world can no longer be mastered with static, monolithic, and inert information technology (IT) solutions; instead it needs

agile

autonomic, adaptive, and agile systems – living systems. To achieve that, new systems not only need faster processors, more communication bandwidth, and modern software tools – more than ever they have to be built following a new design paradigm. As determined by the industrial and business environment, systems have to mirror and implement the real-world distribution of data and responsibility, the market (money)-driven decision basis for all stakeholders in the (real or virtual) market, and the goal orientation of people, which leads to on-demand, loosely coupled, communication with relevant partners (other players, roles) based on reactive or proactive activities.

This chapter provides an insight into the core challenges of todayʼs dynamics and complexity, briefly describes the ideas and goals of the new concept of software agents, and then presents and discusses industry-proven solutions in real-time environments based on this

distributed

distributed solution design.

For some companies,

service

oriented grid

information technology (IT)

information technology (IT) services constitute a fundamental function without which the company could not exist. Think of UPS without the ability to electronically track every package in its system or any large bank managing millions of customer accounts without computers. IT can be capital and labor intensive, representing anywhere between 1% and 5% of a companyʼs gross expenditures, and keeping costs commensurate with the size of the organization is a constant concern for the chief information officer (CIO)s in charge of IT.

A common strategy to keep labor costs in check today is through a deliberate

sourcing

service

sourcing

or service procurement strategy, which may include in-sourcing using in-house resources or outsourcing, which involve the delegation of certain standardized business processes such as payroll to service companies such as ADP.

Yet another way of keeping labor costs in check with a long tradition is through the use of automation, that is, the integrated use of technology, machines, computers, and processes to reduce the cost of labor.

The convergence of three technology domains, namely

information technology (IT)

virtualization

virtualization, service orientation, and

information technology (IT)

grid

grid computing promises to bring the automation of provision and delivery of IT services to levels never seen before. An IT environment where these three technology domains coexist is

virtual service-oriented environment (VSG)

said to be a

virtual service-oriented environment

or

VSG

environment. The cost savings are accrued through systemic reuse of resources and the ability to quickly integrate resources not just within one department, but across the whole company and beyond.

In this Chapter we will review each of the constituent technologies for a virtual service-oriented grid and examine how each contributes to the automation of delivery of IT services.

The increasing adoption of

service-oriented architecture (SOA)

service-oriented architectures (SOAs) represents the increasing recognition by IT organizations of the need for business and technology alignment. In fact, under SOA there is no difference between the two. The unit of delivery for SOA is a service, which is usually defined in business terms.

In other words, SOA represents the up-leveling of IT, empowering IT organizations to meet the business needs of the community they serve. This up-leveling creates a gap, because for IT business requirements eventually need to be translated into technology-based solutions.

Our research indicates that this gap is being fulfilled by the resurgence of two very old technologies, namely virtualization and grid computing.

To begin with, SOA allowed the decoupling of data from applications through the magic of extensible mark-up language (XML).

A lot of work that used to be done by application developers and integrators now gets done by computers. When most data centers run at 5–10% utilization, growing and deploying more data centers is not a good solution. Virtualization technology came in very handy to address this situation, allowing the decoupling of applications from the platforms on which they run. It acts as the gearbox in a car, ensuring efficient transmission of power from the engine to the wheels.

The net effect of virtualization is that it allows utilization factors to increase to 60–70%. The technique has been applied to mainframes for decades. Deploying virtualization to tens of thousands of servers has not been easy.

Finally, grid technology has allowed very fast, on-the-fly resource management, where resources are allocated not when a physical server is provisioned, but for each instance that a program is run.

Designers frequently look toward automation as a way to increase system efficiency and safety by reducing human involvement. This approach often leads to disappointment because the role of people becomes more, not less, important as automation becomes more powerfull and prevalent. Developing automation without consideration of the human operator leads to new and more catastrophic failures. For automation to fulfill its promise, designers must avoid a technology-centered approach and adopt an approach that considers the joint operator–automation system. Automation-related problems arise because introducing automation changes the type and extent of feedback that operators receive, as well as the nature and structure of tasks. In addition, operatorsʼ behavioral, cognitive, and emotional responses to these changes can leave the system vulnerable to failure. Automation is not a homogenous technology. There are many types of automation and each poses different design challenges. This chapter describes how different types of automation place different demands on operators. It also presents strategies that can help designers achieve the promise of automation. The chapter concludes with future challenges in automation design.

The development

collaborative

decision-making

decision-making (DM)

collaborative

human–automation

decision-making

of a comprehensive collaborative human–computer decision-making model is needed that demonstrates not only what decision-making functions should or could be assigned to humans or computers, but how many functions can best be served in a mutually supportive environment in which the human and computer collaborate to arrive at a solution superior to that which either would have come to independently. To this end, we present the

human–automation

collaboration taxonomy (HACT)

human–automation collaboration taxonomy (HACT), which builds on previous research by expanding the

Parasuraman

information processing model [

26.1

], specifically the decision-making component. Instead of defining a simple level of automation for decision making, we deconstruct the process to include three distinct roles: the

level of collaboration (LOC)

moderator, generator, and decider. We propose five levels of collaboration (LOCs) for each of these roles, which form a three-tuple that can be analyzed to evaluate system collaboration, and possibly identify areas for design intervention. A resource allocation mission planning case study is presented using this framework to illustrate the benefit for system designers.

This chapter presents an overview of the teleoperation of robotics systems, starting with a historical background, and including the description of an up-to-date specific teleoperation scheme as a representative example to illustrate the typical components and functional modules of these systems. Some specific topics in the field are particularly discussed, for instance, control algorithms, communications channels, the use of graphical simulation and task planning, the usefulness of virtual and augmented reality, and the problem of dexterous grasping. The second part of the chapter includes a description of the most typical application fields, such as industry and construction, mining, underwater, space, surgery, assistance, humanitarian demining, and education, where some of the pioneering, significant, and latest contributions are briefly presented. Finally, some conclusions and the trends in the field close the chapter.

The topics of this chapter are closely related to the contents of other chapters such as those on

Communication in Automation, Including Networking and Wireless

(Chap. 13),

Virtual

Reality and Automation

(Chap. 15), and

Collaborative Human–Automation Decision Making

(Chap. 26).

Agent-based software and hardware technologies have emerged as a major approach to organize and

distributed agent software

integrate distributed elements of complex automation. As an example, this chapter focuses on a particular situation. Composite curing, a rapidly developing industry process, generates high costs when not properly controlled. Curing autoclaves require tight control over temperature that must be uniform throughout the curing vessel. This chapter discusses how agent-based software is being

agent-based software

implemented into the curing process by pushing control logic down to the lowest level of the control hierarchy into the process controller, i.e., the programmable logic controller (PLC). The chapter also discusses how the benefits of process survivability, diagnostics, and dynamic reconfiguration are achieved through the use of autoclave and thermocouple intelligent agents.

In this chapter,

evolutionary

technique (ET)

evolutionary techniques (ETs) will be introduced for treating automation problems in factory, manufacturing, planning and scheduling, and logistics and transportation systems. ET is the most popular metaheuristic method for solving NP-hard optimization problems. In the past few years, ETs have been exploited to solve design automation problems. Concurrently, the field of ET reveals a significant interest in evolvable hardware and problems such as routing, placement or test pattern generation.

The rest of this chapter is organized as follows. First the background developments of evolutionary techniques are described. Then basic schemes and working mechanism of genetic algorithms (GAs) will be given, and multiobjective evolutionary algorithms for treating optimization problems with multiple and conflicting objectives are presented. Lastly, automation and the challenges for applying evolutionary techniques are specified.

Next, the various applications based on ETs for solving

factory automation (FA)

factory automation (FA) problems will be surveyed, covering planning and scheduling problems, nonlinear optimization problems in manufacturing systems, and optimal design problems in logistics and transportation systems.

Finally, among those applications based on ETs, detailed case studies will be introduced. The first case study covers

automated guided vehicle (AGV)

dispatching of automated guided vehicles (AGV) and machine scheduling in

flexible

manufacturing system (FMS)

manufacturing system

a flexible manufacturing system (FMS). The second ET case study for treating automation problems is the robot-based

assembly

line balancing (ALB)

assembly line balancing (ALB) problem. Numerical experiments for various scales of AGV dispatching problems and robot-based ALB problems will be described to show the effectiveness of the proposed approaches with greater search capability that improves the quality of solutions and enhances the rate of convergence over existing approaches.

Errors

automating

errors prevention

error prevention

automation

and conflicts exist in many systems. A fundamental question from industries is How can errors and conflicts in systems be eliminated by automation, or can we at least use automation to minimize their damage? The purpose of this chapter is to illustrate a theoretical background and applications of how to automatically prevent errors and conflicts with various devices, technologies, methods, and systems. Eight key functions to prevent errors and conflicts are identified and their theoretical background and applications in both production and service are explained with examples. As systems and networks become larger and more complex, such as global enterprises and the Internet, error and conflict prognostics and prevention become more important and challenging; the focus is shifting from passive response to proactive prognostics and prevention. Additional theoretical developments and implementation efforts are needed to advance the prognostics and prevention of errors and conflicts in many real-world applications.

The field of process automation is concerned with the analysis of dynamic behavior of chemical processes, design of automatic controllers, and associated instrumentations. Process automation as practised in the process industries has undergone significant changes since it was first introduced in the 1940s. Perhaps the most significant influence on the changes in process control technology has been the introduction of inexpensive digital computers and instruments with greater capabilities than their analog predecessors. During the past 20 years automatic control has assumed increased importance in the process industries, which has led to the application of more sophisticated techniques.

The combined effects of rapidly growing computational power, and the shrinking of the associated hardware in recent decades, mean that almost all products used in industry have acquired some form of

intelligence

, and can perform at least part of their functions automatically.

The influence of this development on global society is breathtaking. Today, only 50 years after the first indication of automation, the life of individuals and the way industries work has been transformed fundamentally.

The automation of a product requires the ability to achieve unsupervised interaction between the deviceʼs various sensors and actuators, and ultimately the ability to communicate and interact with other units.

This chapter gives an overview of the requirements to be fulfilled in the automation of products, and gives a flavor of todayʼs state of the art by presenting typical examples of automated products from a wide range of industrial applications. These examples cover automation in instrumentation, motors, circuit breakers, drives, robots, and embedded systems.

A fast and effective industrial service, supporting plants with a broad spectrum of assistance from preventive maintenance to emergency repair, rests on two legs: the physical transport of people and equipment, and the provision of the vast variety of information required by service personnel. While the automation of physical movement is limited, data management for efficient servicing, including optimized logistics for transport, is increasingly expanding throughout the service industry.

This chapter discusses the basic requirements for the automation of service and gives examples of how the challenging issues involved can be solved.

Over the last few decades, automation has developed into a central technological strategy. Automation technologies augment human life in many different fields. However, after having an unrealistic vision of fully automated production, we came to the realization that automation would never be able to replace man completely, but rather support him in his work. A contemporary model is the human-oriented design of an automated man–machine system. Here, the technology helps man to accomplish his tasks and enables him at the same time to expand his capacities.

In addition to traditional usage in industrial process automation nowadays automation technology supports man through the help of

smarter

, so to speak, better linked, efficient, miniaturized systems. In order to facilitate the interaction taking place between man and machine, functionality and usability are stressed.

In addition to basic knowledge, examples of use, and development prospects, this chapter will present strategies, procedures, methods, and rules regarding human-oriented and integrative design of automated man–machine systems.

This chapter deals with automation of machining lines, sometimes called transfer lines, which are serial machining systems dedicated to the production of large series. They are composed of a set of workstations and an automatic handling system. Each workstation carries out one identical set of operations every cycle time. The design of transfer lines is comprised of several steps: product analysis, process planning, line configuration, transport system design, and line implementation. In this chapter, we deal with line configuration. Its design performance is crucial for companies to compete in the market. The main problem at this step is to assign the operations necessary to manufacture a product to different workstations while respecting all constraints (i.e., the line balancing problem). The aim is to minimize the cost of this line while ensuring a desired production rate. After a review of the existing types of automated machining lines, an illustration of a developed methodology for line configuration is given using an industrial case study of a flexible and reconfigurable transfer line.

Large-scale complex systems (LSS)

large-scale complex system (LSS)

have traditionally been characterized by large numbers of variables, structure of interconnected subsystems, and other features that complicate the control models such as nonlinearities, time delays, and uncertainties. The decomposition of LSS into smaller, more manageable subsystems allowed for implementing effective decentralization and coordination mechanisms. The last decade revealed new characteristic features of LSS such as the networked structure, enhanced geographical distribution and increased cooperation of subsystems, evolutionary development, and higher risk sensitivity. This chapter aims to present a balanced review of several traditional well-established methods and new approaches together with typical applications. First the hierarchical systems approach is described and the transition from coordinated control to collaborative schemes is highlighted. Three subclasses of methods that are widely utilized in LSS – decentralized control, simulation-based, and artificial-intelligence-based schemes – are then reviewed. Several basic aspects of decision support systems (DSS)

decision support system (DSS)

that are meant to enable effective cooperation between man and machine and among the humans in charge with LSS management and control are briefly exposed. The chapter concludes by presenting several technology trends in LSS.

This chapter

computer-aided

design (CAD)

design

computer-aided

computer-aided

engineering

is an overview of computer-aided design (CAD) and computer-aided engineering and includes elements of computer graphics, animation, and visualization. Commercial brands of three-dimensional (3-D) modeling tools are dimension driven, parametric, feature based, and constraint based all at the same time. The term

constraint-based

is intended to include all of these many facets. This means that, when geometry is created, the user specifies numerical values and requisite geometric conditions for the elemental dimensional and geometric constraints that define the object. Many of todayʼs modern CAD tools also operate on similar interfaces with similar geometry-creation command sequences [

37.1

] that operate interdependently to control the modeling process. Core modules include the sketcher, the solid

solid modeling

modeling system itself, the dimensional constraint engine, the feature manager, and the assembly manager [

37.2

]. In most cases, there is also a drawing tool, and other modules that interface with analysis, manufacturing process planning, and machining. The 3-D animation production process can be divided into three main phases:

Concept development and preproduction

Production

Postproduction and delivery.

These processes can begin with the 3-D geometry generated by CAD systems in the design process or 3-D models can be created as a separate process. The second half of the chapter explains the process commonly used to create animations and visualizations.

Design automation

computer-aided

design (CAD)

design

computer-aided

or computer-aided design (CAD) for microelectronic circuits has emerged since

integrated circuits (IC)

the creation of integrated circuits (IC). It has played a crucial role to enable the rapid development of hardware and software systems in the past several decades. CAD techniques are the key driving forces behind the reduction of circuit design time and the optimization of circuit quality. Meanwhile, the exponential growth of circuit capacity driven by Mooreʼs law prompts new and critical challenges for CAD techniques. Mooreʼs law describes an important trend in the history of the semiconductor industry: that the number of transistors per unit chip area would be doubled approximately every 2 years. This observation was first made by Intel co-founder Gordon E. Moore in a paper in 1965. Mooreʼs law has held true for the past four decades, and many people believe that it will continue to apply for at least another decade before reaching the fundamental physical limits of device fabrication.

In this chapter we will introduce the fundamentals of design automation as an engineering field. We begin with several important processor technologies and several existing IC technologies. We then present a typical CAD flow covering all the major steps in the design cycle. We also cover some important topics such as verification and technology computer-aided design (TCAD). Finally, we introduce some new trends in design automation.

Automated systems can provide tremendous benefits to users; however, there are also potential hazards that users must be aware of to safely operate and interact with them. To address this need, safety warnings are often provided to operators and others who might be placed at risk by the system. This chapter discusses some of the roles safety warnings can play in automated systems, from both the traditional perspective of warnings as a form of hazard control and the perspective of warnings as a form of automation. During this discussion, the chapter addresses some of the types of warnings that might be used, along with issues and challenges related to warning effectiveness. Design recommendations and guidelines are also presented.

The future of any investment project is undeniably linked to its economic rationalization. The chance that a project is realized depends on our ability to demonstrate the benefits that it can convey to a company. However, traditional investment evaluation must be enhanced and used carefully in the context of rationalization to reflect adequately the characteristics of modern automation systems. Nowadays automation systems often take the form of complex, strongly related autonomous systems that are able to operate in a coordinated fashion in distributed environments. Reconfigurability is a key factor affecting automation systemsʼ economic evaluation due to the reusability of equipment and software for the manufacturing of several products. A new method based on an analytical hierarchy process for project selection is reviewed. A brief discussion on risk and salvage consideration is included, as are aspects needing further development in future rationalization techniques.

Quality of service (QoS) of

quality of service (QoS)

automation involves issues of cost, affordability, energy, maintenance, and dependability. This chapter focuses on cost, affordability, and energy. (The next chapter addresses the other aspects.) Cost-effective or cost-oriented automation is part of a strategy called

low-cost automation

. It considers the life cycle of an automation system with respect to their owners: design, production, operating, and maintenance, refitting or recycling.

Affordable automation

is

lifecycle

cost

affordable automation

another part of the strategy. It considers automation or automatic control in small enterprises to enhance their competitiveness in manufacturing and service. Despite relative expensive components the automation system can be cheap with respect to operation and maintenance. As examples are discussed: numerical controls of machine tools; shop floor control with distributed information processing; programmable logic controllers (PLCs) shifting to general-purpose (PC); smart devices, i.e. information processing integrated in sensors and actuators; and distributed manufacturing, and maintenance.

Energy saving

energy saving

can be supported by automatic control of consumption in households, office buildings, plants, and transport.

Energy intensity

is decreasing in most developing countries, caused by changing habits of people and by new control strategies. Centralized generation of electrical energy has advantages in terms of economies of scale, but also wastes energy. Decentralized generation of electricity and heat in regional or local units are of advantage. A combination of wind energy, solar energy, hydropower, energy from biomass, and fossil fuel in small units could provide electrical energy and heat in regions isolated from grids. These hybrid energy concepts are demanding advanced, but low-cost, controls.

Within the last 20 years, digital automation has increasingly taken over manual control

reliability

functions in manufacturing plants, as well as in products. With this shift, reliability,

safety

maintainability

maintainability, and safety responsibilities formerly delegated to skilled human operators have increasingly shifted to automation systems that now

close the loop

. In order to design highly

dependable

automation systems, the original concept of design for reliability has been refined and greatly expanded to include new engineering concepts such as availability, safety, maintainability, and survivability. Technical definitions for these terms are provided in this chapter, as well as an overview of engineering methods that have been used to achieve these properties. Current standards and industrial

dependable system

practice in the design of dependable systems are noted. The integration of dependable automation systems in multilevel architectures has also evolved greatly, and new concepts of control and monitoring, remote

remote

diagnostics

software

safety

diagnostics, software safety, and automated reconfigurability are described. An extended example of the role of dependable automation systems at the

enterprise level

is also provided. Finally, recent research trends, such as automated verification, are cited, and many citations from the extensive literature on this topic are provided.

The closed-loop

embedded

information device

information device

embedded

lifecycle

management

product lifecycle management (PLM)

product lifecycle management (PLM) system focuses on tracking and managing the information of the whole product lifecycle, with possible feedback of information to product lifecycle phases. It provides opportunities to reduce the inefficiency of lifecycle operations and gain competitiveness. Thanks to the advent of hardware and software related to product identification technologies, e.g., radiofrequency identification (RFID) technology, recently closed-loop PLM has been highlighted as a tool of companies to enhance the performance of their business models. However, implementing the PLM system requires a high level of coordination and integration. In this chapter we present the background methodologies and techniques and the main components for closed-loop PLM and how they are related to each other. We start with the concept of closed-loop PLM and a system architecture in Sect.

43.1

. In Sect.

43.2

we describe the necessary components for closed-loop PLM and how to integrate and coordinate them with respect to business models, hardware, and software. In Sect.

43.3

we propose a development guide based on experiences gathered from prototype applications developed to date. In Sect.

43.4

we introduce a real case example that implements a closed-loop PLM solution focusing on end-of-life (EOL) of vehicles (ELV). Finally, Sect.

43.5

discusses some challenging issues and emerging trends in the implementation of closed-loop PLM.

Engineering education has seen an explosion of interest in recent years,

qualification

education

fueled simultaneously by reports from both industry and academia. Automatic control education has recently become a core issue for the international control community. This has occurred in tandem with the explosion of interest in engineering education as a whole. The applications of control are growing rapidly. There is an increasing interest in control from researchers from outside of traditionally control-based fields such as aeronautics, chemical, mechanical, and electrical engineering. Recently control and systems theory have had much to offer to nontraditional control fields such as biology, biomedicine, finance, actuarial science, and the social sciences as well as transportation and telecommunications networks. Complementary, innovative developments of control and systems theory have been motivated and inspired by complex real-world problems. These new developments present huge challenges in control education. Meeting these challenges will require a multifaceted approach by the control community that includes new approaches to teaching, new preparations for facing new theoretical control and systems theory problems, and a critical review of the status quo. This chapter discusses these new challenges as well as new approaches to education and outreach. This chapter starts by presenting an argument towards the future of controls as the application of control theory expands into new and unique disciplines. It provides two case studies of nontraditional areas where control theory has been applied: finance and biomedicine. These two case studies show a high potential for using powerful fundamental principles and tools of automatic control in research with an interdisciplinary nature. The chapter then outlines current and future

science, technology, engineering, and mathematics (STEM)

pedagogical approaches being employed in control education, particularly introductory courses, around the world. It concludes with a discussion about the role of scholarship, teaching, and learning in control education both now and in the coming years.

This chapter is an introduction to

software management

software management

automation

software management in the context of automation. It recognizes how software and automation are intertwined and have been mutually enabling in enhancing the reach and seemingly unimaginable applications of these two disciplines. It further identifies software engineering as application of various tools, techniques, methodologies, and disciplines to produce and maintain an automated solution to a problem and how software management plays a central role in making it possible. We recognize that software must be managed like any other corporate or organizational resource albeit as a virtual rather than an actual or tangible entity. In this chapter we restrict ourselves to three crucial issues of software management in the context of software as a component in automation and how it enhances its value and availability by effective software distribution, asset management, and cost estimation. It presents current best practices in software automation, distribution, asset management, and cost estimation.

This chapter specifies equipment-based control system structures for complex and integrated systems and describes the approach to and implementation of an equipment-based control strategy. Based on a view of subsystems in a production, process or a single machine the control system has to abstract the subunits in an object-oriented manner to obtain their methods and properties. The base subunits will run as separate state machines (either on centralized or decentralized control devices) representing themselves to the next control hierarchy level only by said methods and properties. These base subunits form functional subsystems in the same way.

Advantages of such a modular specification are: easy replacement of different base units with the same functionality to the next hierarchy level, high efficiency in construction kit engineering of systems, easy integration of systems to vertical integration attempts – especially in the field of networking and data concentration. The challenge is the implementation on standard industrial programmable logic controller (PLC) systems with a standard industrial-like programming language (e.g., EN 61131). An example demonstrates the implementation in a modern test stand for heat meters for the German Physikalisch-Technische Bundesanstalt (PTB) institute, a system with about 1000 physical input/output (I/O) and measurement points.

Should we trust automation? Can automation cause harm to individuals and to society? Can individuals apply automation to harm other individuals? The answers are yes; hence, ethical issues are deeply associated with automation. The purpose of this chapter is to provide some ethical background and guidance to automation professionals and students. Governmental action and economic factors are increasingly resulting in more global interactions and competition for jobs requiring lower-end skills as well as those that are higher-end endeavors such as research. Moreover, as the Internet continually eliminates geographic boundaries, the concept of doing business within a single country is giving way to companies and organizations focusing on serving and competing in international frameworks and a global marketplace. Coupled with the superfluous nature of an Internet-driven social culture, the globally-distributed digitalization of work, services and products, and the reorganization of work processes across many organizations have resulted in ethically challenging questions that are not just economically, or socially sensitive, but also highly culturally sensitive. Like the shifting of commodity manufacturing jobs in the late 1900s, standardization of information technology and engineering jobs have also accelerated the prospect of services and jobs more easily moved across the globe, thereby driving a need for innovation in design, and in the creation of higher-skill jobs. In this chapter, we review the fundamental concepts of ethics as it relates to automation, and then focus on the impacts of automation and their significance in both education and research.

Numerical control (NC)

numerical control (NC)

is the greatest innovation in the achievement of machine tool automation in manufacturing. In this chapter, first a history of the development up to the advent of NC machine tools is briefly reviewed (Sect.

48.1

). Then the machining centers and the turning centers are described with their key modules and integration into flexible manufacturing systems (FMS)

flexible

manufacturing system (FMS)

manufacturing system

and flexible manufacturing cells (FMC)

flexible

manufacturing cell (FMC)

in Sect.

48.2

. NC part programming is described from manual programming to the computer-aided manufacturing (CAM) system in Sect.

48.3

. In Sect.

48.4

and Sect.

48.5

, following the technical innovations in the advanced hardware and software systems of NC machine tools, future control systems for intelligent CNC machine tools are presented.

Advances in the Internet, communication technologies, and computation power have accelerated the cycle of new product development as well as supply chain efficiency in an unprecedented manner. Digital technology provides not only an important means for the optimization of production efficiency through simulations prior to the start of actual operations but also facilitates manufacturing process automation through efficient and effective automatic tracking of production data from the flow of materials, finished goods, and people, to the movement of equipment and assets in the value chain. There are two major applications of digital technology in manufacturing. The first deals with the modeling, simulation, and visualization of manufacturing systems and the second deals with the automatic acquisition, retrieval, and processing of manufacturing data used in the supply chain. This chapter summarizes the state of the art of digital manufacturing which is based on virtual

virtual manufacturing (VM)

manufacturing

virtual

manufacturing (VM) simulation and radio frequency identification (RFID)-based automation. The associated technologies, their key techniques, and current research work are highlighted. In addition, the social and technological obstacles to the development of a VM system and in an RFID-based manufacturing process automation system, and some practical application case studies of digital manufacturing based on VM and RFID-based automation, are also discussed.

Flexible

flexible

assembly

precision

assembly

assembly refers to an assembly system that can build multiple similar products with little or no reconfiguration of the assembly system. It can serve as a case study for some of the emerging applications in flexible automation. A truly flexible assembly system should include flexible part feeding, grasping, and fixturing as well as a variety of mating and fastening processes that can be quickly added or deleted without costly engineering. There is a limited science base for how to design flexible assembly systems in a manner that will yield predictable and reliable throughputs. The emergence of geometric modeling systems (computer-aided design, CAD) has enabled work in geometric reasoning in the last few years. Geometric models have been applied in areas such as machine vision for object recognition, design and throughput analysis of flexible part feeders, and dynamic simulation of assembly stations and assembly lines. Still lacking are useful techniques for automatic model generation, planning, error representation, and error recovery. Future software architectures for flexible automation should include geometric modeling and reasoning capabilities to support autonomous, sensor-driven systems.

Increasingly the manufacturing of complex products and component parts involves significant automation functions. This chapter describes a cross section of automated manufacturing systems used to fabricate, inspect, and assemble aircraft. Aircraft manufacturing cost reductions were made possible by development of advanced technologies and applied automation to produce high-quality products, make air transportation affordable, and improve the standard of living for people around the globe. Fabrication and assembly of a commercial aircraft involve a variety of detail part fabrication and assembly operations. Fuselage assembly involves riveting/fastening operations at five major assembly levels. The wing has three major levels of assembly. The propulsion systems, landing gear, interiors, and several other electrical, hydraulic, and pneumatic systems are installed to complete the aircraft structurally and, after functional tests, it normally gets painted and goes to the flight ramp for final customer acceptance checks and delivery. Aircraft manufacturing techniques are well developed, fabrication and assembly processes follow a defined sequence, and process parameters for manual and mechanized/automated manufacturing are precisely controlled. Process steps are inspected and documented to meet the established Federal Aviation Administration quality requirements, ensuring reliable functions of components, structures, and systems, which result in dependable aircraft performance.

We review automation requirements and technologies for semiconductor manufacturing. We first discuss equipment integration architectures and control to meet automation requirements for modern fabs. We explain tool architectures and operational issues for modern integrated tools such as cluster tools, which combine several processing modules with wafer-handling robots. We then review recent progress in tool science for scheduling and control of integrated tools and discuss control software architecture, design, and development for integrated tools. Next, we discuss requirements and technologies in fab integration architectures and operation such as modern fab architectures and automated material-handling systems, communication architecture and networking, fab control application integration, and fab control and management.

This chapter reports the key developments for nanomanufacturing automation. Automated CAD guided nanoassembly can be performed by an improved atomic force microscopy (AFM).

atomic force microscopy (AFM)

Although CAD guided automated manufacturing has been widely studied in the macro-world, nanomanufacturing is challenging. In nanoenvironments, the nanoobjects are usually distributed on a substrate randomly, so the nanoenvironment and the available nanoobjects have to be modeled in order to design a feasible nanostructure. Because of the positioning errors due to the random drift, the actual position of each nanoobject has to be identified by our local scanning method. The advancement of AFM increases the efficiency and accuracy to manipulate and assemble nanoobjects. Besides, the manufacturing process of carbon nanotube (CNT)

carbon nanotube (CNT)

based nanodevices is discussed. A novel automated manufacturing system has been especially designed for manufacturing nanodevices. The system integrates a new dielectrophoretic (DEP)

dielectrophoretic (DEP)

microchamber into a robotic based deposition workstation and increases the yield to form semi-conducting CNTs for manufacturing nanodevices. Therefore, by using the proposed CNT separation and deposition system, CNT based nanodevices with specific and consistent electronic properties can be manufactured automatically and effectively.

To effectively manage a supply chain it is necessary to coordinate the flow of materials and information both within and among companies. This flow goes from suppliers to consumers, as it passes through manufacturers, wholesalers, and retailers. While materials and information move through the supply chain, automation is used in a variety of forms and levels as a way to raise productivity, enhance product quality, decrease labor costs, improve safety, and even to perform tasks that go beyond the precision and reliability of humans. A rapid development in information technology has transformed not only the way people work and interact with each other; electronic media enable enterprises to collaborate on their work and missions within each organization and with other independent enterprises, including suppliers and customers.

Within this chapter, the focus is on the main benefits of automation in production, supply, logistics, and distribution environments. The first Section centers on machines and equipment automation for production. The second section focuses on computing/communication automation for planning and operations decisions. Finally, the last section highlights some considerations regarding economics, productivity, and flexibility important to bear in mind while designing an automation strategy.

This

warehouse

system

chapter presents material handling automation for production and warehouse management systems that process: receipt of parts from vendors, handling of parts in production lines, and storing and shipping in warehouses or distribution centers. With recent advancements in information interface technology, innovative system design technology, and intelligent system control technology, more sophisticated systems are being adopted to enhance the productivity of material handling systems. Information interface technology utilizing wireless devices such as radiofrequency identification (RFID) tags and mobile personal computers significantly simplifies information tracking, and provides more accurate data, which enables the development of more reliable systems for material handling automation. Highly flexible and efficient automated material handling systems have been newly designed for various applications in many industries. Recently these systems have been connected into large-scale integrated automated material handling systems (IAMHS) that create synergy with material handling automation by proving speedy and robust infrastructures. As a benefit of high-level material handling automation, the modern supply chain management (SCM) successfully synchronizes sales, procurement, and production in enterprises.

This

communication

network

network

communication

chapter discusses a very relevant aspect in modern automation systems: the presence of industrial

industrial communication

industrial communication

protocols

communication networks and their protocols. The introduction of Fieldbus systems has been associated with a change of paradigm to deploy distributed industrial automation systems, emphasizing device autonomy and decentralized decision making and control loops. The chapter presents the main wired and wireless industrial protocols used in industrial automation, manufacturing, and process control applications. In order to help readers to better understand the differences between industrial communication protocols and protocols used in general computer networking, the chapter also discusses the specific requirements of industrial applications. As the trend of future automation systems is to incorporate complex heterogeneous networks, consisting of (partially homogeneous) local and wide area

virtual automation network (VAN)

as well as wired and wireless communication systems, the concept of virtual automation networks is presented

Mines and mineral processing plants need integrated process control systems capable of improving plant-wide efficiency and productivity. Mining automation systems today typically control fixed plant equipment such as pumps, fans, and phone systems. Much work is underway around the world in attempting to create the moveable equivalent of the manufacturing assembly line for mining. This technology has the goals of speeding production, improving safety, and reducing costs. Process automation systems in mineral processing plants provide important plant operational information such as metallurgical accounting, mass balances, production management, process control, and optimization. This chapter discusses robotics and automation for mining and process control in mineral processing. Teleoperation of mining equipment and control strategies for grinding and flotation serve as examples of current development of field.

Plant automation

paper

industry

wood industry

in the

timber (wood) industry

and

paper industry

has many analogies due to the similar process characteristics, i.e., hybrid process. From a plant automation point of view these industries are challenging because of their technical requirements. The USA is the largest producer of paper and paperboard. In a census by the America Census Bureau, the paper industry is placed 7 among 21 different industry groups, with 6% of the total value of product shipments for the years 2005 and 2006 [

58.1

]. China, as the second largest paper producer after the USA, is expecting a growth rate of 12.4% per annum (for the forecast from 1990 to 2010) [

58.2

]. The German woodworking machinery sector, with more than 26% of the world market share, had a € 3.4 billion turnover in 2006 and 72% export quota [

58.3

]. In 2006, the German print and paper industry grew by more than 7%, to € 8.5 billion and more than 84% export quota ([

58.4

], more details in [

58.5

]). This chapter will not only highlight the specific requirements from a technical point of view but also from the marketing point of view. Observations from these two points of view will lead to a heterogeneous automation system with proprietary devices for real-time and machinery-safety-related tasks, and standard devices for the rest. Both industries belong to plant manufacturing industries with their typical business characteristics. Automation in this field is technology driven and its importance is growing because more functionalities are being implemented using automation software to increase systems flexibility. The interface from automation level to enterprise resource planning (ERP) systems is being standardized in international manufacturing companies. Engineering is the key factor for improvement that needs to be considered in the coming years, and therefore also modularity and reusability where applicable.

This Chapter

welding

automation

focuses on automation of welding processes that are commonly used in industry for joining metals, thermoplastics, and composite materials. It includes a brief review of the most important welding techniques, welding equipment and power sources, sensors, manipulating devices, and controllers. Particular emphasis is given to monitoring and control strategies, seam-tracking methods, integration of welding equipment with robotic manipulators, computer-based control architectures, and offline programming of robotic welding systems. Application examples demonstrating state-of-the-art and recent advances in robot-based welding are also presented. Conclusions define next challenges and future trends in enhancing of welding technology and its automation potential, modeling and control of welding processes, development of welding equipment and dedicated robotic manipulators, automation of robot programming and process planning, human–machine interfaces, and integration of the automated robotic stations within the global production system.

Factory-based

food processing

food production and processing globally forms one of the largest economic and employment sectors. Within it, current automation and engineering practice is highly variable, ranging from completely manual operations to the use of the most advanced manufacturing systems. Yet overall there is a general lag in the use of automation technology compared with other industries. There are many reasons for this lack of uptake and this chapter will initially discuss the factors that make automation of food production so essential and at the same time consider counterinfluences that have prevented this automation uptake.

In particular the chapter will focus on the diversity of an industry covering areas such as bakery, dairy, confectionary, snacks, meat, poultry, seafood, produce, sauce/condiments, frozen, and refrigerated products, which means that generic solutions are often (considered by the industry) difficult or impossible to obtain. However, it will be shown that there are many features in the production process that are almost completely generic, such as labeling, quality/safety automation, and palletization, and others that do in fact require an almost unique approach due to the natural and highly variable features of food products. In considering these needs, this chapter has therefore approached the specific automation requirements of food production from two perspectives. Firstly, it will be shown that in many cases there are generic automation solutions that could be valuably used across the industry ranging from small cottage facilities to large multinational manufacturers. Examples of generic types of automation well suited across the industry will be provided. In addition, for some very specific difficult handling operations, customized solutions will be shown to give opportunities to study the problems/risks/demands associated with food handling and to provide an insight into the solution, thereby demonstrating that in most instances the difficult/impossible can indeed be achieved.

The construction industry is labor intensive, project based, and slow to adopt emerging technologies. Combined, these factors make the construction industry not only one of the most dangerous industries worldwide, but also prone to low productivity and cost overruns due to shortages of skilled labor, unexpected site conditions, design changes, communication problems, constructability challenges, and unsuitability of construction means and techniques. Construction automation emerged to overcome these issues, since it has the potential to capitalize on increasing quality expectations from customers, tighter safety regulations, greater attention to computerized project control, and technological breakthroughs led by equipment manufacturers. Today, many construction operations have incorporated automated equipment, means, and methods into their regular practices.

The Introduction to this chapter provides an overview of construction automation, highlighting the contribution from robotics. Several motivations for automating construction operations are discussed in Sect.

61.1

, and a historical background is included in Sect.

61.2

. A description of automation in horizontal construction is included in Sect.

61.3

, followed by an overview of building construction automation in Sect.

61.4

. Some techniques and guidelines for construction management automation are discussed in Sect.

61.5

, which also presents several emerging trends. Section

61.6

shows some typical application examples in todayʼs construction environment. Finally, Sect.

61.7

briefly draws conclusions and points out challenges for the adoption of construction automation.

Buildings account for a large fraction of global energy use and have a correspondingly significant impact on the environment. Buildings are also ubiquitous in virtually every aspect of our lives from where we work, live, learn, govern, heal, and worship, to where we play. The application of control and automation to buildings can lead to significant energy savings, improved health and safety of occupants, and enhance life quality. The aim of this chapter is to describe what makes buildings smart, provide examples of common control strategies, and highlight emerging trends and open challenges. Today, the most prevalent use of automation in buildings is in heating, ventilating, and air-conditioning (HVAC)

heating, ventilating, and air-conditioning (HVAC)

systems. This chapter reviews common control and automation methods for HVAC, but also describes how automation is being extended to other building processes. The number of controllable and interconnected systems is increasing in modern buildings and this is creating new opportunities for the application of automation to coordinate and manage operation. However, the chapter draws attention to the fact that the buildings industry is very large, fragmented, and cost-oriented, with significant economic and technical barriers that can, in some cases, impede the adoption and wide-scale deployment of new

smart

building

automation technologies.

The complex agricultural environment combined with intensive production requires development of robust systems with short development time at low cost. The unstructured nature of the external environment increases chances of failure. Moreover, the machines are usually operated by low-tech personnel. Therefore, inherent safety and reliability is an important feature. Food safety is also an issue requiring the automated systems to be sanitized and reliable against leakage of contaminations. This chapter reviews agricultural automation systems including field machinery, irrigation systems, greenhouse automation, animal automation systems, and automation of fruit production systems. Each section describes the different automation systems with many application examples and recent advances in the field.

Many factories,

control system

feed plant

automated

especially in developing countries, still use old technology and control systems. Some of them are forced to replace at least the control and supervising system in order to increase their productivity. This chapter presents a modern solution for updating the control system of a fodder-producing factory without replacing the field devices or the infrastructure. The automation system was chosen in order to allow correct control of the whole plant, using a single programmable logic controller (PLC). Structure and design of the software project is described. Also, several interesting software solutions for managing special processes such as material extraction and weighing machines calibration are presented. Production quality results and future development are also discussed. In the last part of the chapter some guidelines for automation of a chicken-growing plant are presented.

Automation

electrical power system

in power systems has a very long tradition. Just recall the flyball governor in a steam engine and it becomes clear that power people have been using control principles and instruments for more than a century. There are, however, new challenges in power generation and transmission concerning the security and efficiency of those services that require the attentions of both theoreticians and practitioners. These challenges are the subject of this chapter. The power failures that affect large grids from time to time show that system collapses are not simply a subject of academic debate. Power network operating reliability has become an issue that any country must make a top priority. The reliability of a power system depends for the most part on the quality of the decisions made, both automatically and manually. The term

power system

is very broad, and we focus here on the power system backbone, electric power transmission, and its operational reliability, particularly when automatic control plays a vital role. The content of the chapter remains interdisciplinary, spanning power systems, automation and economy, as changes resulting from the opening of the markets and permanent power system restructuring affect its operation.

Presently

vehicle

road automation

vehicle

automation

in the USA, Europe, Japan, and in other parts of the world, intelligent transportation system (ITS) technologies are being developed and deployed to increase the

intelligence

of vehicles. The two key benefits of these technologies are enhancement of safety and mobility of the traveling public. The

intelligence

is provided by electronics, communications systems, software, and human–machine interfaces and is assisting drivers with many aspects of the driving task. Drivers may be warned about potential crashes with other cars, about objects that are hidden from their vantage point, and about excessive speeds. Information about real-time traffic conditions including incidents on a driverʼs preferred route, travel times to specific destinations, and about restaurants, hotels, and other destination points may be provided. In-vehicle navigation systems can tell drivers how to get to a destination on a turn-by-turn basis and may be linked to a central dispatch center to summon help automatically in case of an accident.

The major initiatives and technologies being developed in the USA – integrated vehicle-based safety systems, forward collision warning systems, road departure crash warning systems, vehicle infrastructure integration – are described and discussed in this chapter. In addition, how they interact with the driver is important in terms of safety, liability, and acceptance of the technologies. The human factors elements that should be considered are presented and discussed in the chapter as well.

The air transportation system infrastructure is comprised of communication, navigation, surveillance, and air traffic management systems, and is known as the National Airspace System. This chapter describes the current very high-frequency and high-frequency modes of communication, very high-frequency omnidirectional range, distance measuring equipment, and instrument landing systems for navigation/guidance to the aircraft, and primary, as well as secondary radars, for surveillance. The two primary functions of the ground-based air traffic management system, viz. traffic flow management for strategic air traffic planning and air traffic control for safe movement of aircraft, are discussed in detail. This chapter also addresses the limited role of automation in both the aircraft cockpit and the ground-based air traffic management system.

A review

flight deck

automation

automation

flight deck

of flight deck automation is provided with an emphasis on examples and design principles. First, a review of historical developments in flight deck automation is provided. Current examples of control automation, warning and alerting systems, and information automation are then provided. A discussion of human factors, integration, safety, and certification issues are then discussed. The chapter provides guidance to managers, engineers, and researchers tasked with studying or building flight deck systems. In particular, the chapter provides an appreciation of the challenges of building such systems, and the challenges facing those who will build the flight decks of the future.

Space-faring nations are actively exploring outer space and planetary bodies in our solar system both individually and as collaborators with

exploration automation

other nations. In most endeavors, the inherent risk to human life has been mitigated by the use of automation and robotics to conduct space missions. Missions extending from low-Earth orbit to Earthʼs moon and beyond to destinations throughout the solar system have been successfully conducted. Robots and human astronauts assisted by automated systems have been used on space missions. Infrastructure and service automation in the context of space missions are discussed in this chapter. Automation and robotics have played a substantial role in installing space exploration infrastructure such as Earth-orbiting satellites and space stations occupied for extended periods by astronauts as well as satellites that operate for extended periods in orbit around other planets. General background information about automation and robotics for exploration of space is presented. Challenges of applying automation in space and planetary environments are highlighted for robots that operate in Earth orbit, at the Moon, at Mars, and other destinations. A look forward to what the future will hold for further space and exploration automation is provided, including mention of advancements in technological capabilities that will be needed to accomplish more ambitious space missions.

The potential applications of automation for cleaning are many and diverse. All over the world, research organizations and companies are developing automatic cleaning systems [

70.1

]. Products such as automatic floor

robot

cleaning

cleaning robots and floor vacuum cleaners available for household use are sold ten thousand times over every year at prices below US $300 (Fig.

70.1

). While versatile, high-performance systems exist for other applications such as professional floor cleaning, airplane washing, ship cleaning, and facade cleaning, they are by no means as widespread as household systems.

Fig. 70.1

iRobot Roomba

Automatic cleaning systems are frequently extremely complex robot systems that operate autonomously in unstructured environments or outdoor areas. Cleaning automation not only incorporates cleaning engineering but also a variety of other technical disciplines, e.g., autonomous power supply, sensor systems, environment modeling, and path planning in dynamic environments.

Some examples of automatic cleaning systems for floors, facades, swimming pools, ventilation ducts, and sewer lines serve to highlight the current potential of cleaning automation and provide a glimpse of future developments.

While the information services industry dates back to the 15th century AD, the information technology services is as young as 60 years. Yet the pace at which both have grown is phenomenal, and this is tied to the evolution of computer technology. Networking of computers and people through the Internet has moved into high gear. It has also given birth to multiple business segments in the process. Delivery of data and information, data processing, business process outsourcing, analytics, and printing and display solutions are the five segments identified within the information services. Computer-aided software engineering, independent software testing and quality assurance, package and bespoke software implementation and maintenance, network and security management, and hosting and infrastructure management are covered as segments within information technology services. The automation path of each segment is reviewed in detail. An impact analysis to identify the changing landscape is described. Finally current trends are traced, followed by predictions for future developments.

Library automation has a rich history of 130 years of development, from the standardization

machine-readable cataloging (MARC)

of card catalogs to the creation of the machine-readable cataloging (MARC) communications format and bibliographic utilities. Beginning in the early 1980s university libraries and

integrated library system (ILS)

library automation vendors pioneered the first integrated library systems (ILS). The digital era, characterized by the proliferation of content in electronic format, brought with it the development of services for casual users as well as scholarly researchers — services such as OpenURL linking and metasearching and library staff tools such as electronic resource management systems. Libraries are now reacting to user demands for quick, easy, and effective discovery and delivery such as those they have grown accustomed to through the use of Google and other Internet heavyweights, by developing a new

discovery to delivery (D2D)

series of Library 2.0-based discovery-to-delivery (D2D) applications. These newest offerings deliver an up-to-date user experience, allowing libraries to retain their back-office systems (e.g., acquisitions, cataloging, circulation) and add to or replace them as needed. In the process libraries can leverage Web 2.0 services to interconnect systems from different vendors and thereby ensure a gradual transition toward a new automation platform.

In

serious games

this chapter, we present the theoretical underpinnings of and conditions

immersive learning

for learning through experiences gained

simulation

in

immersive learning simulations

(or simply

gaming

) and show some examples of authentic learning experiences for business professionals. We argue that recent developments in the theory of knowledge acquisition coupled with changes in the educational landscape (e.g., the proliferation of online courses and programs) present an unrivalled and so far mostly unexploited opportunity for serious games. The examples presented are from using Managerial Enterprise Resource Planning (MERP) in a variety of MBA and corporate business training programs. Related examples of other virtual learning environments are also included.

A service robot has to be intelligent, mobile, and able to cooperate with other robots and devices. We are on the way towards multirobot systems in which several robots, called multiagent systems (MAS), will act in

multiagent system (MAS)

a cooperative way together a common task. One of the newest application areas of service robots and especially MAS is the field of entertainment, leisure, and hobby. People have more free time, and modern information technologies lead to loneliness of humans (teleworking, telebanking, teleshopping, etc.). Entertainment robots are expected to be one of the real frontiers of the next decade.

In this chapter a short description of such robots will be given, including some application examples. Due to the broad range of possible applications of robots in entertainment, leisure, and hobby, the following classification has been made in order to give this contribution a basic structure: robot construction sets, sports assistants, promotion and public relations, robots in the entertainment industry, personal robots, humanoid robots, and competition robots.

As an example, robot soccer competitions will be described in more detail. Finally an outlook on future development trends will be given.

The reductionist approaches of molecular and cellular biology have produced revolutionary advances in our understanding of biological function and information processing. The difficulty associated with relating molecular components to their systemic function led to the development of systems biology, a relatively new field that aims to establish a bridge between molecular level information and systems level understanding. The novelty of systems biology lies in the emphasis on analyzing complexity in networked biological systems using integrative rather than reductionist approaches. By its very nature, systems biology is a highly interdisciplinary field that requires the effective collaboration of scientists and engineers with different technical backgrounds, and the interdisciplinary training of students to meet the rapidly evolving needs of academia, industry, and government. This chapter summarizes state-of-the-art developments of automatic control in systems biology with substantial theoretical background and illustrative examples.

Biomedical systems

biomedical

system

are a complex collection of case studies where the principles of automation and control theory are seeing increased application. This growing interest has a twofold motivation: the need for advanced automation and treatment design tools for use in medical practice and the challenges inherent to biomedical systems and clinical deployment of technology. This chapter provides an overview of the automation, control, and optimization tools used in the biomedical arena. While the scope of potential applications is vast, examples of biomedical treatment design systems for cancer and insulin-dependent diabetes are discussed. The chapter concludes by scratching the surface of emerging areas in need of translated or novel systems and automation tools.

Healthcare is a complex industry, but yet it lags behind virtually all others in automation and use of

information technology (IT)

information technology (IT). For healthcare, technology serves as an untapped catalyst for higher efficiency, lower cost and broader access to care. The appropriate application can minimize medical errors, promote better management of chronic illness, and enable clinicians to intervene earlier and anticipate prognosis. Additionally, medical informatics provides the tools to generate new insights about both individuals and entire populations through data analysis and visualization. These systems can also be used in support of continuous quality improvement efforts as well as to reduce inefficiencies. While significant strides have been made in the implementation of medical informatics, there are numerous challenges to resolve before we will be able to realize the full benefits of healthcare IT.

Robotic systems that are integrated in medical applications are designed to help and assist rather than injure a human being, whether it is the patient or the operator. This chapter presents the classification of medical robots as passive, semiactive, active, remote manipulators, and navigators. The kinematic structure of medical robots is discussed next, as are the fundamental requirements from medical robots. Finally, the main advantages and emerging trends in medical robotics are given.

The left ventricular assist device (LVAD)

left ventricular assist device (LVAD)

is a mechanical device implanted in patients with congestive heart failure to assist the heart in pumping blood through the circulatory system. The latest generation of this device is comprised of a rotary pump which is generally much smaller, lighter, and quieter than the first-generation conventional pulsatile-type pump. The rotary pump is controlled by varying the rotor (or impeller) speed to adjust the amount of blood flow through the LVAD. If the patient is in a health care facility, the pump speed can be adjusted manually by a trained clinician to meet the patientʼs blood needs. However, an important challenge facing the increased use of these devices is the desire to allow the patient to return home. The development of an appropriate feedback controller that is capable of automatically adjusting the pump speed is therefore a crucial step in meeting this challenge. In addition to being able to adapt to changes in the patientʼs daily activities by automatically regulating the pump speed, the controller must also be able to prevent the occurrence of excessive pumping. This dangerous phenomenon, known as suction, may cause collapse of the ventricle and damage to the heart muscle. In order to be able to develop such a controller based on modern control theory an appropriate mathematical model of a combined cardiovascular system and LVAD must first be developed. In this chapter, we develop such a model. The model is dynamic, time-varying, and consists of six coupled nonlinear differential equations. The time variation occurs over four consecutive intervals representing the contraction, ejection, relaxation, and filling phases of the left ventricle. The LVAD in the model along with its inlet and outlet cannulae are represented by a nonlinear differential equation which relates the pump rotational speed and pump flow to the pressure difference across the pump. Suction is accounted for by adding a nonlinear resistance in the LVAD model when the pressure in the left ventricle drops below a specified threshold. Using this model we discuss some of the challenges faced in the development of: (1) an appropriate feedback controller for the LVAD, and (2) an effective algorithm for detection of suction in the left ventricle.

All of todayʼs patients receive healthcare services from a team of healthcare practitioners through various integrated medical information systems and automated systems. Due to the requirements of accuracy, safety, privacy, and responsiveness on healthcare services, medical informatics itself has become an important research field. This chapter intends to introduce medical informatics from the perspectives of (1) integration, (2) database and data warehouse, (3) individual medical support systems, and (4) medical knowledge and decision support systems. For integration, standard protocols (e.g., HL7, EDIFACT, and DICOM) are important connectivity agreements for hospital information system (HIS),

hospital information system (HIS)

medical support systems and healthcare equipment. For database and data warehouse, this chapter introduces the important concept of link relationships between data tables. The value of medical database and data warehouse relies on the correct link relationships. All modern healthcare organizations consist of multiple separated yet integrated systems. For individual medical support systems, this chapter introduces imaging, laboratory, hospital pharmacy, and nursing information systems. Evidence-based medicine and data mining techniques are two important fields in todayʼs medical knowledge and decision support systems. Finally, this chapter introduces how to strategically introduce healthcare information systems into a healthcare organization. Emerging issues of care quality, security, and public-use databases are also introduced.

This chapter is a review of the work in nanoelectronic detection of biological molecules and its applications in biology and medicine. About half of the chapter focuses on the methods employed to immobilize deoxyribonucleic acid (DNA) on solid substrates with particular focus on the electronic detection and characterization of DNA. Charge-transfer properties and theories are explained, as such electronic and electrical sensing of molecular-level interactions are very important in medical applications for rapid and cheap diagnosis.

A special tool called nanopore, which has been used extensively to characterize DNA, is then reviewed. A special distinction is made between the characteristics, capabilities, and impacts of the biological and the solid-state nanopores. Nanopores, when used in the ion current measurement setup, are used to measure the behavior of DNA as it traverses the nanopore. When the DNA traverses the pore, the blockage of the ion current is observed as a pulse. The statistical analysis of the pulses yields trends that are used to sort the DNA based on various properties. The nanopores are strong prototypes for biosensors, and have become a major experimental tool for investigating biophysical properties of double and single strands of DNA. The DNA sequence can potentially be determined by measuring how the forces on the DNA molecules, and the ion currents through the nanopore, change as the molecules pass through the nanopore.

Medical robotics includes assistive devices used by the physician in order to make his/her diagnostic or therapeutic practice easier and more efficient. This chapter focuses on such systems. It introduces the general field of computer-assisted medical interventions, its aims, and its different components, and describes the place of robots in this context. The evolution in terms of general design and control paradigms in the development of

medical

robot

robot

medical

medical robots are presented and issues specific to that application domain are discussed. A view of existing systems, ongoing developments, and future trends is given. A case study is detailed. Other types of robotic help in the medical environment exist (such as for assisting a handicapped person, for rehabilitation of a patient or for replacement of some damaged/suppressed limbs or organs) but are outside the scope of this chapter.

Home appliances, by their very nature, represent realizations of the principles of automation. Home appliances exist for the purpose of automating otherwise manual processes in the home. The operation of home appliances has been refined over the years, though the machine function has remained essentially the same. Advancements in the areas of microprocessor-based controls, sensors, displays, and interconnectivity, however, are enabling a new generation of appliances with advanced automation capabilities. Smart refrigerators, smart cooking appliances, and smart cleaning appliances are already appearing on the market. Along with these appliances we observe the viability of advanced applications in home automation. Software-based controls, appliance area networks (AANs), and display devices capable of creating a rich user experience are enabling advances in refrigeration automation, cooking integration automation, automated home utility management, automated fault and performance monitoring, and more. In this chapter we explore the enabling technologies and applications of advanced home appliance automation.

The

service

robot

automation for the disabled

disabled

increasing number of elderly people is resulting in increased demand for new solutions to support self-initiative and independent life. Robotics and automation technologies, initially applied in industrial environments only, are starting to move into our everyday lives to provide support and enhance the quality of our lives. This chapter analyzes the needs of disabled or limited persons and discusses possible tasks of new assistive service robots. It further gives an overview of existing solutions available as prototypes or products. Existing technologies to assist disabled or limited persons can be grouped into stand-alone devices operated by the user explicitly such as robotic walkers, wheelchairs, guidance robots or manipulation aids, and wearable devices that are attached to the user and operated implicitly by measuring the desired limb motion of the user such as in orthoses, exoskeletons or prostheses. Two recent developments are discussed in detail as application examples: the robotic home assistant Care-O-bot and the bionic robotic arm ISELLA. One of the most important challenges for future developments is to reduce costs in order to make assistive technologies available to everybody. On the technological side, user interfaces need to be designed that allow the use of the machines even by persons who have no technical knowledge and that enable new tasks to be taught to assistive robots without much effort. Finally, safe manipulation of assistive robots among humans must be guaranteed by new sensors and corresponding safety standards.

The information technology (IT) revolution which began in the latter half of the 20th century has brought great changes to education and learning. The spread of the Internet has made information ubiquitous, changing the emphasis of education from the transmission and

knowledge

creation

acquisition of knowledge to knowledge creation [

85.1

], and shifting the focus from group to individual education. Since the perspective for discussions of education systems is moving from instructors to learners [

85.2

,

3

,

4

], in place of

education systems

we adopt the expression

education/learning systems

. When considering the automation of education/learning systems, along with the impact of

information and communication technology (ICT)

information and communications technology (ITC), the effects of educational psychology and educational technology cannot be ignored. This field overall is referred to

instructional design (ID)

as instructional design (ID) [

85.5

]. This chapter examines the history and present conditions of automation in

e-Learning

education/learning systems, centered on e-Learning, from the perspectives of information and communication technologies and instructional design. The chapter also introduces two examples from the

industrial engineering

field of industrial engineering and management systems concerning projects to develop education/learning programs to train Japanese manufacturing management personnel. These examples are both ongoing industry–government–academia collaboration projects aimed at the transmission and development of Japanese manufacturing

kaizen

(continuous improvement) knowhow and the education and training of management personnel.

The chapter concludes with a summary of future issues concerning the automation of education/learning systems and a list of reference materials in related fields for readers who seek further details.

Enterprise integration and interoperability deal with facilitating communication, cooperation, and collaboration within an organization, be it a single organization or a networked organization, or be it a public or a private organization. This chapter first defines enterprise integration and systems interoperability and presents relevant architectural frameworks. It then explains the technical, semantic, and organizational dimensions of interoperability before presenting essential standards and technology for interoperability and integration. Applications and future trends are pointed out before concluding.

This chapter places decision automation in a broader context of using information technologies in decision making. Key definitions and a brief history of computerized decision support create important boundaries. Then a description and explanation of characteristics of computerized

decision support system (DSS)

decision support systems (DSS) clarifies this application domain. After reviewing management information needs, a modern taxonomy of decision support systems is briefly summarized. Issues associated with building DSS and various architectures are reviewed before concluding the overview.

A major part of automation today is represented by collaborative e-Work, e-Business, and e-Service. In this chapter the fundamental theories and scope of collaborative e-Work and collaborative control theory (CCT) are reviewed, along with design principles for effectiveness in the design and operation of their automation solutions. The potential benefits, opportunities, and sustainability of emerging electronic activities, such as virtual manufacturing, e-Healthcare, automated inspection, e-Supply, e-Production, e-Collaboration, e-Logistics, and other e-Activities, will not materialize without the design of effective e-Work. For instance, without automatic error prevention or recovery, e-Activities in complex systems will collapse. The

four-wheels

collaboration

four-wheels

collaboration

15 e-Dimensions

of collaborative e-Work, their respective 15 e-Dimensions, and their role in e-Business and e-Service are explained and illustrated. Case studies of e-Work, e-Manufacturing, e-Logistics, e-Business and e-Service are also provided to enable readers to get a glimpse into the depth and breadth of ongoing efforts and potential inhibitors to revolutionize such e-Systems. Challenges and emerging solutions are discussed to stimulate readers to push the boundaries of collaborative e-Work.

Electronic commerce (e-Commerce) is fast becoming a way of life in the 21st century. As more and more consumers and organizations resort to electronic means for conducting purchases and facilitating business transactions, it has become vital for academic researchers as well as practitioners to understand its workings, and be able to analyze problems and rectify weaknesses. This is complicated by the fact that the e-Commerce market is global and constantly evolving, with new and innovative business models and products being introduced at a rapid pace. We present an overview of the status of e-Commerce, with particular emphasis on academic research. Specifically, we review the historical background of e-Commerce, discuss theoretical frameworks, and examine e-Commerce models. We also discuss emerging trends as well as pressing issues facing the e-Commerce marketplace.

Integrated enterprise-wide information systems (EwIS)

enterprise-wide

information system (EwIS)

information

enterprise-wide system

are a class of customizable packaged business software applications that have replaced arrays of disparate legacy systems in organizations around the world. EwIS have been the catalyst for the reengineering and automation of core business processes that has led to organization-wide transformation across most industries in corporate America. Chief among this category of packaged business software is enterprise resource planning (ERP), the

enterprise resource planning (ERP)

back-office suite that was embraced by many industries in the 1990s as a cure for legacy system ailments and impending year-2000 (Y2K) disasters. ERP is considered a product of the evolution of an earlier manufacturing planning system referred to as manufacturing resource planning (MRPII). Whereas MRPII was focused on the factory

manufacturing

resource planning (MRPII)

planning environment, ERP incorporates enterprise-wide functionality and therefore is used in virtually all industries. ERP has enabled organizations to streamline, automate, and commoditize their business processes, leveraging best-of-industry practices, quite significantly over the last 15 years. Two other packages that are attributing to this phenomenon are customer relationship management (CRM) and supply chain management (SCM). In this

customer relationship

management (CRM)

management

customer relationship

supply chain

management (SCM)

chapter we review EwIS in a historical context as it has developed over the years and discuss the most important characteristics of EwIS today as well as how we expect this field to evolve.

This chapter addresses automation in the

financial

services industry

financial services industry with a focus on small banks and credit unions. The financial services industry includes all organizations that engage in or facilitate financial transactions. Automation is essential for these firms to both lower cost and differentiate their services. Small banks and credit unions are an important subset of this industry, with unique automation needs to enable them to compete with large, international firms.

The chapter begins with a description of the financial services industry in general, then moves on to describe community banks and credit unions, how they operate, and the role of automation. The chapter then addresses two key automation areas for these institutions: their core systems that support basic account processing, and a key customer-facing system – Internet banking. Factors that drive success and recommendations for how to approach each of these automation areas is discussed. For these small financial institutions, successful automation of back-end systems depends on how they source the system, with outsourcing both raising costs and the number of channels through which they distribute their products. Successful automation of customer-facing systems, such as Internet banking, depends on getting their customers to use the system. Because of this, success is more of a management than a technical issue. The chapter concludes with a discussion of emerging trends, technologies, and issues.

e-Government in its most generic form refers to the automation of government processes and services by using modern information and communication technologies, usually – but not necessarily – in combination with web technology. The transition from paper-based administrative workflows to electronically supported process chains involving a multitude of stakeholders (in particular, government agencies, citizens or companies) is a key driver of todayʼs e-Government policies. Whereas in their early manifestations, e-Government efforts were primarily geared towards improving internal administrative performance, todayʼs focus is on increasing the overall quality of government services. The aim is to improve the living conditions of citizens and to create a favorable climate for business.

This chapter provides a short introduction to the basic concepts of e-Government, explains how e-Government evolved over the last 10 years, gives an overview of the dimensions on which the design and implementation of successful and sustainable e-Government services has to proceed, and outlines some future challenges for e-Government.

Many of todayʼs important scientific breakthroughs are made by large, interdisciplinary collaborations of scientists working in geographically distributed locations, producing and collecting vast and complex datasets. Experimental astrophysics, in particular, has recently become a data-intensive science after many decades of relative data poverty. These large-scale science projects require software tools that support not only insight into complex data but collaborative science discovery. Such projects do not easily lend themselves to fully automated solutions, requiring hybrid human–automation systems that facilitate scientist input at key points throughout the data analysis and scientific discovery process. This chapter presents some of the issues to consider when developing such software tools, and describes Sunfall, a collaborative visual analytics system developed for the Nearby Supernova Factory, an international astrophysics experiment and the largest data volume supernova search currently in operation. Sunfall utilizes novel interactive visualization and analysis techniques to facilitate deeper scientific insight into complex, noisy, high-dimensional, high-volume, time-critical data. The system combines novel image-processing algorithms, statistical analysis, and machine learning with highly interactive visual interfaces to enable collaborative, user-driven scientific exploration of supernova image and spectral data. Sunfall is currently in operation at the Nearby Supernova Factory; it is the first visual analytics system in production use at a major astrophysics project. The chapter concludes with a set of guidelines and lessons learned about developing software to support scientific collaborations.

This chapter contains automation information collected from many different sources around the world, among them the US Census Bureau, the International Federation of Automatic Control (IFAC), the American Automatic Control Council (AACC), the American Bankers Association, World Robotics, and many more. Section

94.1

introduces automation statistical data according to its application domain, such as: financial and e-Commerce, industrial, healthcare, and the service industries. In Sect.

94.2

a list of worldwide automation, control, and robotics associations is provided. Section

94.3

provides the reader with a list of automation labs around the world and lastly, in Sect.

94.4

a list of automation related journals and publications is presented.

statistics

The statistics, organizations, and journals included in this chapter open a window into the current and emerging state of automation. While attempting to be comprehensive, because of the broadness of automation, the authors recognize that there may be additional relevant items, but none were omitted intentionally. The scope of the information is meant to highlight and expose the broad span, applications, concerns and benefits of automation, and clearly, cannot completely include all areas of automation influence. Beyond this chapter, other chapters in this handbook provide additional statistical data directly related to their specific topic.