Changeable and Reconfigurable Manufacturing Systems

Manufacturing has been experiencing dynamically changing environment that presents industrialists and academics with formidable challenges to adapt to these changes effectively and economically while maintaining a high level of responsiveness, agility and competitiveness. Advances in manufacturing technologies, equipment, systems and organizational strategies are helping manufacturers meet these challenges. The ability to change and effectively manage this change is a fundamental pre-requisite for surviving and prospering in this turbulent environment. Changeability is presented as an umbrella concept that encompasses many change enablers at various levels of an industrial company throughout the life cycle of the manufacturing system. In this introduction, the scope of manufacturing changeability is outlined, the objects of change are defined, the change enablers are introduced and discussed and the change management strategy is highlighted.

Many manufacturing challenges emerged due to the proliferation of products variety caused by products evolution and customization. They require responsiveness in all manufacturing support functions to act as effective enablers of change. This Chapter summarizes some recent findings by the author and coresearchers that address these issues.A variation hierarchy for product variants, from part features to products portfolios, was presented and discussed. The evolution of products and manufacturing systems is discussed and linked, for the first time, to the evolution witnessed in nature. The concept of evolving families for varying parts and products is presented. A biological analogy was used in modeling of products evolution and Cladistics was used for its classification. This novel approach was applied to the design of assembly systems layouts with the objective of rationalizing and delaying products differentiation and managing their variations. Process planning is part of the “soft” or “logical” enablers of change in manufacturing as the link between products and their processing steps. New perspectives on process planning for changing and evolving products and production systems are presented. Process-neutral and process-specific products variations were identified and defined. A recently developed innovative, and fundamentally different, method for Reconfiguring Process Plans (RPP) and new metrics for their evaluation are presented and their significance and applicability in various domains are summarized. The merits of reconfiguring process plans on-the-fly for managing the complexity and extensive variations in products families, platforms and portfolios are highlighted and compared with the traditional re-planning and pre-planning approaches. The conclusions shed light on the increasing challenges due to variations and changes in products and their manufacturing systems and the need for effective solutions and more research in this field.

Manufacturing flexibility is seen as the main mechanism for surviving in the present market environment. Companies acquire systems with a high degree of flexibility to cope with frequent production volume changes and evolutions of the technological requirements of products. However, literature and industrial experience show that flexibility is not always a well-defined concept. Therefore it is really complex to understand and use flexibility during system design process. Indeed, the development of structured approaches to support the system design by considering basic flexibility forms is still an open issue. This work presents an Ontology on Flexibility aiming at providing a standard method to analyze flexibility. Firstly, it contributes in systemizing the large number of existing flexibility definitions and classifications. Secondly, it can be used to analyze real systems and to better understand their characteristics in terms of flexibility. Finally this ontology represents a key point of a general approach to design production system with the right level of flexibility.

Changes in manufacturing requirements and market demands call for increased flexibility, adaptability and sometimes reconfiguration. This is true for manufacturing systems and their components such as machines and robots. This chapter discusses both the physical hardware reconfiguration of these components as well as their logical reconfiguration manifested in the control system. The challenges involved in the physical reconfiguration are detailed and solutions are presented. The requirements for reconfigurable control systems are discussed and the state-of-the-art implementations and systems are described. The remaining obstacles and challenges for future research and industrial adoption are highlighted.

A flexible manufacturing system with CNC machining centers is becoming decidedly appealing to automotive industry. Such production systems are required to have minimal cycle times and exhibit high flexibility. Consequently, the development and supply of machine tool systems that can fulfill the utmost important requirements such as flexibility, reliability, and productivity for mass production is necessary. This chapter will discuss newly developed CNC machine tools with reconfigurable features. The design concept, machine tool configuration, and application examples of the machines are addressed.

Reconfigurable Manufacturing Systems (RMS) are characterized by their quick adaptation to un-scheduled and un-predictable changes in production requirements. Trends, like the reduction of product life cycles, high products diversity at small lot sizes, as well as the fast development and implementation of new production technologies, call for new approaches in the design of flexible and life cycle overlappingmachine tools. The flexibility of RMS comprises changes in machining technology, production capacity, machine structure and function as well as in work piece spectrum and material property. The presented design of RMS is based on a construction kit principle, which enables it to adjust to new production requirements by substitution, addition or removal of machine systems. A new trend in the area of RMS is the complete machining of work pieces by using different machining technologies in one machine workspace (Abele, Wörn, 2004). This paper describes a method that considers the constructive particularities of the Reconfigurable Multitechnology Machine tool (RMM) taking flexibility aspects into consideration.

Industrial assembly is subject to quick product changes, increasing numbers of variants and short planning spans of the customer. Because of the relatively high percentage of manual work the cost pressures from low wage countries is especially high. These challenges can be effectivelymet, however, through a comprehensive rationalization approach to the assembly, highly flexible assembly technology and qualified personnel. Depending on the product complexity, variant diversity and output rate there are a number of concepts available, which are situated between the competing demands of productivity and flexibility. This chapter describes the main features of manual, automated and hybrid assembly with a special attention to flexibility and reconfigurability.

A highly reconfigurable control system that intelligently unifies reconfiguration and manages the interaction of individual robotic control systems within a Reconfigurable Manufacturing System (RMS), is presented. A Reconfigurable Plant Model (RPM) representing different robotic systems was developed to perform any reconfigurable control process. The RPM has seven reconfigurable modules: Reconfigurable Puma-Fanuc (RPF) model, Unified Kinematic Modeler and Solver (UKMS), Reconfigurable Puma-Fanuc Jacobian Matrix (RPFJM), Reconfigurable Puma-Fanuc Singularity Matrix (RPFSM), Reconfigurable RobotWorkspace (RRW), Reconfigurable Puma-Fanuc Dynamic Model (RPFDM), Reconfigurable Puma-Fanuc Dynamic Model Plus actuators (RPFDM+). The Reconfigurable Control Platform (RCP) was developed for the Reconfigurable Plant Model using MATLAB/Simulink® software. The PUMA 560 robot was selected for the case study. Using information of the kinematic and dynamic parameters for PUMA 560 robot and its DC motors parameters, the reconfigurable “PI” controller was designed in a function of the motor parameter. The system response exhibits a very good performance. The reverse modeling of the reconfigurable modules can be used for developing a new Reconfigurable Robot Meta Model.

This chapter deals with the effect of changes at the machine/robot physical level and new reconfigurable control strategies to enable such change. Joint flexibility constitutes the major source of compliance in most industrial robots. It is important to account for joint flexibility when dealing with force control problems. In addition, the type of environment that the robot is in contact with, or the object that the robot works on, may be made of different materials. Hence, force control strategies suitable for both rigid and soft contact is needed corresponding to different parts of the object/surface while performing the task. A decoupling-based force/position control of flexible joint robot is first designed for rigid, stiff and dynamic environments. A reconfigurable force control scheme is proposed for when the robot’s working trajectory covers different types of environments. Numerical simulation results are presented to demonstrate the effectiveness of the proposed decoupling approach and the reconfigurable force control scheme. The desired contact force can be obtained, whether it is rigid or soft environment, without stopping the robot, due to the active reconfiguration of the controller. This novel reconfigurable control scheme can be extended, by including other well-designed controllers, thus achieving more versatile control reconfiguration under changeable situations.

In a customer driven market, the increasing number of product variants is a challenge most engineering companies face. Unpredictable changes in product design and associated engineering specifications trigger frequent changes in process plans, which often dictate costly and time consuming changes to jigs, fixtures and machinery. Process Planning should be further developed to cope with evolving parts and product families, increased mass customization and reduced-time-tomarket. Agility and responsiveness to change is important in process planning. The current methods do not satisfactorily support this changeable manufacturing environment. They involve re-planning or pre-planning, where new process plans are generated from scratch every time change takes place, which results in production delays and high costs due to consequential changes and disruptions on the shop floor. The obvious cost, limitations and computational burden associated with the re-planning/pre-planning efforts are avoided by the developed methods. A novel process planning concept and a new mathematical programming model have been developed to genuinely reconfigure process plans to optimize the scope, extent and cost of reconfiguration and to overcome the complexity and flaws of existing models. Hence, process planning has been fundamentally changed from an act of sequencing to that of insertion. For the first time, the developed methods reconfigure process plans to account for changes in parts’ features beyond the scope of original product families. A new criterion in process planning has been introduced to quantify the extent of resulting plan changes and their downstream implications. The presented method was shown to be cost effective, time saving, and conceptually and computationally superior. This was illustrated using two case studies in different engineering domains. The developed hypothesis and model have potential applications in other disciplines of engineering and sciences.

Rapid changes are characterizing the market and supply situation of manufacturing companies. Changeability ensures their ability to act successfully in this environment. Logistics is one topic of changeability and in particular Production Planning and Control (PPC). This chapter presents a framework to design a changeable PPC system and discusses the relevant enablers for changeability as well as required change processes. Examples illustrate how to achieve PPC changeability.

Agile manufacturing is defined as the capability of manufacturing systems to survive and prosper in a competitive environment of continuous and unpredictable change, by reacting quickly and effectively to changing markets driven by customerdesigned products and services. A new agile Manufacturing Planning and Control (MPC) system design is needed to respond to the changeability of the underlying manufacturing system as well as to the uncertainty of the surrounding environment. It should be resilient to change and responsive to its environment. It should satisfy required performance measures and achieve the required competitive strategy. A new conceptual model and framework to handle MPC system problems from the system perspective is introduced. Component Based Software Engineering (CBSE) provides the tools and the power to design the proposed new system. The MPC system should be able to achieve the required balance between demands and supply, high service levels, low inventories and deal with volume-mix issues. The coordination and interactions between different system components achieve the required system resilience and peak system performance.

Uncertainty associated with managing the dynamic capacity in changeable manufacturing is the main source of its complexity. A system dynamics approach to model and analyze the operational complexity of dynamic capacity in multi-stage production is presented. The unique feature of this approach is that it captures the stochastic nature of three main sources of complexity associated with dynamic capacity. The model was demonstrated using an industrial case study of a multi-stage engine block production line. The analysis of simulation experiments results showed that ignoring complexity sources can lead to wrong decisions concerning both capacity scaling levels and backlogmanagement scenarios. In addition, a general trade-off between controllability and complexity of the dynamic capacity was illustrated. A comparative analysis of the impact of each of these sources on the complexity level revealed that internal delays have the highest impact. Guidelines and recommendations for better capacity management and reduction of its complexity, in changeable manufacturing environment, are presented.

Numerous markets are characterized by increasing individualization and high dynamics. A company’s ability to quickly adjust its production system to future needs and conditions with minimum effort is a key competitive factor. Especially in high-wage countries, two conflicts increasingly complicate the design of production systems: the conflict between scale and scope on the one hand and the conflict between a high planning orientation and maximizing value-added activities on the other hand. For future production systems in high-wage countries, effective means are needed to minimize the gaps resulting from this poly-lemma. This contribution introduces a measurable target system to assess the degree of target achievement with regard to these criteria. Based on this target measurement system, a new approach that introduces object-oriented-design to production systems is presented. The central element of object-oriented design of production systems is the definition of objects, e.g. product functions, with homogeneous change drivers, which are consistently handled from product planning up to process design. Both product and process design are driven by interfaces between the defined objects and their inter-dependencies. The findings show that a consistent application of objectoriented design to production systems will significantly increase the flexibility in implementing product changes, minimize engineering change and process planning efforts and support process synchronization to achieve economies of scale more efficiently. Two case studies illustrate the implementation and impact of this approach.

The changeability of manufacturing systems enhances their adaptation to the increasingly dynamic market conditions and severe global competition. The effect of manufacturing systems changeability objective on their design process is discussed in this chapter at different levels, from the general frameworks, where the main objectives are stated, to the finest synthesis details, where product and production modules are designed. The conventional design frameworks are discussed and critiqued, and the tendency of most manufacturing systems design processes to be uni-directional is pointed out. Furthermore, a new manufacturing systems design framework is proposed to overcome the uni-directionality drawback of conventional design frameworks and help achieve a closer integration of both products and systems design and evolution.

Several factors must be considered to effectively manage process change. However, when changing or reconfiguring a system, care should be taken to assure that the changes minimize deviations from the original manufacturing process plans in a controlled manner. The new system configuration should utilize much of the original programs, tooling, fixturing, material handling, and inspection equipment in order to minimize the chances of introducing new quality or logistics issues. A systematic, spreadsheet based methodology for assessing configurations or reconfigurations for CNC machine tools is presented. This methodology can be used in the initial planning stages, or when a change is introduced into the system. Heuristics are utilized that consider the physical and functional characteristics to determine a candidate machine’s suitability. The application of this methodology is demonstrated using practical examples.

The evolving characteristic of changeable manufacturing systems requires design and assessment techniques that consider both the strategic and financial criteria and incorporate the reconfiguration aspects as well as fluctuations in the demand over the planned system life cycle. The economic evaluation approaches to reconfigurable and flexible manufacturing systems have been reviewed. A fuzzy multi-objective mixed integer optimization model for evaluating investments in reconfigurable manufacturing systems used in a multiple product demand environment is presented. The model incorporates in-house production and outsourcing options, machine acquisition and disposal costs, operational costs, and re-configuration cost and duration for modular machines. The resulting configurations are optimized by considering life-cycle costs, responsiveness performance, and system structural complexity simultaneously. The overall model is illustrated with a case study where FMS and RMS implementations were compared. System configurations generated from the proposed model are simulated to compare the life-cycle costs of FMS and RMS. The suitable conditions for RMS investments have been discussed.

Despite the existence of many tools for assessing the product quality in manufacturing systems, there is limited research and/or tools that are concernedwith studying the impact of manufacturing system design on the resulting product quality; especially, at the system development stage. The methodologies that are used for designing the product for quality, especially when considering form, function and variations and their interaction with the manufacturing system design, are rather limited. In the context of reconfigurable manufacturing systems, the designer will be faced with many configuration alternatives, and other changes. From the quality point of view, the designer should have an insight, and most preferably mathematical models, of how design decisions could affect the product quality. Except for the research work that was devoted to investigate the impact of the system layout on quality, until recently the relationship between the quality and the different system parameters were not well defined and quantified. Manufacturing system changeability affects product quality in two respects: 1) manufacturing system design, and 2) maintenance of the manufacturing system equipment. Concerning the first aspect, the changeability in a manufacturing system affects many dimensions of the product quality. Some of these effects are positive and others are negative. A framework is presented for the complex relationship between quality, and the changes in reconfigurable manufacturing parameters. Details are also in the first Author’s publications and other publications referred to in this Chapter. With regards to maintainability, it is an important concern in choosing the manufacturing system parameters. A maintainability strategy based on axiomatic design and complexity reduction is presented using the relationships between the manufacturing system parameters and the multi-objectives for optimizing quality, cost and availability. This should lead to maintenance systems that are less complex and adaptive to the changes in manufacturing.

This chapter includes a review of the recent developments in this field motivated by the need for changeability and reconfiguration and its consequences on the maintenance strategies. It also includes technical details about the author’s own work and obtained scientific results in the field of fuzzy adaptive preventivemaintenance in manufacturing control systems and self-maintenance as well as industrial application, future challenges and new directions.

The automation of processes and production steps is one of the key factors for a cost effective production. Fully automated production systems can reach lead times and quality levels exceeding by far those of human workers. These systems are widely spread in industries of mass production where the efforts needed for setup and programming are amortized by the large number of manufactured products. In the production of prototypes or small lot sizes, however, human workers with their problem solving abilities, dexterity and cognitive capabilities are still the single way to provide the required flexibility, adaptability and reliability. The reason is that humans have brains, computational mechanisms that are capable of acting competently under uncertainty, reliably handling unpredicted events and situations and quickly adapting to changing tasks, capabilities, and environments. The realization of comparable cognitive capabilities in technical systems, therefore, bears an immense potential for the creation of industrial automation systems that are able to overcome today’s boundaries. This chapter presents a new paradigm of production engineering research and outlines the way to reach the Cognitive Factory, where machines and processes are equipped with cognitive capabilities in order to allow them to assess and increase their scope of operation autonomously.

The increasing individualization in the automotive industry characterized by so called ‘model offensives’ together with pressures due to high costs, shorter product life cycle, rising diversity of models and quantity volatility, demand new concepts in the production of vehicles. This is particularly true for ‘niche cars’. These difficulties are a motivation to develop a new concept for the body-in-white production, which is highly flexible with respect to models and variants that will be denoted as the “Migration Concept”. The concept can be applied to other product categories and industries and can therefore be named as Migration Manufacturing. Its essential characteristics are themanufacturing of different body work models and their variants on one production line, as well as the ability to extend the basic layout along the “migration path”. The specific changeability of a body-in-white production with regards to the integration and removal of newmodels and versions is called “Migration”. The production volumes proportion of the specific models can vary in great range and the investments are flexible according to the required volume. The paper describes the basic concept, its components and production phases, as well as its comparison with the conventional transfer lines.

The construction of factories is an extensive and complex single-piece production in our economy. Only a well-balanced consideration of all planning criteria can ensure a project’s success in the long run. A factory’s design cannot be derived from production requirements only but it also grows out of the context of location, climate, society and human beings within an extremely creative process. Over and above its purely functional suitability the sensible structure of a building can give a positive impulse to future changeability aspects as well as motivation and communication. This chapter presents construction relevant design fields and their elements as they arise from the planning of the manufacturing processes. The versatile network of buildings will be analytically classified according the design aspects of buildings structure as well as the future changeability of manufacturing processes.