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2018 | Book

Cloud-Based Cyber-Physical Systems in Manufacturing

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About this book

This book presents state-of-the-art research, challenges and solutions in the area of cloud-based cyber-physical systems (CPS) used in manufacturing. It provides a comprehensive review of the literature and an in-depth treatment of novel methodologies, algorithms and systems in the area of architecture design, cyber security, process planning, monitoring and control.

The book features detailed descriptions of how to derive solutions in a cloud environment where physical machines can be supported by cyber decision systems when engaged in real operations. It presents a range of novel ideas and is characterized by a balanced approach in terms of scope vs. depth and theory vs. applications. It also takes into account the need to present intellectual challenges while appealing to a broad readership, including academic researchers, practicing engineers and managers, and graduate students.

Dedicated to the topic of cloud-based CPS and its practical applications in manufacturing, this book benefits readers from all manufacturing sectors, from system design to lifecycle engineering and from process planning to machine control. It also helps readers to understand the present challenges and future research directions towards factories of the future, helping them to position themselves strategically for career development.

Table of Contents

Frontmatter

Literature Survey and Trends

Frontmatter
Chapter 1. Latest Advancement in Cloud Technologies
Abstract
Cloud computing is a model for enabling ubiquitous, convenient, on-demand network access to a shared pool of configurable computing resources (e.g. networks, servers, storage, applications, and services). It is changing the way that industries and enterprises do their businesses. Inspired by cloud computing, coupled with other newly emerging technologies such as Internet of Things (IoT), Cyber-Physical Systems (CPS), service-oriented technology, big data analytics, and driven by new manufacturing requirements such as globalisation, highly efficient collaboration and servitisation, cloud manufacturing as a new service-oriented manufacturing paradigm has been proposed. Cloud computing and cloud manufacturing represent the latest advancement and applications of cloud technologies in computing and manufacturing industries, respectively. This chapter aims to provide a comprehensive introduction to both cloud computing and cloud manufacturing, and presents their current status and advancement.
Lihui Wang, Xi Vincent Wang
Chapter 2. Latest Advancement in CPS and IoT Applications
Abstract
This chapter presents the latest advancement of Cyber-Physical Systems (CPS) and Internet of Things (IoT), especially in manufacturing systems. To comprehensively understand CPS and IoT, a brief introduction to both of them is given, and the key enabling technologies related to CPS and IoT are outlined. Key features, characteristics, and advancements are explained, and a few applications are reported to highlight the latest advancement in CPS and IoT. The aim of this chapter is to provide readers with basic understandings of the relevant literature for the ease of further reading of subsequent chapters.
Lihui Wang, Xi Vincent Wang
Chapter 3. Challenges in Cybersecurity
Abstract
With the growing development of Web, Cloud and Internet applications in industry, one concern that potential users may have is the security of data, remote machines, and operators. Potential security risks in communication with remotely operated manufacturing equipment have been of recent interest which is dubbed cybersecurity in this book. The purpose of this chapter is to provide an overview of cybersecurity measures being considered to ensure the protection of data being sent to physical machines in a cybernetic system. Topics covered include: remote equipment control, security concerns in remote equipment control, existing proposed security measures for remote equipment control and the future outlook of remote equipment control and security in cybernetic systems. While common to other cybernetic systems, security issues in Cloud Manufacturing are focused in this chapter for brevity.
Lihui Wang, Xi Vincent Wang

Cloud-Based Monitoring, Planning and Control in CPS

Frontmatter
Chapter 4. Machine Availability Monitoring and Process Planning
Abstract
Cloud manufacturing as a trend of future manufacturing would provide cost-effective, flexible and scalable solutions to companies by sharing manufacturing resources as services with lower support and maintenance costs. Targeting the distributed manufacturing, the scope of this chapter is to present an Internet- and Web-based service-oriented system for machine availability monitoring and process planning. Particularly, this chapter introduces a tiered system architecture and introduces IEC 61499 function blocks for prototype implementation. By connecting to a Wise-ShopFloor framework, it enables real-time machine availability and execution status monitoring during metal-cutting operations, both locally or remotely. The closed-loop information flow makes process planning and monitoring feasible services for the distributed manufacturing.
Lihui Wang, Xi Vincent Wang
Chapter 5. Cloud-Enabled Distributed Process Planning
Abstract
Today, the dynamic market requires manufacturing firms to possess a high degree of adaptability to deal with shop-floor uncertainties. Specifically targeting SMEs active in the metal cutting sector who normally deal with intensive process planning problems, researchers have tried to address the subject. Among reported solutions, Cloud-DPP elaborates a two-layer distributed adaptive process planning based on function block technology and cloud concept. One of the challenges of companies is to machine as many part features as possible in a single setup on a single machine. Nowadays, multi-tasking machines are widely used due to their various advantages, such as reduced setup times and increased machining accuracy. However, they also possess programming challenges because of their complex configuration and multiple machining functions. This chapter reports the latest state of the design and implementation of Cloud-DPP methodology to support parts with a combination of milling and turning features, and process planning for multi-tasking machining centres with special functionalities to minimise the total number of setups. This chapter covers representation of machining states and part transfer functionality, support of multi-tasking machines in adaptive setup merging, development of special function blocks to handle sub-setups and transitions, and finally generation of function block networks for the merged setups. A case study is also included to validate the reported methodology.
Lihui Wang, Xi Vincent Wang
Chapter 6. Adaptive Machining Using Function Blocks
Abstract
In a Cyber-Physical System (CPS), sensors or other communicating tools embedded in physical entities are responsible for real-time data acquisitions. Operation decisions are adaptively made according to the physical inputs, and are transferred to the physical entities in order to optimise the performance of the system. Within a CPS, function blocks are applied at control level. Function blocks, as data and function carriers, are embedded in machining processes by combining machining features (MFs), which represent machining information, e.g. machining sequence, machining parameters, and other relevant machining resources. MFs are enriched to carry much more machining information and knowledge. A reachability-based MF sequencing method then generates MF sequence adaptively to minimise the cutting tool change times. Moreover, 3-axis based setups can be merged and dispatched adaptively to the selected machine tool.
Lihui Wang, Xi Vincent Wang
Chapter 7. Condition Monitoring for Predictive Maintenance
Abstract
Advanced manufacturing depends on the timely acquisition, distribution, and utilisation of information from machines and processes across spatial boundaries. These activities can improve accuracy and reliability in predicting resource needs and allocation, maintenance scheduling, and remaining service life of equipment. As an emerging infrastructure, cloud computing provides new opportunities to achieve the goals of advanced manufacturing. This chapter reviews the historical development of prognosis theories and techniques and projects their future growth enabled by the emerging cloud infrastructure. Techniques for cloud computing are highlighted, as well as the influence of these techniques on the paradigm of cloud-enabled prognosis for manufacturing. Finally, this chapter discusses the envisioned architecture and associated challenges of cloud-enabled prognosis for manufacturing.
Lihui Wang, Xi Vincent Wang

Sustainable Robotic Assembly in CPS Settings

Frontmatter
Chapter 8. Resource Efficiency Calculation as a Cloud Service
Abstract
Optimising the energy consumption of robot movements has been one of the main focuses for most of today’s robotic simulation software. This optimisation is based on minimising a robot’s joints movements. In many cases, it does not take into consideration the dynamic features. Therefore, reducing energy consumption is still a challenging task and it involves studying the robot’s kinematic and dynamic models together with application requirements. This chapter explains how to minimise the robot energy consumption during assembly. Given a trajectory and based on the inverse kinematics and dynamics of a robot, a set of attainable configurations for the robot can be determined, perused by calculating the suitable forces and torques on the joints and links of the robot. The energy consumption is then calculated for each configuration and based on the assigned trajectory. The ones with the lowest energy consumption are selected. Given that the energy-efficient robot configurations lead to reduced overall energy consumption, this approach becomes instrumental and can be wrapped as a cloud service for energy-efficient robotic assembly.
Lihui Wang, Xi Vincent Wang
Chapter 9. Safety in Human-Robot Collaborative Assembly
Abstract
Safety is critical to human-robot collaborative assembly, both locally and remotely. This has led to the monitoring of shop floor operators through tradition cameras and safety scanners. There are two main drawbacks in this kind of approach: the first is the limitation of the sensing devices which usually sense the environment from one perspective and in two dimensions only, and the second is the lack of flexibility in safety systems which usually triggers emergency stops in case of any intrusions. Such problems can be solved by using depth cameras installed carefully in the robotic environment. The advantage of this approach is the ability to install multiple depth cameras and fuse the 3D point clouds in one central server. This chapter first presents the latest accomplishments in active collision avoidance through local human-robot collaboration. A remote robotic assembly system is then introduced in the second half of the chapter.
Lihui Wang, Xi Vincent Wang
Chapter 10. Cloud Robotics Towards a CPS Assembly System
Abstract
Modern manufacturing industry calls for a new generation of production system with better interoperability and new business models. As a novel information technology, Cloud provides new service models and business opportunities for manufacturing industry. In this chapter, recent cloud manufacturing and cloud robotics approaches are reviewed. Function block-based integration mechanisms are presented to integrate various types of manufacturing facilities. A cloud-based manufacturing system is introduced to support ubiquitous manufacturing, which provides a service pool maintaining physical facilities in terms of manufacturing services. The introduced framework and mechanisms are evaluated by both machining and robotics applications. In practice, it is possible to establish an integrated manufacturing environment across multiple levels with the support of manufacturing cloud and function blocks. It provides a flexible architecture as well as ubiquitous and integrated methodologies for the cloud manufacturing.
Lihui Wang, Xi Vincent Wang
Chapter 11. Context-Aware Human-Robot Collaborative Assembly
Abstract
In human-robot collaborative manufacturing, industrial robots would work alongside the human workers who jointly perform the assigned tasks. Recent research work revealed that recognised human motions could be used as input for industrial robots control. However, the human-robot collaboration team still cannot work symbiotically. In response to the requirement, this chapter explores the potential of establishing context awareness between a human worker and an industrial robot for human-robot collaborative assembly. The context awareness between the human worker and the industrial robot is established by applying gesture recognition, human motion recognition and Augmented Reality (AR) based worker instruction technologies. Such a system works in a cyber-physical environment and is demonstrated by case studies.
Lihui Wang, Xi Vincent Wang

CPS Systems Design and Lifecycle Analysis

Frontmatter
Chapter 12. Architecture Design of Cloud CPS in Manufacturing
Abstract
Cloud manufacturing is a new concept extending and adopting the concept of cloud computing for manufacturing. The aim is to transform manufacturing businesses to a new paradigm in that manufacturing capabilities and resources are componentised, integrated and optimised globally. This chapter presents an interoperable manufacturing perspective based on cloud manufacturing. A literature search has been undertaken regarding cloud architecture and technologies that can assist cloud manufacturing. Manufacturing resources and capabilities are discussed in terms of cloud services. A service-oriented, interoperable cloud manufacturing system is introduced. Service methodologies are developed to support two types of cloud users, i.e. customer user and enterprise user, along with standardised data models describing cloud service and relevant features. Two case studies are undertaken to evaluate the reported system. Cloud technology brings into manufacturing industry with a number of benefits such as openness, cost-efficiency, resource sharing and production scalability.
Lihui Wang, Xi Vincent Wang
Chapter 13. Product Tracking and WEEE Management
Abstract
Waste Electrical and Electronic Equipment (WEEE) is both valuable and harmful since it contains a large number of profitable and hazardous materials and elements at the same time. At component level, many parts of the discarded equipment are still functional and recoverable. Thus it is necessary to develop a distributed and intelligent system to support WEEE component recovery and recycling. In recent years, the cloud concept has gained increasing popularity since it provides a service-oriented architecture that integrates various resources over the network. Cloud manufacturing systems are proposed worldwide to support operational manufacturing processes. In this chapter, cloud manufacturing is further extended to the WEEE recovery and recycling context. The cloud services are applied in WEEE recovery and recycling processes by tracking and management services. These services include all the stakeholders from the beginning to the end of life of the electric and electronic equipment. A cloud-based WEEE recovery system is developed to provide modularised recovery services in the cloud. A data management system is developed as well, which maintains the knowledge throughout the product lifecycle. A product tracking mechanism is also introduced with the help of the Quick Response (QR) code method.
Lihui Wang, Xi Vincent Wang
Chapter 14. Big Data Analytics for Scheduling and Machining
Abstract
In modern manufacturing industries, defect prediction and prevention are the key features. In this context, this chapter introduces a big data analytics based approach to scheduling and machining. In order to minimise machining errors in advance, a big data analytics based fault prediction approach is presented first for shop-floor scheduling, where machining tasks, machining resources, and machining processes are represented by data attributes. Based on the available data on the shop floor, the potential fault/error patterns, referring to machining errors, machine faults, maintenance states etc., are mined to discover unsuitable scheduling arrangements before machining as well as upcoming errors during machining. Targeting a global machining optimisation, this chapter then presents a big data analytics based optimisation method for machining process planning. Within the context, the machining factors are represented by data attributes, i.e. workpiece, machining requirement, machine tool, cutting tool, machine condition, machining process, machining result, etc. The problem of machining optimisation is treated as a statistical problem.
Lihui Wang, Xi Vincent Wang
Chapter 15. Outlook of Cloud, CPS and IoT in Manufacturing
Abstract
This chapter presents a summary of the current status and the latest advancement of Cloud technology, Cyber-Physical Systems (CPS) and Internet of Things (IoT) in manufacturing, where CPS is treated as a main thread. In order to understand CPS and its future potential in manufacturing, definitions and characteristics of CPS are explained and compared with cloud manufacturing and IoT concepts. Research and application potentials are outlined to highlight the latest advancement and future directions in the manufacturing domain. Cloud-based CPS shows great promise in factories of the future in the areas of future trends as identified at the end of this chapter.
Lihui Wang, Xi Vincent Wang
Backmatter
Metadata
Title
Cloud-Based Cyber-Physical Systems in Manufacturing
Authors
Prof. Lihui Wang
Dr. Xi Vincent Wang
Copyright Year
2018
Electronic ISBN
978-3-319-67693-7
Print ISBN
978-3-319-67692-0
DOI
https://doi.org/10.1007/978-3-319-67693-7

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