Special Session on Industry 4.0

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Revolution of Production System for the Industry 4.0

Nowadays, good coordination of production and logistics at a production operational level is required to handle rapidly evolving technology, frequently changing customer demand and satisfaction, and remain competitive. Accelerated by exponentially growing technologies in information and communication technology, production industries are in the throes of a digital transformation, which is referred to as the fourth industrial revolution or Industry 4.0. The shorter product life cycles due to market-demand variables and volatile developments in the production system have forced manufacturing company to work flexibly in order to adapt to changing customer needs. These environments cannot be managed through traditional production systems such as job shops and dedicated production lines. Reconfigurable manufacturing system, which combines the versatility and capability to re-configure of job shops and the dedicated production lines, has been seen as a potential solution in such situations. As the main component of production systems, a new concept of material handling, a reconfigurable conveyor system is introduced

CHANGE-READY MPC SYSTEMS AND PROGRESSIVE MODELING: VISION, PRINCIPLES, AND APPLICATIONS

The last couple of decades have witnessed a level of fast-paced development of new ideas, products, manufacturing technologies, manufacturing practices, customer expectations, knowledge transition, and civilization movements, as it has never before. In today\u27s manufacturing world, change became an intrinsic characteristic that is addressed everywhere. How to deal with change, how to manage it, how to bind to it, how to steer it, and how to create a value out of it, were the key drivers that brought this research to existence. Change-Ready Manufacturing Planning and Control (CMPC) systems are presented as the first answer. CMPC characteristics, change drivers, and some principles of Component-Based Software Engineering (CBSE) are interwoven to present a blueprint of a new framework and mind-set in the manufacturing planning and control field, CMPC systems. In order to step further and make the internals of CMPC systems/components change-ready, an enabling modeling approach was needed. Progressive Modeling (PM), a forward-looking multi-disciplinary modeling approach, is developed in order to modernize the modeling process of today\u27s complex industrial problems and create pragmatic solutions for them. It is designed to be pragmatic, highly sophisticated, and revolves around many seminal principles that either innovated or imported from many disciplines: Systems Analysis and Design, Software Engineering, Advanced Optimization Algorisms, Business Concepts, Manufacturing Strategies, Operations Management, and others. Problems are systemized, analyzed, componentized; their logic and their solution approaches are redefined to make them progressive (ready to change, adapt, and develop further). Many innovations have been developed in order to enrich the modeling process and make it a well-assorted toolkit able to address today\u27s tougher, larger, and more complex industrial problems. PM brings so many novel gadgets in its toolbox: function templates, advanced notation, cascaded mathematical models, mathematical statements, society of decision structures, couplers--just to name a few. In this research, PM has been applied to three different applications: a couple of variants of Aggregate Production Planning (APP) Problem and the novel Reconfiguration and Operations Planning (ROP) problem. The latest is pioneering in both the Reconfigurable Manufacturing and the Operations Management fields. All the developed models, algorithms, and results reveal that the new analytical and computational power gained by PM development and demonstrate its ability to create a new generation of unmatched large scale and scope system problems and their integrated solutions. PM has the potential to be instrumental toolkit in the development of Reconfigurable Manufacturing Systems. In terms of other potential applications domain, PM is about to spark a new paradigm in addressing large-scale system problems of many engineering and scientific fields in a highly pragmatic way without losing the scientific rigor

Dynamic modelling of reconfigurable manufacturing planning and control systems using supervisory control

This research is concerned with studying the dynamic performance of reconfigurable Manufacturing Planning and Control (MPC) systems. Such goal requires two main tasks. The first task is to develop a dynamic MPC system model that has the ability to reconfigure to different MPC policies. The second task is to design a supervisory control unit that has as input the high level strategic market decisions and constraints together with a feedback of the current manufacturing system state and then select the optimal suitable operation mode or policy at these conditions. This paper addresses the first task of the proposed research and presents and analyses a dynamic reconfigurable MPC model. The response of the developed model to sudden demand changes under different parameters settings is analyzed. In addition, the stability limits of the system are also studied. The results give a better understanding of the dynamics of reconfigurable MPC systems and the different trade-off decisions required when selecting an MPC policy and the limits for parameters settings. These results represent the first step towards designing the supervisory control unit which will be responsible for managing the reconfiguration of the whole system

Engineering methods and tools for cyber–physical automation systems

Much has been published about potential benefits of the adoption of cyber–physical systems (CPSs) in manufacturing industry. However, less has been said about how such automation systems might be effectively configured and supported through their lifecycles and how application modeling, visualization, and reuse of such systems might be best achieved. It is vitally important to be able to incorporate support for engineering best practice while at the same time exploiting the potential that CPS has to offer in an automation systems setting. This paper considers the industrial context for the engineering of CPS. It reviews engineering approaches that have been proposed or adopted to date including Industry 4.0 and provides examples of engineering methods and tools that are currently available. The paper then focuses on the CPS engineering toolset being developed by the Automation Systems Group (ASG) in the Warwick Manufacturing Group (WMG), University of Warwick, Coventry, U.K. and explains via an industrial case study how such a component-based engineering toolset can support an integrated approach to the virtual and physical engineering of automation systems through their lifecycle via a method that enables multiple vendors' equipment to be effectively integrated and provides support for the specification, validation, and use of such systems across the supply chain, e.g., between end users and system integrators