Design of Smart Manufacturing Systems covers the fundamentals and applications of smart manufacturing or Industry 4.0 system design, along with interesting case studies. Digitization and Cyber-Physical Systems (CPS) have vastly increased the amount of data available to manufacturing production systems. This book addresses the planning, modeling and experimentation of different decision-making problems as well as the conditions that affect manufacturing. In addition, recent developments in the design of smart manufacturing and its applications are explained, covering the needs of both researchers and practitioners.
To fully navigate the challenges and opportunities of smart manufacturing systems, contributions are drawn from operations research, information systems, computer science and industrial engineering as well as manufacturing engineering.
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Daniel Alejandro Rossit, PhD is a Researcher of CONICET (National Research Council of Argentina) and Professor in the Engineering Department of the Universidad Nacional del Sur, Bahía Blanca, Argentina. He has an Industrial Engineer degree and a PhD in Engineering. His research has focused on production problems, operations research and engineering systems optimization. He has published in journals such as Omega, International Journal of Production Research, The International Journal of Advanced Manufacturing, Computers and Electronics in Agriculture, International Journal of Computer Integrated Manufacturing, among others.
Design of Smart Manufacturing Systems covers the fundamentals and applications of smart manufacturing or Industry 4.0 system design, as well as providing interesting case studies. Digitization and Cyber-Physical Systems (CPS) have vastly increased the amount of data available to manufacturing production systems. This data can provide real-time information on the status of production, and also transmit this information to as many decision centers as required, leading to total integration between the operator, supervisors, managers and laboratory analysts. This digitization also allows the creation of digital replicas of the process (Digital Twins) that can allow the design and simulation of different scenarios to improve decision-making processes. These technologies together, in addition to others can be combined to form a smart manufacturing system, but to do so successfully it is necessary to adopt a new perspective on decision-making processes.
To achieve this, this book addresses the planning, modeling and experimentation of different decision-making problems as well as the conditions that affect manufacturing. In addition, recent developments in the design of smart manufacturing and its applications are explained, covering the needs of both researchers and practitioners. To fully navigate the challenges and opportunities of smart manufacturing systems, contributions are drawn from operations research, information systems, computer science and industrial engineering as well as manufacturing engineering.
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