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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Table of Contents
I Smart manufacturing design
1. Cloud manufacturing implementation for smart manufacturing networks 2. Improving Brazilian Engineering Education: real engineering challenges in an IIoT undergraduate course
II Industry 4.0 information technology developments
3. New verification and validation tools for Industry 4.0 software 4. Stepping stone to smarter supervision: a human-centered multidisciplinary framework
III Industry 4.0 business developments
5. How to define a business-specific smart manufacturing solution 6. Assessment of the competitiveness and effectiveness of the business model 4.0 7. Sustainable Business Models in the context of Industry 4.0 8. Understanding Digital Transformation challenges: evidence from Brazilian and British manufacturers 9. Smart green supply chain management: a configurational approach for reaching sustainable performance goals and decreasing COVID-19 impact 10. Multicriteria Decision Making approach for selection and prioritization of projects into the Digital Transformation journey
IV Industry 4.0 production planning and decision making
11. Smart manufacturing scheduling with Petri nets 12. Characterizing nervousness at the shop-floor level in the context of Industry 4.0 13. Digital and smart production planning and control 14. Simulation-based generation of rescheduling knowledge using a cognitive architecture
Authors
Daniel Rossit Engineering Department, Universidad Nacional del Sur, Argentina.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, Bah�a 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.
Chaudhery Mustansar Hussain Adjunct Professor and Director of laboratories, New Jersey Institute of Technology (NJIT), USA. Chaudhery Mustansar Hussain is an Adjunct Professor and Director of laboratories in the Department of Chemistry & Environmental Sciences at the New Jersey Institute of Technology (NJIT), United States. His research is focused on the applications of nanotechnology and advanced materials, environmental management, analytical chemistry, and other various industries. Dr. Hussain is the author of numerous papers in peer-reviewed journals as well as a prolific author and editor of around 150 books, including scientific monographs and handbooks in his research areas.
