Designing Smart Manufacturing Systems

Daniel Alejandro Rossit PhD, is an Assistant Researcher at CONICET (National Research Council of Argentina) and Teaching Assistant in the Engineering Department of the Universidad Nacional del Sur, Bahía Blanca, Argentina. He has an Industrial Engineering degree and a PhD in Engineering. His research has focused on production problems, operations research and engineering systems optimization. Prof. 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), Newark, New Jersey, 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.

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