Architecting A Knowledge-Based Platform for Design Engineering 4.0

Zhenjun Ming is an Assistant Professor of the School of Mechanical Engineering at Beijing Institute of Technology (BIT). He received his PhD in Mechanical Engineering and his Bachelor's degree in Industrial Engineering, both from BIT. Zhenjun Ming's research interests include knowledge- -based systems, decision making in engineering design, collective intelligence and self-organizing systems. He devotes himself to merging Information Technology (IT) and Operation Technology (OT) to deliver useful, effective, and efficient tools and approaches for supporting human decisions in the design of cyber-physical-social systems. He is a winner of the "2015 NSF/ASME Student Design Essay Award". He has spent 20 months working with Professors Farrokh Mistree and Janet K. Allen as a visiting scholar at the University of Oklahoma (Norman), on a China Scholarship Council (CSC) sponsored project - Knowledge-Based Platform for Decision Support in the Design of Engineering Systems. He has publishedone monograph, ten journal papers and eight conference papers.
Anand Balu Nellippallil is an Assistant Professor in the Department of Mechanical and Civil Engineering at Florida Institute of Technology (FIT). Anand directs the Systems Realization Laboratory at FIT. He received his Ph.D. in Mechanical Engineering from the University of Oklahoma (OU) in 2018. Anand received his M. Tech degree in Materials Science and Engineering from the Indian Institute of Technology, Bhubaneswar, India in 2014, and his B.Tech degree in Production Engineering from the Government Engineering College Thrissur, University of Calicut, India in 2012. Before joining Florida Tech, he worked as a Research Engineer II at the Center for Advanced Vehicular Systems (CAVS) in Mississippi State University. His current research interests are focused on the realization of evolving human-cyber-physical-manufacturing-social systems. Anand has received several scholarships and awards, namely, the2018 Provost's Dissertation Prize for outstanding dissertation in science and engineering at OU, the Gallogly College of Engineering Dissertation Excellence Award, the Frank Chuck Mechanical Engineering Scholarships (2016 and 2017), Paper of Distinction at the ASME Design Automation Conference, a silver medal from the Indian Institute of Technology (IIT), Bhubaneswar for best academic performance and a university first rank medal from the University of Calicut. Anand has co-authored one other research monograph anchored in his PhD dissertation titled: Architecting Robust Co-Design of Materials, Products, and Manufacturing Processes. Anand is a member of ASME.
Ru Wang is an Assistant Professor of the School of Mechanical Engineering at Beijing Institute of Technology (BIT). He received his Ph.D. in Mechanical Engineering in June 2018 from BIT and got his B.E. and M.E. degree in Traffic Engineering and Vehicle Operation Engineering in 2011 and 2014 from Shandong Universityof Technology. Since December 2016 to November 2017, Ru joined the Systems Realization Laboratory at the University of Oklahoma (Norman) as a Visiting Scholar for one year and conducted a Joint PhD Program supported by BIT. He is an ASME member and the winner of the "2017 NSF/ASME Student Design Essay Award". His research interests include the management of complexity and uncertainty in decision-based design, intelligent design and knowledge engineering. He has co-authored sixteen journal papers, and five conference papers.
Janet K. Allen holds the John and Mary Moore Chair of Engineering at the University of Oklahoma, Norman. She received her SB from the Massachusetts Institute of Technology and her PhD form the University of California, Berkeley. Her research focus is on managing the uncertainty which is inherent in simulation-based design. Her group was among the first to recognize that there are four types of uncertainty inherent in simulation-based design andto s

"Design Engineering for Industry 4.0 (DE4.0) represents the 'human-cyber-physical view of the systems realization ecosystem "that is necessary to accommodate the drivers of Industry 4.0 (IoX) and provide an open ecosystem for the realization of complex systems. Seamless integration of digital threads and digital twins throughout the product design, the development and fulfillment lifecycle; the ability to accommodate diverse and rapidly changing technologies; and the mechanisms to facilitate the creation of new opportunities for the design of products, processes, services, and systems are some of the desired characteristics of DE4.0."
Jiao, R., Commuri, S. Panchal, J., Milisavljevic-Syed, J, Allen, J.K., Mistree, F. and Schaefer, D., "Design Engineering in the Age of Industry 4.0," ASME Journal of Mechanical Design, 143(7), 070801, 25 pages.
In keeping with the Design Engineering 4.0 construct the authors describe architecting a computer platform to support human designers make decisions associated with the realization of complex engineered systems. The platform is designed to facilitate end-to-end digital integration, customization and personalization, agile collaboration networks, open innovation, co-creation and crowdsourcing, product servitization and anything-as-a-service.
Recognizing that simulation models are abstractions of reality the authors opt for a satisficing strategy instead of an optimization strategy. They include fundamentals and then describe tools for architecting a knowledge-based platforms for decision support. Challenges associated with developing a computational platform for decision support for the realization of complex engineered systems in the context of Design Engineering 4.0 are identified. Constructs for formulating design decisions (e.g., selection, compromise, and coupled decisions), knowledge modelling schemes (e.g., ontologies and modular templates), diagrams for designing decision workflows (e.g., the PEI-X diagram), and some analytical methods for robust design under uncertainty are presented. The authors describe integrating the knowledge-based platform to architect a cloud-based platform for decision support promoting co-design and cloud-based design communication essential for mass collaboration and open innovation for Design Engineering 4.0.
This book is a valuable resource for researchers, design engineers, and others working on pushing the boundary of digitized manufacturing to include Design Engineering 4.0 principles in designing products, processes, and services.

Presents theoretical fundamentals for formulating design decisions in the context of industry 4.0