Hardback : £168.00
"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.
"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.
Frame of Reference.- Foundations for Design Decision Support in Model Based Realization of Complex Engineered Systems.- Ontology for Decision Support Problems Templates.- Ontology for Designing Decision Workflows.- PDSIDES: A Knowledge-Based Platform for Decision Support in the Design of Engineering Systems.- Design of a Hot Rod Rolling System Using PDSIDES.- Conclduing Remarks.
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
suggest that this uncertainty could be managed with robust design.
Janet Allen and her research group have co-authored one textbook
and three monographs and more than 300 technical articles. She is a
member of several academic and professional organizations, and is a
Fellow of the American Society of Mechanical Engineers, a Senior
Member of the American Institute of Aeronautics and Astronautics
and is an Honorary Member of the Mechanical Engineering Honor
Society Pi Tau Sigma. Professor Allen co-directs the Systems
Realization Laboratory @ OU with Professor Farrokh Mistree.
Guoxin Wang is a Professor of School of Mechanical Engineering at
Beijing Institute of Technology (BIT). He is a Senior Member of the
Chinese Society of Mechanical Engineers. Professor Wang directs and
has accomplished 30 projects from the National Nature Science
Foundation of China, the National High-Tech. R&D Program, and
the National and International Enterprise Research Foundation. He
has published over 80 papers and two books. His research interests
include knowledge-based engineering, model-based system engineering
and reconfigurable manufacturing systems.
Yan Yan is a Professor of the School of Mechanical Engineering at
Beijing Institute of Technology (BIT). She is also the Dean of the
Department of Human Resource at BIT. Professor Yan received her
Bachelor’s degree in 1989 and her PhD in 2001, both of them are in
Mechanical Engineering at BIT. Her research interests include
digital platform for design and manufacturing, knowledge-based
engineering, decision-based design, and artificial intelligence in
design and manufacturing. She has accomplished tens of projects
funded by the Chinese NSF, Beijing NSF, and Chinese Key R&D
Programs. Professor Yan has received seven National Science and
Technology Advance Awards, one National Teaching Award. She has
been granted more than ten patents in China, published three
textbooks and two monographs (in Chinese), published more than
eighty journal papers (in Chinese and English). She is a member of
the Teaching Steering Committee of Industrial Engineering Specialty
of China Ministry of Education, a member of the Chinese Society of
Mechanical Engineers, an expert of Advance Design and Manufacturing
in the Chinese Key R&D Programs.
Professor Farrokh Mistree holds the L. A. Comp Chair in the School
of Aerospace and Mechanical Engineering at the University of
Oklahoma in Norman, Oklahoma. He received his B. Tech (Hons) degree
in Naval Architecture in 1967 from the Indian Institute of
Technology, Kharagpur and his Ph.D. in Engineering from the
University of California, Berkeley in 1974. He has co-authored two
textbooks, four monographs and more than 400 technical papers. His
current research focus is on collaboratively defining the emerging
frontier for the “intelligent” evolving cyber-physical-social
systems when the computational models are incomplete and
inaccurate. He is aFellow of ASME, an Associate Fellow of AIAA, a
Life Member of The Honor Society of Phi Kappa Phi and a Member of
ASEE, RINA and SNAME. Professor Mistree co-directs the Systems
Realization Laboratory @ OU with Professor Janet K. Allen in
Industrial and Systems Engineering.
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