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English
Academic Press Inc
18 April 2023
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.

Edited by:   , , ,
Imprint:   Academic Press Inc
Country of Publication:   United Kingdom
Dimensions:   Height: 229mm,  Width: 152mm, 
ISBN:   9780323992084
ISBN 10:   0323992080
Pages:   430
Publication Date:  
Audience:   Professional and scholarly ,  Undergraduate
Format:   Paperback
Publisher's Status:   Active
PART I: SMART MANUFACTURING DESIGN 1. Factories of the Future 2. Cloud Manufacturing Applications 3. Industry 4.0 Technologies Assessment 4. Human Factor Within Industry 4.0 Environments 5. Design of Jobs for People in Industry 4.0 PART II: INDUSTRY 4.0 INFORMATION TECHNOLOGY DEVELOPMENTS 1. Artificial Intelligence in Industry 4.0 2. Robotic Operating Systems interoperability for manufacturing environments 3. Cyberspace Modelling for Smart Manufacturing Problems 4. Resource-Based Manufacturing Processes 5. Software Validation for Industry 4.0 PART III: INDUSTRY 4.0 BUSINESS DEVELOPMENTS 1. Sustainable Business Models for Smart Manufacturing Systems 2. Digital Transformation of Enterprise 3. How Industry 4.0 has Changed SMEs 4. Funding Options for Enterprise Digital Transformations 5. Investment for Sustainable and Smart Manufacturing 6. Business Processes in Collaborative Smart Manufacturing Environments 7. Smart Contracts for Industry PART IV: INDUSTRY 4.0 PRODUCTION PLANNING AND DECISION MAKING 1. Production Planning and Control in Industry 4.0 2. Scheduling in Smart Manufacturing 3. Maintenance Planning in Smart Manufacturing 4. Digital Transformation of Maintenance Management 5. Digital Twin and Prognosis for Industrial Maintenance

Chaudhery Mustansar Hussain, PhD, is an adjunct professor and director of laboratories in the Department of Chemistry & Environmental Science 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, smart materials and technologies, 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 hundred (100) books, including scientific monographs and handbooks in his research areas. He has published with ELSEVIER, American Chemical Society, Royal Society of Chemistry, SPRINGER John Wiley & Sons, and CRC Press. 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, Bahia 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.

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