Supply Chain Management in Manufacturing and Service Systems
Idioma: inglés
Editorial: Springer, Palgrave Macmillan Jun 2021, 2021
Serie: Libro 297 de 323 - International Series in Operations Research & Management Science
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This item is printed on demand - Print on Demand Titel. Neuware -Management of supply chains has been evolving rapidly over the last few years due to the inception of Industry 4.0, where businesses adopt automation technologies and data exchanges leading to dynamic and interconnected supply chain systems. Emphasizing on analytical approaches such as predictive and prescriptive modeling, this book presents state-of-the-art original research work dealing with advanced analytical models for the design, planning, and operation of the supply chain to provide faster and smarter decisions in the era of digitization.In particular, the book integrates machine learning and operations research models for faster and smarter decisions, presents prescriptive analytics models for strategic, tactical, and operational decision making in the supply chain, and addresses recent challenges such as sustainability in the supply chain, supply chain visibility, and supply chain digitalization. Key concepts are illustrated using real-life case studies, making thebook a valuable reference for researchers, technical professionals, and students.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 296 pp. Englisch.…
N° de ref. del artículo 9783030692643
- Título
- Supply Chain Management in Manufacturing and Service Systems
- Autor
- Sharan Srinivas
- Editorial
- Springer, Palgrave Macmillan Jun 2021
- Año de publicación
- 2021
- Estado
- Neu
- Encuadernación
- Buch
- Idioma
- inglés
- ISBN 10
- 3030692647
- ISBN 13
- 9783030692643
- Peso del artículo
- 612 gramos
- Dimensiones
- 241x160x22 mm
- Serie
- Libro 297 de 323: International Series in Operations Research & Management Science
Management of supply chains has been evolving rapidly over the last few years due to the inception of Industry 4.0, where businesses adopt automation technologies and data exchanges leading to dynamic and interconnected supply chain systems. Emphasizing on analytical approaches such as predictive and prescriptive modeling, this book presents state-of-the-art original research work dealing with advanced analytical models for the design, planning, and operation of the supply chain to provide faster and smarter decisions in the era of digitization.
In particular, the book integrates machine learning and operations research models for faster and smarter decisions, presents prescriptive analytics models for strategic, tactical, and operational decision making in the supply chain, and addresses recent challenges such as sustainability in the supply chain, supply chain visibility, and supply chain digitalization. Key concepts are illustrated using real-life case studies, making the book a valuable reference for researchers, technical professionals, and students.
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Acerca del autor
Dr. Sharan Srinivas is an Assistant Professor with a joint appointment in the Department of Industrial & Manufacturing Systems Engineering and the Department of Marketing at the University of Missouri. Dr. Srinivas received his Ph.D. in industrial engineering and operations research from Pennsylvania State University. He holds a Bachelor’s degree in industrial engineering from College of Engineering, Guindy, Anna University, India, a MS in industrial and systems engineering from Binghamton University, State University of New York (SUNY), and a MEng. in industrial engineering and operations research from the Pennsylvania State University.
Dr. Srinivas' area of specialization is data analytics and operations research with research interests in healthcare operations management, logistics, smart service systems, and supply chain. He has been an investigator on industry-based research projects. He has published over 20 scholarly articles in journals and his research work hasappeared in leading journals such as Computers and Industrial Engineering, Expert Systems with Applications, Transportation Research Part C: Emerging Technologies, Transportation Research Part E: Logistics and Transportation Review, International Journal of Medical Informatics. Dr. Srinivas has taught undergraduate, graduate, and MBA level courses that include topics pertaining to data analytics, machine learning, simulation, service systems, and supply chain optimization. He is also an active member of INFORMS and IISE professional societies, and has served numerous times as a session chair in their annual conferences. Dr. Srinivas is a certified six sigma black belt and recipient of multiple awards (INFORMS Koopman prize, Winemiller Excellence Award, Richard Wallace Faculty Grant, Penn State Doctoral Fellowship, Service Enterprise Engineering Fellowship).
Dr. Suchithra Rajendran is an Assistant Professor with a joint appointment in the Departmentof Industrial and Manufacturing Systems Engineering and the Department of Marketing at the University of Missouri, Columbia, USA. Prior to that, she served as a consultant for many private and public organizations on various collaborative projects. She holds a Bachelor's degree in industrial engineering from Anna University in India. Her graduate degrees are from the Pennsylvania State University, where she received a M.S. and a Ph.D. in industrial engineering and operations research.Dr. Rajendran's research interests include healthcare systems engineering, big data analytics, multiple criteria decision-making, and quality assurance. She is a Penn State National Science Foundation Center for Health Organization Transformation (NSF-CHOT) scholar, Service Enterprise Engineering fellow and also a recipient of the Richard Wallace Faculty Incentive Grant and DAAD-WISE Fellowship.
Prof. Dr. Hans Ziegler held the Chair for Production, Operations and Logistics Management in the School of Business, Economics and Information Systems at the University of Passau, Germany. He received a diploma in industrial engineering from the University of Karlsruhe (TH), Germany (now called Karlsruhe Institute of Technology), a doctoral degree in business and economics and a post-doctoral habilitation in business, both from the University of Paderborn, Germany. He had been on the faculty of the University of Paderborn and the Technical University of Darmstadt, Germany, before moving to the University of Passau. He has research interests in production, operations and logistics management. Professor Ziegler has published over 60 articles in peer-reviewed journals, conference proceedings and books.
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