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Supply chain management in manufactu...

Rajendran, Suchithra.

Supply chain management in manufacturing and service systemsadvanced analytics for smarter decisions /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Supply chain management in manufacturing and service systemsedited by Sharan Srinivas, Suchithra Rajendran, Hans Ziegler.
Reminder of title:	advanced analytics for smarter decisions /
other author:	Srinivas, Sharan.
Published:	Cham :Springer International Publishing :2021.
Description:	xviii, 278 p. :ill. (some col.), digital ;24 cm.
Contained By:	Springer Nature eBook
Subject:	Business logistics.
Online resource:	https://doi.org/10.1007/978-3-030-69265-0
ISBN:	9783030692650$q(electronic bk.)

Supply chain management in manufacturing and service systemsadvanced analytics for smarter decisions /
Supply chain management in manufacturing and service systemsadvanced analytics for smarter decisions /[electronic resource] :edited by Sharan Srinivas, Suchithra Rajendran, Hans Ziegler. - Cham :Springer International Publishing :2021. - xviii, 278 p. :ill. (some col.), digital ;24 cm. - International series in operations research & management science,v.3040884-8289 ;. - International series in operations research & management science ;v. 140..

An Overview of Decisions, Performance and Analytics in Supply Chain Management -- Intelligent Digital Supply Chains -- Product Life Cycle Optimization Model for Closed Loop Supply Chain Network Design -- Supply Chain Risk Management in Indian Manufacturing Industries: An Empirical Study and a Fuzzy Approach -- Improving Service Supply Chain of Internet Services by Analyzing Online Customer Reviews -- An Integrated Problem of Production Scheduling and Transportation in a Two-Stage Supply Chain with Carbon Emission Consideration -- A Simulation-Based Evaluation of Drone Integrated Delivery Strategies for Improving Pharmaceutical Service -- Pro-Active Strategies in Online Routing -- Prescriptive Analytics for Dynamic Real Time Scheduling of Diffusion Furnaces.

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.

ISBN: 9783030692650$q(electronic bk.)

Standard No.: 10.1007/978-3-030-69265-0doiSubjects--Topical Terms:

199351
Business logistics.

LC Class. No.: HD38.5 / .S83 2021

Dewey Class. No.: 658.7

Supply chain management in manufacturing and service systemsadvanced analytics for smarter decisions /
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505 0 $a An Overview of Decisions, Performance and Analytics in Supply Chain Management -- Intelligent Digital Supply Chains -- Product Life Cycle Optimization Model for Closed Loop Supply Chain Network Design -- Supply Chain Risk Management in Indian Manufacturing Industries: An Empirical Study and a Fuzzy Approach -- Improving Service Supply Chain of Internet Services by Analyzing Online Customer Reviews -- An Integrated Problem of Production Scheduling and Transportation in a Two-Stage Supply Chain with Carbon Emission Consideration -- A Simulation-Based Evaluation of Drone Integrated Delivery Strategies for Improving Pharmaceutical Service -- Pro-Active Strategies in Online Routing -- Prescriptive Analytics for Dynamic Real Time Scheduling of Diffusion Furnaces.
520 $a 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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