Advances in Production Management Systems. Towards Smart Production Management Systems

丛 书 名：IFIP Advances in Information and Communication Technology

版本说明：1

作     者：Farhad Ameri Kathryn E. Stecke Gregor von Cieminski Dimitris Kiritsis 

I S B N：(纸本) 9783030299958;9783030299989 

出 版 社：Springer Cham 

出 版 年：1000年

页      数：XXVII, 645页

主 题 词：Computer-Aided Engineering (CAD, CAE) and Design Information Systems Applications (incl. Internet) Artificial Intelligence Computer Systems Organization and Communication Networks Coding and Information Theory e-Commerce/e-business 

摘      要：The two-volume set IFIP AICT 566 and 567 constitutes the refereed proceedings of the International IFIP WG 5.7 Conference on Advances in Production Management Systems, APMS 2019, held in Austin, TX, USA.;The 161 revised full papers presented were carefully reviewed and selected from 184 submissions. They discuss globally pressing issues in smart manufacturing, operations management, supply chain management, and Industry 4.0. The papers are organized in the following topical sections: lean production; production management in food supply chains; sustainability and reconfigurability of manufacturing systems; product and asset life cycle management in smart factories of industry 4.0; variety and complexity management in the era of industry 4.0; participatory methods for supporting the career choices in industrial engineering and management education; blockchain in supply chain management; designing and delivering smart services in the digital age; operations management in engineer-to-order manufacturing; the operator 4.0 and the Internet of Things, services and people; intelligent diagnostics and maintenance solutions for smart manufacturing; smart supply networks; production management theory and methodology; data-driven production management; industry 4.0 implementations; smart factory and IIOT; cyber-physical systems; knowledge management in design and manufacturing; collaborative product development; ICT for collaborative manufacturing; collaborative technoloy; applications of machine learning in production management; and collaborative technology.