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Advances in Production Management Systems. Towards Smart Production Management Systems - IFIP WG 5.7 International Conference, APMS 2019, Austin, TX, USA, September 1-5, 2019, Proceedings, Part II (Paperback, 1st ed. 2019)
Loot Price: R3,138
Discovery Miles 31 380
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Advances in Production Management Systems. Towards Smart Production Management Systems - IFIP WG 5.7 International Conference, APMS 2019, Austin, TX, USA, September 1-5, 2019, Proceedings, Part II (Paperback, 1st ed. 2019)
Series: IFIP Advances in Information and Communication Technology, 567
Expected to ship within 10 - 15 working days
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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.
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