%0 Conference Proceedings
%T Factors for Effective Learning in Production Networks to Improve Environmental Performance
%+ University of Cambridge [UK] (CAM)
%+ Technische Universität Munchen - Technical University Munich - Université Technique de Munich (TUM)
%+ Fraunhofer IWU Project Group Resource-Efficient Mechatronic Processing Machines
%A Schurig, Alexander
%A Despeisse, Mélanie
%A Unterberger, Eric
%A Evans, Steve
%A Reinhart, Gunther
%Z Part 5: Sustainability and Production Management
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B IFIP International Conference on Advances in Production Management Systems (APMS)
%C Tokyo, Japan
%Y Shigeki Umeda
%Y Masaru Nakano
%Y Hajime Mizuyama
%Y Nironori Hibino
%Y Dimitris Kiritsis
%Y Gregor von Cieminski
%3 Advances in Production Management Systems: Innovative Production Management Towards Sustainable Growth
%V AICT-459
%N Part I
%P 697-704
%8 2015-09-07
%D 2015
%R 10.1007/978-3-319-22756-6_85
%K Interfactory learning
%K Environmental performance
%K Learning collaboratively
%Z Computer Science [cs]Conference papers
%X There is evidence that the environmental performances of factories operating under similar circumstances vary greatly, even within one company. This indicates that production sites are operated in different ways which suggests a potential for improvement. Previous research shows that collaboration within production networks can improve factory performance. Learning collaboratively across factories is a promising approach to reduce the environmental impact of production sites. Several companies recognised this opportunity. Processes and systems to support knowledge and know-how exchange within their production network are already in place. In this research a literature review and interviews were carried out to explore factors that influence learning between factories. Such factors are critical to develop an effective tool enabling learning across factories and thus environmental performance improvements.
%G English
%Z TC 5
%Z WG 5.1
%2 https://hal.science/hal-01417636/document
%2 https://hal.science/hal-01417636/file/346972_1_En_85_Chapter.pdf
%L hal-01417636
%U https://hal.science/hal-01417636
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-TC5
%~ IFIP-WG
%~ IFIP-APMS
%~ IFIP-WG5-1
%~ IFIP-AICT-459