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Analytical target cascading for optimal configuration of cloud manufacturing services
Northwestern Polytech University, Peoples R China; Northwestern Polytech University, Peoples R China.
Northwestern Polytech University, Peoples R China.
Jinan University, Peoples R China.
Linköping University, Department of Management and Engineering, Environmental Technology and Management. Jinan University, Peoples R China; University of Vaasa, Finland. (PSI)ORCID iD: 0000-0001-8006-3236
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2017 (English)In: Journal of Cleaner Production, ISSN 0959-6526, E-ISSN 1879-1786, Vol. 151, 330-343 p.Article in journal (Refereed) Published
Abstract [en]

Combining with advanced technologies (e.g., cloud computing, Internet of Things, and service-oriented technology), cloud manufacturing was proposed and gained wide attention. By managing a huge amount of distributed and idle manufacturing resources to meet various manufacturing requirements, cloud manufacturing provides sustainable means for promoting cleaner production. Manufacturing service configuration plays an important role in implementing cloud manufacturing. Most research adopted central optimization methods to get optimal service configuration results. However, these all-in-one methods with an individual decision model can hardly maintain the autonomous decision rights of different service providers. Consequently, service providers may lose their flexibility to achieve private decision objectives, which is unfavorable for keeping the sustainable competitive advantages of enterprises. In this paper, a decentralized decision mechanism named analytical target cascading is introduced to solve the manufacturing service configuration problem. An analytical target cascading model for the manufacturing service configuration problem is proposed based on the hierarchical structure of cloud manufacturing system. Elements in the proposed model are formulated and solved in a loose coupling and distributed manner. The situation when alternative service providers owned autonomous decision rights to configure their respective upstream manufacturing stages is also considered. A case study is employed to verify the effectiveness of analytical target cascading in solving the manufacturing service configuration problem. It shows that analytical target cascading can not only obtain the same manufacturing service configuration results as central optimization method but also maintain the autonomous decision rights of different service providers. (C) 2017 Elsevier Ltd. All rights reserved.

Place, publisher, year, edition, pages
ELSEVIER SCI LTD , 2017. Vol. 151, 330-343 p.
Keyword [en]
Cloud manufacturing; Manufacturing service configuration; Analytical target cascading
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:liu:diva-137375DOI: 10.1016/j.jclepro.2017.03.027ISI: 000399624000029OAI: oai:DiVA.org:liu-137375DiVA: diva2:1096705
Note

Funding Agencies|National Science Foundation of China [51675441, 51475095]; 111 Project Grant [B13044]; Mistra REES (Resource Efficient and Effective Solutions) program - MISTRA; Swedish Foundation for Strategic Environmental Research [2014/16]; Circularis (Circular Economy through Innovating Design) project - VINNOVA, Swedens Innovation Agency [2016-03267]

Available from: 2017-05-18 Created: 2017-05-18 Last updated: 2017-06-16

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CiteExportLink to record
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Cite
Citation style
  • apa
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