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Smart box-enabled product–service system for cloud logistics
Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, School of Mechanical Engineering, Northwestern Polytechnical University, Shaanxi, China.
Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, School of Mechanical Engineering, Northwestern Polytechnical University, Shaanxi, China.
Department of Production, University of Vaasa, Vaasa, Finland.ORCID iD: 0000-0001-8006-3236
Key Laboratory of Contemporary Design and Integrated Manufacturing Technology, School of Mechanical Engineering, Northwestern Polytechnical University, Shaanxi, China.
2016 (English)In: International Journal of Production Research, ISSN 0020-7543, E-ISSN 1366-588X, Vol. 54, no 22, 6693-6706 p.Article in journal (Refereed) Published
Abstract [en]

Modern logistics takes significant progress and rapid developments with the prosperity of E-commerce, particularly in China. Typical challenges that logistics industry is facing now are composed by a lack of sharing, standard, cost-effective and environmental package and efficient optimisation method for logistics tasks distribution. As a result, it is difficult to implement green, sustainable logistics services. Three important technologies, Physical Internet (PI), product–service system (PSS) and cloud computing (CC), are adopted and developed to address the above issues. PI is extended to design a world-standard green recyclable smart box that is used to encapsulate goods. Smart box-enabled PSS is constructed to provide an innovative sustainable green logistics service, and high-quality packaging, as well as reduce logistics cost and environmental pollution. A real-time information-driven logistics tasks optimisation method is constructed by designing a cloud logistics platform based on CC. On this platform, a hierarchical tree-structure network for customer orders (COs) is built up to achieve the order-box matching of function. Then, a distance clustering analysis algorithm is presented to group and form the optimal clustering results for all COs, and a real-time information-driven optimisation method for logistics orders is proposed to minimise the unused volume of containers. Finally, a case study is simulated to demonstrate the efficiency and feasibility of proposed cloud logistics optimisation method. © 2016 Informa UK Limited, trading as Taylor & Francis Group.

Place, publisher, year, edition, pages
Taylor & Francis, 2016. Vol. 54, no 22, 6693-6706 p.
Keyword [en]
Physical Internet, logistics, smart box, product–service system, cloud computing
National Category
Transport Systems and Logistics Computer Engineering Computational Mathematics
Identifiers
URN: urn:nbn:se:liu:diva-133460DOI: 10.1080/00207543.2015.1134840Scopus ID: 2-s2.0-84954212012OAI: oai:DiVA.org:liu-133460DiVA: diva2:1060451
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Available from: 2016-12-28 Created: 2016-12-28 Last updated: 2016-12-28Bibliographically approved

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CiteExportLink to record
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Citation style
  • apa
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