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Title: A data-driven reversible framework for achieving sustainable smart product-service systems
Authors: Li, Xinyu
Wang, Zuoxu
Chen, Chun-Hsien
Zheng, Pai
Keywords: Engineering::Electrical and electronic engineering
Engineering::Mechanical engineering
Issue Date: 2021
Source: Li, X., Wang, Z., Chen, C. & Zheng, P. (2021). A data-driven reversible framework for achieving sustainable smart product-service systems. Journal of Cleaner Production, 279, 123618-.
Project: RCA-16/434
Journal: Journal of Cleaner Production
Abstract: Higher sustainability with extended product lifecycle is a tireless pursuit in companies’ product design/development endeavours. In this regard, two prevailing concepts, namely the smart circular system and smart product-service system (Smart PSS), have been introduced, respectively. However, most existing studies only focus on the sustainability of physical materials and components, without considering the cyber-physical resources as a whole, let alone an integrated strategy towards the so-called Sustainable Smart PSS. To fill the gap, this paper discusses the key features in Sustainable Smart PSS development from a broadened scope of cyber-physical resources management. A data-driven reversible framework is hereby proposed to sustainably exploit high-value and context-dependent information/knowledge in the development of Sustainable Smart PSS. A four-step context-aware process in the framework, including requirement elicitation, solution recommendation, solution evaluation, and knowledge evolvement, is further introduced to support the decision-making and optimization along the extended or circular lifecycle. An illustrative example is depicted in the sustainable development of a smart 3D printer, which validates the feasibility and advantages of the proposed framework. As an explorative study, it is hoped that this work provides useful insights for Smart PSS development with sustainability concerns in a cyber-physical environment.
ISSN: 0959-6526
DOI: 10.1016/j.jclepro.2020.123618
Schools: School of Electrical and Electronic Engineering 
School of Mechanical and Aerospace Engineering 
Research Centres: Delta-NTU Corporate Laboratory for Cyber-Physical Systems
Rights: © 2020 Elsevier Ltd. All rights reserved.
Fulltext Permission: none
Fulltext Availability: No Fulltext
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