A design method for edge–cloud collaborative product service system: a dynamic event-state knowledge graph-based approach with real case study

ABSTRACTABSTRACTProduct service system (PSS) is an effective approach to achieve win–win situation between service providers and consumers, and the design of PSS is the first step of its application. However, on the one hand, PSS is relatively an abstract concept, and what exactly should be considered when designing a PSS still require further exploration; on the other hand, the fast development of information and web technologies bring both opportunities and challenges for PSS design. For example, how to efficiently design the smart & connected products that support remote monitoring and control of service operation, how to build the dynamic service activity flow model that can be intuitively and visually read by human engineers and also can be conveniently deployed on computers, and how to realise edge–cloud collaboration between service providers and consumers. In this regard, a service requirement-oriented four-step generic PSS design method is established, including service mode selection and structured service order generation → smart & connected service product configuration → dynamic event-state knowledge graph-based service activity flow and service resource network configuration → industrial internet-based edge–cloud collaborative service delivering. Finally, a real design case of carbon block grinding and polishing PSS is used for verification.ABBREVIATIONS: AS: assembly service; C: controlling targets or objectives; I: input; M: enabling methods or mechanisms; MRO: maintenance, repair, and operation; MS: maintenance service; O: output; OEE: overall equipment effectiveness; PSS: product service system; PV: processing volume; RxEy-Sz: the relation from Event y to the State z of Service activity x; RxSz-Ey: the relation from the State z of Service activity x to Event y; StateAiCurrent: the current state of Service activity i; StateAiFuturek: the kth possible future state of Service activity i; StateAiHistoryj: the jth historical state of service activity i; StateEy: the state of Event y; Tq: the qth time point in the time line.KEYWORDS: Industrial product service systemservice activity flowservice resource networkdynamic event-state knowledge graphindustrial internet service platform Disclosure statementNo potential conflict of interest was reported by the author(s).Data availability statementData sharing is not applicable to this article as no new data were created or analysed in this study.Additional informationFundingThis work was supported by National Key Research and Development Program of China [grant number 2021YFE0116300].Notes on contributorsMaolin YangMaolin Yang received his Bachelor degree in Mechanical Engineering from Tongji University in 2012, and PhD degree in Mechanical Engineering from Xi’an Jiaotong University (XJTU) in 2021. Currently, he is an assistant professor at the State Key Laboratory of Manufacturing Systems Engineering in XJTU. His research interests include social manufacturing, product service systems, data-driven intelligent product design, crowdsourcing decision, etc.Yuqian YangYuqian Yang is a doctoral candidate in mechanical engineering at Xi’an Jiaotong University, China. He is the general manager of Shandong cloud imagination Technology Co., Ltd. He is also a senior engineer. He was rated as a high-level talent in Yantai, Shandong Province. Mr Yang has participated in 3 major projects and has 37 patents for inventions and utility models. Mr Yang is an author for six academic papers. His current research interest is systems engineering for manufacturing and services, including intelligent equipments, cyber-physical systems, product service systems, etc.Pingyu JiangPingyu Jiang is a professor of the state key laboratory for manufacturing systems engineering at Xi’an Jiatong University (XJTU), China. He received his PhD degree in mechanical engineering from XJTU in 1991 and held Humboldt and JSPS international research fellowships from 1995 to 1999 in Germany and Japan, respectively. Prof. Jiang has been a faculty member at XJTU since 1991 and was promoted to full professor in 1999. His current research interests include social manufacturing, cyber-physical systems, product service systems, data-driven intelligent product design, etc.