A knowledge graph-aided concept–knowledge approach for evolutionary smart product–service system development

In order to meet user expectations and to optimize user experience with a higher degree of flexibility and sustainability, the Smart product–service system (Smart PSS), as a novel value proposition paradigm considering both online and offline smartness, was proposed. However, conventional manners fo...

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Bibliographic Details
Main Authors: Li, Xinyu, Chen, Chun-Hsien, Zheng, Pai, Wang, Zuoxu, Jiang, Zuhua, Jiang, Zhixing
Other Authors: School of Electrical and Electronic Engineering
Format: Article
Language:English
Published: 2021
Subjects:
Online Access:https://hdl.handle.net/10356/146515
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Institution: Nanyang Technological University
Language: English
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Summary:In order to meet user expectations and to optimize user experience with a higher degree of flexibility and sustainability, the Smart product–service system (Smart PSS), as a novel value proposition paradigm considering both online and offline smartness, was proposed. However, conventional manners for developing PSS require many professional consultations and still cannot meet with the new features of Smart PSS, such as user context-awareness and ever-evolving knowledge management. Therefore, aiming to assist Smart PSS development cost-effectively, this paper adopted the knowledge graph (KG) technique and concept–knowledge (C-K) model to propose an evolutionary design approach. Two knowledge graphs are firstly established with open-source knowledge, prototype specifications, and user-generated textual data. Then, triggered by personalized requirements, four KG-aided C-K operators are conducted based on graph-based query patterns and computational linguistics algorithms, thus generating innovative solutions for evolving Smart PSS. To validate the performance of the proposed approach, a case study of a smart nursing bed fulfilling multiple personalized requirements is conducted, and the evaluation result of its knowledge evolution is acceptable. It hopes that this work can offer insightful guidance to industrial organizations in their development of Smart PSS.