A novel data-driven graph-based requirement elicitation framework in the smart product-service system context

Zuoxu Wang, Chun Hsien Chen, Pai Zheng, Xinyu Li, Li Pheng Khoo

Research output: Journal article publicationJournal articleAcademic researchpeer-review

28 Citations (Scopus)

Abstract

Nowadays, industrial companies are facing ever-increasing challenges to generate new value-in-use and maintain their high competitiveness in the market. With the rapid development of Information and Communication Technology (ICT), IT is embedded in the products themselves, i.e. smart, connected products (SCPs) to generate values. Hence, an emerging value proposition paradigm, smart product-service system (Smart PSS) was introduced, by leveraging both SCPs and its generated services as a solution bundle to meet individual customer needs. Unlike other types of PSS, in Smart PSS, massive user-generated data and product-sensed data are collected during the usage phase, where potential requirements can be elicited readily in a value co-creation manner with context-awareness. Nevertheless, only few scholars discuss any systematic manner to support requirement elicitation in such context. To fill the gaps, this research proposes a novel data-driven graph-based requirement elicitation framework in the Smart PSS, so as to assist engineering/designers make better design improvement or new design concept generation in a closed-loop manner. It underlines the informatics-based approach by integrating heterogeneous data sources into a holistic consideration. Moreover, by leveraging graph-based approach, context-product-service information can be linked by the edges and nodes in-between them to derive reliable requirements. To validate its feasibility and advantages, an illustrative example of smart bicycle design improvement is further adopted. As an explorative study, it is hoped that this work provides useful insights for the requirement elicitation process in today's smart connected environment.

Original languageEnglish
Article number100983
JournalAdvanced Engineering Informatics
Volume42
DOIs
Publication statusPublished - Oct 2019
Externally publishedYes

Keywords

  • Data-driven design
  • Knowledge management
  • Product-service systems
  • Requirement elicitation
  • Value co-creation

ASJC Scopus subject areas

  • Information Systems
  • Artificial Intelligence

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