Open AccessDecision‐making of product‐service system solution selection based on integrated weight and technique for order preference by similarity to an ideal solution
Author(s) -
Li Lianhui,
Mao Chunlei,
Lei Bingbing,
Gao Yang,
Liu Yang,
Huang George Q.
Publication year - 2020
Publication title -
iet collaborative intelligent manufacturing
Language(s) - English
Resource type - Journals
ISSN - 2516-8398
DOI - 10.1049/iet-cim.2020.0003
Subject(s) - ideal solution , topsis , weighting , selection (genetic algorithm) , similarity (geometry) , preference , consistency (knowledge bases) , computer science , data mining , product (mathematics) , service (business) , fuzzy logic , index (typography) , ideal (ethics) , operations research , artificial intelligence , mathematics , statistics , philosophy , geometry , epistemology , image (mathematics) , medicine , physics , economy , world wide web , economics , radiology , thermodynamics
Product‐service system (PSS) solution selection is of great significance to better meet the personalised needs of customers and ensure the subsequent implementation. The problems of incomplete index system, difficulty to obtain the value of the qualitative index and unreasonable single index weighting have a significant impact on the decision‐making of PSS solution selection. In response to these problems, a decision‐making framework of PSS solution selection is constructed. A comprehensive index system is established from the perspectives of multiple stakeholders. Expert evaluating with the fuzzy number and multi‐expert evaluation opinion combination is adopted for index value solving. Integration of objective and subjective weights is achieved based on the multi‐weight information consistency model and the candidate PSS solutions are ranked by technique for order preference by similarity to an ideal solution finally. An application case of automobile PSS solution selection is given to verify the effectiveness and rationality of the constructed decision‐making framework.