DC Field | Value | Language |
---|---|---|
dc.contributor | Department of Industrial and Systems Engineering | en_US |
dc.creator | Song, W | en_US |
dc.creator | Niu, Z | en_US |
dc.creator | Zheng, P | en_US |
dc.date.accessioned | 2021-11-09T07:10:28Z | - |
dc.date.available | 2021-11-09T07:10:28Z | - |
dc.identifier.issn | 0360-8352 | en_US |
dc.identifier.uri | http://hdl.handle.net/10397/91591 | - |
dc.language.iso | en | en_US |
dc.publisher | Pergamon Press | en_US |
dc.subject | Smart product service system | en_US |
dc.subject | Sustainability | en_US |
dc.subject | Rough set theory | en_US |
dc.subject | Best worst method | en_US |
dc.subject | Criteria importance though inter-criteria | en_US |
dc.subject | Correlation | en_US |
dc.title | Design concept evaluation of smart product-service systems considering sustainability : an integrated method | en_US |
dc.type | Journal/Magazine Article | en_US |
dc.identifier.volume | 159 | en_US |
dc.identifier.doi | 10.1016/j.cie.2021.107485 | en_US |
dcterms.abstract | Intelligent products and services are integrated into Smart product-service systems (PSS) through information and communication technology (ICT). Various feasible Smart PSS designs are usually created in the design stage, and the design concept selection directly affects the delivery performance of the Smart PSS. However, existing methods often require more comparisons, omit criteria objective weights, and consider less about the impact of information subjectivity and impreciseness on the Smart PSS design concept selection. To solve the problems, a new integrated method is proposed, which integrates both subjective and objective weights to improve the accuracy of evaluation. Firstly, for criteria weighting, the proposed approach integrates the merits of the Best Worst Method (BWM) in reducing the burden of pair-wise comparisons when determining the subjective weights, and the strengths of the Criteria Importance Though Inter-criteria Correlation (CRITIC) method in considering the correlation and contrast between all criteria when determining the objective weights. Then, Rough Set Theory is used to flexibly deal with the decision-making vagueness without much prior information. Finally, a case study of a smart washing machine is adopted to validate the effectiveness of the proposed method. | en_US |
dcterms.accessRights | embargoed access | en_US |
dcterms.bibliographicCitation | Computers and industrial engineering, Sep. 2021, v. 159, 107485 | en_US |
dcterms.isPartOf | Computers and industrial engineering | en_US |
dcterms.issued | 2021-09 | - |
dc.identifier.isi | WOS:000679957900017 | - |
dc.identifier.eissn | 1879-0550 | en_US |
dc.identifier.artn | 107485 | en_US |
dc.description.validate | 202111 bchy | en_US |
dc.description.oa | Not applicable | en_US |
dc.identifier.FolderNumber | a1047-n06 | - |
dc.identifier.SubFormID | 43847 | - |
dc.description.fundingSource | Others | en_US |
dc.description.fundingText | National Key Research and Development Program of China (No. 2019YFB1405502), and the National Natural Science Foundation of China (Grant No. 71971012, 71501006). It is also supported in part by the National Science and Technology Major Project (2017-Ⅰ-0011-00120) and the Fundamental Research Funds for the Central Universities. | en_US |
dc.description.pubStatus | Published | en_US |
dc.date.embargo | 2024.09.30 | en_US |
Appears in Collections: | Journal/Magazine Article |
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