A discrete stress–strength interference theory-based dynamic supplier selection model for maintenance service outsourcing

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DOIResolve DOI: http://doi.org/10.1109/TEM.2016.2527684
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TypeArticle
Journal titleIEEE Transactions on Engineering Management
ISSN0018-9391
1558-0040
Volume63
Issue2
Pages189200
SubjectDemand fulfillment level; Maintenance service outsourcing; Stress–strength interference (SSI) theory; Supplier reliability; Supplier selection
AbstractMaintenance service outsourcing is a strategic driver for asset intensive industries pursuing the enhancement of supply chain performance. Maintenance service supplier selection plays a relevant role in this premise since its significant impact on equipment availability, and hence, on business success. To periodically review suppliers' performances and update the outsourcing contract, a discrete stress-strength interference (DSSI) theory-based dynamic supplier selection model is presented for maintenance service outsourcing process. Taken account of the influence of randomness and uncertainty, a novel and universal evaluation criterion, demand fulfillment level (DFL) is introduced based on the DSSI theory. DFL is relevant to two random variables, which are random user's service order quantity (stress) and random supplier's service fulfillment quantity (strength), and DFL is defined as the probability that the latter (strength) is larger than the former (stress). Based on DFL, the proposed model can help users outsource the corresponding maintenance service to the most suitable supplier (maximum supplier reliability) at different periods. The decision rule can be described as a dynamic 3-D diagram, according to which decision makers can periodically review suppliers' performances and update the outsourcing contract. A case study on maintenance service supplier selection problem for a steel company illustrates the effectiveness of the proposed model.
Publication date
PublisherIEEE
LanguageEnglish
AffiliationConstruction; National Research Council Canada
Peer reviewedYes
NPARC number23000398
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Record identifier9a90cbff-9fe9-4e0b-a57f-4f264c4d6c9e
Record created2016-07-13
Record modified2016-07-13
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