Please use this identifier to cite or link to this item: http://cmuir.cmu.ac.th/jspui/handle/6653943832/68329
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dc.contributor.authorWorrasete Tansuraten_US
dc.contributor.authorWichai Chattinnawaten_US
dc.date.accessioned2020-04-02T15:25:09Z-
dc.date.available2020-04-02T15:25:09Z-
dc.date.issued2020-01-01en_US
dc.identifier.other2-s2.0-85081096150en_US
dc.identifier.urihttps://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85081096150&origin=inwarden_US
dc.identifier.urihttp://cmuir.cmu.ac.th/jspui/handle/6653943832/68329-
dc.description.abstract© WCSE 2019. All rights reserved. Designing the supply chain network model that takes into account product quality could be one of the most key factors that significantly improve the performance of organizations and also affects the most customer satisfaction in a long-term period. However, this model is based on a single product and a single production stage. This paper aims at designing a three-echelon supply chain model including multiple suppliers, multiple manufacturers with multi-stages inspection, and multiple customers. The mathematical problem is formulated with Cost of Quality (COQ) integrated into Supply Chain Network Design (SCND) to minimize the total supply chain cost involving transportation costs and production costs. Further, the paper proposes a meta-heuristic called Particle Swarm Optimization algorithm used to solve the model for the supply chain lot size and sampling inspection strategy. From the numerical data of the case study, the developed technique can determine the minimum of total supply chain cost at quality inspection 30.95%.en_US
dc.subjectComputer Scienceen_US
dc.titleAnalysis of supply chain network design model with quality costen_US
dc.typeConference Proceedingen_US
article.title.sourcetitleProceedings of 2019 the 9th International Workshop on Computer Science and Engineering, WCSE 2019en_US
article.stream.affiliationsChiang Mai Universityen_US
Appears in Collections:CMUL: Journal Articles

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