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Intelligent inventory management with autonomation and service strategy

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dc.contributor.authorDey, Bikash Koli-
dc.contributor.authorSeok, Hyesung-
dc.date.accessioned2022-11-22T05:41:35Z-
dc.date.available2022-11-22T05:41:35Z-
dc.date.issued2022-01-01-
dc.identifier.issn0956-5515-
dc.identifier.issn1572-8145-
dc.identifier.urihttps://scholarworks.bwise.kr/hongik/handle/2020.sw.hongik/30577-
dc.description.abstractThe manufacturer's service to the customer is one of the critical factors in maximizing profit. This study proposes the innovative (Q, r) inventory policy integrated with autonomated inspection and service strategy for service-dependent demand. First, an advanced autonomated inspection makes the product error-free. Therefore, this makes customers more satisfied and increases profit. The proposed model decides the optimal investment for such autonomated inspection. Second, three types of services are considered in the study: unpaid, partially paid, and fully paid services. Each type of service has a different service level and the amount of the customer's payment. Our model finds the optimal service strategy based on the variable conditions along with the optimal quantity and reorder level of inventory policy. Numerical analyses are made for different service strategies, along with a sensitivity analyses for various critical parameters. Results show that the full paid service is 84.88% beneficial compared to the unpaid service, and the autonomated inspection policy is 5.02% beneficial compared to the traditional ones. The increase in unit servicing costs always increases the profit of the company.-
dc.format.extent24-
dc.language영어-
dc.language.isoENG-
dc.publisherSPRINGER-
dc.titleIntelligent inventory management with autonomation and service strategy-
dc.typeArticle-
dc.publisher.location네델란드-
dc.identifier.doi10.1007/s10845-022-02046-4-
dc.identifier.scopusid2-s2.0-85141717134-
dc.identifier.wosid000881600000002-
dc.identifier.bibliographicCitationJOURNAL OF INTELLIGENT MANUFACTURING, v.35, no.1, pp 307 - 330-
dc.citation.titleJOURNAL OF INTELLIGENT MANUFACTURING-
dc.citation.volume35-
dc.citation.number1-
dc.citation.startPage307-
dc.citation.endPage330-
dc.type.docTypeArticle; Early Access-
dc.description.isOpenAccessY-
dc.description.journalRegisteredClassscie-
dc.description.journalRegisteredClassscopus-
dc.relation.journalResearchAreaComputer Science-
dc.relation.journalResearchAreaEngineering-
dc.relation.journalWebOfScienceCategoryComputer Science, Artificial Intelligence-
dc.relation.journalWebOfScienceCategoryEngineering, Manufacturing-
dc.subject.keywordPlusOPTIMAL SELLING PRICE-
dc.subject.keywordPlusSETUP COST REDUCTION-
dc.subject.keywordPlusSUPPLY CHAIN-
dc.subject.keywordPlusEOQ MODEL-
dc.subject.keywordPlusINSPECTION ERRORS-
dc.subject.keywordPlusLEVEL CONSTRAINTS-
dc.subject.keywordPlusSPARE PARTS-
dc.subject.keywordPlusSYSTEM-
dc.subject.keywordPlusQUALITY-
dc.subject.keywordPlusOPTIMIZATION-
dc.subject.keywordAuthorInspection-
dc.subject.keywordAuthorProfit maximization-
dc.subject.keywordAuthorService dependent demand-
dc.subject.keywordAuthor(Q-
dc.subject.keywordAuthorr) model-
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