Advanced Search

Show simple item record

dc.contributor.authorUlutan, Durul
dc.contributor.authorIsler, Zulal
dc.contributor.authorKaya, Burak Erkan
dc.contributor.authorHekimoglu, Mustafa
dc.date.accessioned2023-10-19T15:11:36Z
dc.date.available2023-10-19T15:11:36Z
dc.date.issued2022
dc.identifier.issn2213-8463
dc.identifier.urihttps://hdl.handle.net/20.500.12469/5121
dc.description50th SME North American Manufacturing Research Conference (NAMRC) -- JUN 27-JUL 01, 2022 -- Purdue Univ, West Lafayette, INen_US
dc.description.abstract3D printing has moved from being a rapid prototyping tool to an additive manufacturing method within the last decade. Additive manufacturing can satisfy the need in dire situations where spare parts distribution is an issue but access to a 3D printer is much more likely and rapid than access to original parts. Managing inventories of spare parts can be tackled with more ease thanks to the reduced part types with additive manufacturing. While quality (in terms of reliability) of additively manufactured spare parts in terms of mechanical properties seem to be lower than original parts (particularly due to the inherent staircase appearance and the corresponding stress concentration zones that can lead to premature fatigue failure), use of post-processing subtractive techniques to correct such surface irregularities are found to improve reliability. While each process adds another layer of complexity to the cost minimization problem, demand uncertainty and risk of supply disruption represent the modern global problems faced recently. The problem tackled in this study is the joint optimization of the supply reliability considering the effect of laser polishing parameters and the demand uncertainty. In this problem, a condition of random breakdowns of identical products is considered. Also, the original supplier of machine components is subject to exogenous disruptions, such as strikes, raw material scarcity, or the COVID-19 pandemic. As a result, the optimum control policy with the right cost parameters was shown via numerical experiments originated from mathematical analyses. This optimality can be critical in managing the system in the best possible way, particularly during times of unforeseen circumstances such as pandemics. (C) 2022 Society of Manufacturing Engineers (SME). Published by Elsevier Ltd. All rights reserved. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/) Peer-review under responsibility of the Scientific Committee of the NAMRI/SME.en_US
dc.description.sponsorshipSMEen_US
dc.description.sponsorshipScientific and Technological Research Council of Turkey (TUBITAK) [219M243]en_US
dc.description.sponsorshipThe study is funded by the Scientific and Technological Research Council of Turkey (TUBITAK) with a grant number 219M243.en_US
dc.language.isoengen_US
dc.publisherElsevieren_US
dc.relation.ispartofManufacturing Lettersen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectDynamic Inventory ModelEn_Us
dc.subjectPoliciesEn_Us
dc.subjectAdditive manufacturingen_US
dc.subjectLaser polishingen_US
dc.subjectOptimizationen_US
dc.subjectSupply disruptionen_US
dc.subjectDemand uncertaintyen_US
dc.titleOptimum utilization of on-demand manufacturing and laser polishing in existence of supply disruption risken_US
dc.typeconferenceObjecten_US
dc.identifier.startpage17en_US
dc.identifier.endpage28en_US
dc.identifier.volume33en_US
dc.departmentN/Aen_US
dc.identifier.wosWOS:000880189100006en_US
dc.identifier.scopus2-s2.0-85139211056en_US
dc.institutionauthorN/A
dc.relation.publicationcategoryKonferans Öğesi - Uluslararası - Kurum Öğretim Elemanıen_US
dc.khas20231019-WoSen_US


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record