Variation Modeling of Lean Manufacturing Performance Using Fuzzy Logic Based Quantitative Lean Index

Oleghe, Omogbai; Salonitis, Konstantinos

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dc.contributor.author	Oleghe, Omogbai
dc.contributor.author	Salonitis, Konstantinos
dc.date.accessioned	2016-12-16T11:06:18Z
dc.date.available	2016-12-16T11:06:18Z
dc.date.issued	2016-02-19
dc.identifier.citation	Oleghe O, Salonitis K, Variation Modeling of Lean Manufacturing Performance Using Fuzzy Logic Based Quantitative Lean Index, Procedia CIRP, Volume 41, 2016, Pages 608-613	en_UK
dc.identifier.issn	2212-8271
dc.identifier.uri	http://dx.doi.org/10.1016/j.procir.2016.01.008
dc.identifier.uri	https://dspace.lib.cranfield.ac.uk/handle/1826/11162
dc.description.abstract	The lean index is the sum of weighted scores of performance variables that describe the lean manufacturing characteristics of a system. Various quantitative lean index models have been advanced for assessing lean manufacturing performance. These models are represented by deterministic variables and do not consider variation in manufacturing systems. In this article variation is modeled in a quantitative fuzzy logic based lean index and compared with traditional deterministic modeling. By simulating the lean index model for a manufacturing case it is found that the latter tend to under or overestimate performance and the former provides a more robust lean assessment.	en_UK
dc.language.iso	en	en_UK
dc.publisher	Elsevier	en_UK
dc.rights	2212-8271 © 2015 The Authors. Published by Elsevier B.V. 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 48th CIRP Conference on MANUFACTURING SYSTEMS - CIRP CMS 2015 doi:10.1016/j.procir.2016.01.008 Attribution-Non-Commercial-No Derivatives 3.0 Unported (CC BY-NC-ND 3.0). You are free to: Share — copy and redistribute the material in any medium or format. The licensor cannot revoke these freedoms as long as you follow the license terms. Under the following terms: Attribution — You must give appropriate credit, provide a link to the license, and indicate if changes were made. You may do so in any reasonable manner, but not in any way that suggests the licensor endorses you or your use. Information: Non-Commercial — You may not use the material for commercial purposes. No Derivatives — If you remix, transform, or build upon the material, you may not distribute the modified material. No additional restrictions — You may not apply legal terms or technological measures that legally restrict others from doing anything the license permits.
dc.subject	Lean manufacturing	en_UK
dc.subject	performance measurement	en_UK
dc.subject	variability analysis	en_UK
dc.title	Variation Modeling of Lean Manufacturing Performance Using Fuzzy Logic Based Quantitative Lean Index	en_UK
dc.type	Article	en_UK