Determination of process variability by using triangular fuzzy number to minimize production lead time in a dynamic Value Stream Mapping
This paper shows the incorporation of Value Stream Mapping (VSM) with triangular fuzzy numbers to determine variability and uncertainty in a conveyor manufacturing company. VSM is a pen and paper tool which is used to indicate wastes and bottleneck processes graphically and develop an action plan to...
| Main Authors: | , , , |
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| Format: | Article |
| Published: |
UTM Press
2023
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| Online Access: | http://psasir.upm.edu.my/id/eprint/100936/ |
| _version_ | 1848863452119957504 |
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| author | Thulasi, M. Faieza, A. A. Azfanizam, A. S. Leman, Z. |
| author_facet | Thulasi, M. Faieza, A. A. Azfanizam, A. S. Leman, Z. |
| author_sort | Thulasi, M. |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | This paper shows the incorporation of Value Stream Mapping (VSM) with triangular fuzzy numbers to determine variability and uncertainty in a conveyor manufacturing company. VSM is a pen and paper tool which is used to indicate wastes and bottleneck processes graphically and develop an action plan to enhance the production line. However, some weaknesses are identified in the conventional VSM where it fails to consider variability in a dynamic manufacturing environment. As such, this paper fills up the research gap by using Triangular Fuzzy Number (TFN) to illustrate time intervals, inventories and other variables of VSM operation. The purpose of this paper is to minimize total production lead time (TPLT) and total value-added time (TVAT) in the current value stream of the conveyor chain. More accurate details of variability in the dynamic manufacturing environment can be illustrated by a Triangular Fuzzy Number (TFN) of VSM. As a result, the future value stream map shows 50% and 22% reduction in TPLT and TVAT respectively compared to the current value stream. In conclusion, this paper also recommends that in order to optimize the accuracy of VSM analysis further, a discrete event simulation can be used to examine the fuzzy VSM. |
| first_indexed | 2025-11-15T13:33:08Z |
| format | Article |
| id | upm-100936 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T13:33:08Z |
| publishDate | 2023 |
| publisher | UTM Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1009362023-07-13T08:42:40Z http://psasir.upm.edu.my/id/eprint/100936/ Determination of process variability by using triangular fuzzy number to minimize production lead time in a dynamic Value Stream Mapping Thulasi, M. Faieza, A. A. Azfanizam, A. S. Leman, Z. This paper shows the incorporation of Value Stream Mapping (VSM) with triangular fuzzy numbers to determine variability and uncertainty in a conveyor manufacturing company. VSM is a pen and paper tool which is used to indicate wastes and bottleneck processes graphically and develop an action plan to enhance the production line. However, some weaknesses are identified in the conventional VSM where it fails to consider variability in a dynamic manufacturing environment. As such, this paper fills up the research gap by using Triangular Fuzzy Number (TFN) to illustrate time intervals, inventories and other variables of VSM operation. The purpose of this paper is to minimize total production lead time (TPLT) and total value-added time (TVAT) in the current value stream of the conveyor chain. More accurate details of variability in the dynamic manufacturing environment can be illustrated by a Triangular Fuzzy Number (TFN) of VSM. As a result, the future value stream map shows 50% and 22% reduction in TPLT and TVAT respectively compared to the current value stream. In conclusion, this paper also recommends that in order to optimize the accuracy of VSM analysis further, a discrete event simulation can be used to examine the fuzzy VSM. UTM Press 2023-03 Article PeerReviewed Thulasi, M. and Faieza, A. A. and Azfanizam, A. S. and Leman, Z. (2023) Determination of process variability by using triangular fuzzy number to minimize production lead time in a dynamic Value Stream Mapping. ASEAN Engineering Journal, 13 (1). pp. 163-168. ISSN 2586-9159 https://journals.utm.my/aej/article/view/18574 10.11113/aej.v13.18574 |
| spellingShingle | Thulasi, M. Faieza, A. A. Azfanizam, A. S. Leman, Z. Determination of process variability by using triangular fuzzy number to minimize production lead time in a dynamic Value Stream Mapping |
| title | Determination of process variability by using triangular fuzzy number to minimize production lead time in a dynamic Value Stream Mapping |
| title_full | Determination of process variability by using triangular fuzzy number to minimize production lead time in a dynamic Value Stream Mapping |
| title_fullStr | Determination of process variability by using triangular fuzzy number to minimize production lead time in a dynamic Value Stream Mapping |
| title_full_unstemmed | Determination of process variability by using triangular fuzzy number to minimize production lead time in a dynamic Value Stream Mapping |
| title_short | Determination of process variability by using triangular fuzzy number to minimize production lead time in a dynamic Value Stream Mapping |
| title_sort | determination of process variability by using triangular fuzzy number to minimize production lead time in a dynamic value stream mapping |
| url | http://psasir.upm.edu.my/id/eprint/100936/ http://psasir.upm.edu.my/id/eprint/100936/ http://psasir.upm.edu.my/id/eprint/100936/ |