Evaluation of pull production control strategies under uncertainty: An integrated fuzzy AHP-TOPSIS approach

Purpose: Just-In-Time (JIT) production has continuously been considered by industrial practitioners and researchers as a leading strategy for the yet popular Lean production. Pull Production Control Policies (PPCPs) are the major enablers of JIT that locally control the level of inventory by authori...

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Main Authors: Aydin Torkabadi, Rene Mayorga
Format: Article
Language:English
Published: OmniaScience 2018-03-01
Series:Journal of Industrial Engineering and Management
Subjects:
Online Access:http://www.jiem.org/index.php/jiem/article/view/2528
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spelling doaj-42aafff4b45041c0abb3c96aa63f4af92020-11-24T23:17:51ZengOmniaScienceJournal of Industrial Engineering and Management2013-84232013-09532018-03-0111116118410.3926/jiem.2528512Evaluation of pull production control strategies under uncertainty: An integrated fuzzy AHP-TOPSIS approachAydin Torkabadi0Rene Mayorga1University of ReginaUniversity of ReginaPurpose: Just-In-Time (JIT) production has continuously been considered by industrial practitioners and researchers as a leading strategy for the yet popular Lean production. Pull Production Control Policies (PPCPs) are the major enablers of JIT that locally control the level of inventory by authorizing the production in each station. Aiming to improve the PPCPs, three authorization mechanisms: Kanban, constant-work-in-process (ConWIP), and a hybrid system, are evaluated by considering uncertainty. Design/methodology/approach: Multi-Criteria Decision Making (MCDM) methods are successful in evaluating alternatives with respect to several objectives. The proposed approach of this study applies the fuzzy set theory together with an integrated Analytical Hierarchy Process (AHP) and a Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method. Findings: The study finds that hybrid Kanban-ConWIP pull production control policies have a better performance in controlling the studied multi-layer multi-stage manufacturing and assembly system. Practical implications: To examine the approach a real case from automobile electro mechanical part production industry is studied. The production system consists of multiple levels of manufacturing, feeding a multi-stage assembly line with stochastic processing times to satisfy the changing demand. Originality/value: This study proposes the integrated Kanban-ConWIP hybrid pull control policies and implements several alternatives on a multi-stage and multi-layer manufacturing and assembly production system. An integrated Fuzzy AHP TOPSIS method is developed to evaluate the alternatives with respect to several JIT criteria.http://www.jiem.org/index.php/jiem/article/view/2528Just-in-time manufacturing, Kanban system, hybrid control policy, multi criteria decision making, fuzzy TOPSIS
collection DOAJ
language English
format Article
sources DOAJ
author Aydin Torkabadi
Rene Mayorga
spellingShingle Aydin Torkabadi
Rene Mayorga
Evaluation of pull production control strategies under uncertainty: An integrated fuzzy AHP-TOPSIS approach
Journal of Industrial Engineering and Management
Just-in-time manufacturing, Kanban system, hybrid control policy, multi criteria decision making, fuzzy TOPSIS
author_facet Aydin Torkabadi
Rene Mayorga
author_sort Aydin Torkabadi
title Evaluation of pull production control strategies under uncertainty: An integrated fuzzy AHP-TOPSIS approach
title_short Evaluation of pull production control strategies under uncertainty: An integrated fuzzy AHP-TOPSIS approach
title_full Evaluation of pull production control strategies under uncertainty: An integrated fuzzy AHP-TOPSIS approach
title_fullStr Evaluation of pull production control strategies under uncertainty: An integrated fuzzy AHP-TOPSIS approach
title_full_unstemmed Evaluation of pull production control strategies under uncertainty: An integrated fuzzy AHP-TOPSIS approach
title_sort evaluation of pull production control strategies under uncertainty: an integrated fuzzy ahp-topsis approach
publisher OmniaScience
series Journal of Industrial Engineering and Management
issn 2013-8423
2013-0953
publishDate 2018-03-01
description Purpose: Just-In-Time (JIT) production has continuously been considered by industrial practitioners and researchers as a leading strategy for the yet popular Lean production. Pull Production Control Policies (PPCPs) are the major enablers of JIT that locally control the level of inventory by authorizing the production in each station. Aiming to improve the PPCPs, three authorization mechanisms: Kanban, constant-work-in-process (ConWIP), and a hybrid system, are evaluated by considering uncertainty. Design/methodology/approach: Multi-Criteria Decision Making (MCDM) methods are successful in evaluating alternatives with respect to several objectives. The proposed approach of this study applies the fuzzy set theory together with an integrated Analytical Hierarchy Process (AHP) and a Technique for Order Performance by Similarity to Ideal Solution (TOPSIS) method. Findings: The study finds that hybrid Kanban-ConWIP pull production control policies have a better performance in controlling the studied multi-layer multi-stage manufacturing and assembly system. Practical implications: To examine the approach a real case from automobile electro mechanical part production industry is studied. The production system consists of multiple levels of manufacturing, feeding a multi-stage assembly line with stochastic processing times to satisfy the changing demand. Originality/value: This study proposes the integrated Kanban-ConWIP hybrid pull control policies and implements several alternatives on a multi-stage and multi-layer manufacturing and assembly production system. An integrated Fuzzy AHP TOPSIS method is developed to evaluate the alternatives with respect to several JIT criteria.
topic Just-in-time manufacturing, Kanban system, hybrid control policy, multi criteria decision making, fuzzy TOPSIS
url http://www.jiem.org/index.php/jiem/article/view/2528
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