Comparison Of Parallel Kanban-Base Stock System To Control Multi-Product Multi-Stage Production With Rework Through Simulation

A recent globalization challenge compels manufacturing industries to offer a large variety of products with varied demands to suit their customers’ needs. However, these complex scenarios have led to high work-in-process (WIP) and defects, thus inspires many researches to investigate the optimum wa...

Full description

Bibliographic Details
Main Author: Mustafa, Shaliza Azreen
Format: Thesis
Language:English
Published: 2016
Subjects:
Online Access:http://eprints.usm.my/41278/
http://eprints.usm.my/41278/1/SHALIZA_AZREEN_BINTI_MUSTAFA_24_Pages.pdf
_version_ 1848879246779351040
author Mustafa, Shaliza Azreen
author_facet Mustafa, Shaliza Azreen
author_sort Mustafa, Shaliza Azreen
building USM Institutional Repository
collection Online Access
description A recent globalization challenge compels manufacturing industries to offer a large variety of products with varied demands to suit their customers’ needs. However, these complex scenarios have led to high work-in-process (WIP) and defects, thus inspires many researches to investigate the optimum ways to manage this complex manufacturing system within the scope of production control system (PCS). Most research in PCS has previously focused on the ideal production system and rework is seldom being considered.This study aims to develop and to evaluate the performance of a new hybrid PCS known as Parallel Kanban-Base stock (PKB) system to regulate a multi-product multi-stage production with the entrance of rework. In contrast to the original hybrid kanban-base stock system, PKB system takes into account of three variants. First variant are two classes of the product families known as high-runner (HR) and low-runner (LR) based on the demand of the product mix. The second variant is the variations of dispatch rules to regulate product families categorized as high runner-low runner (HL) and low runner-high runner (LH). Third variant considered was two rework entrance policies classified as merge (MR) and original (OR). The studied systemshave been modeled using discrete-event simulation. The simulation results are analyzed based on statistical methods including analysis of variance, regression and response surface methodology. The selection of related parameters, variables and performance measures is relatively based on literature study and current practice of a case study company. This study has been divided into three cases. For Case 1, among rework entrance policies, predominantly MR rework entrance policy yields more desirable results as observed within the performance measures, compared to OR rework entrance policy. For Case 2, the results revealed that PKB system with different customer demands shows HL dispatch rule is superior to LH dispatch rule. For Case 3, PKB-HL-MR gives the optimum results compared to other models. Overall findings show that PKB system possesses the advantage of a Base stock System (for LR) by causing an approximately 1.3% higher total output and the advantage of a Kanban System (for HR) by having controllable WIP levels. Significantly, this research contributes to the knowledge in the area of PCS in multi-product multi-stage environment considering reworking process.For future research, this work can be extended to the analysis of more complicated system configurations such as a machine breakdownand run the simulation model for various types of industries.
first_indexed 2025-11-15T17:44:11Z
format Thesis
id usm-41278
institution Universiti Sains Malaysia
institution_category Local University
language English
last_indexed 2025-11-15T17:44:11Z
publishDate 2016
recordtype eprints
repository_type Digital Repository
spelling usm-412782018-08-10T08:27:13Z http://eprints.usm.my/41278/ Comparison Of Parallel Kanban-Base Stock System To Control Multi-Product Multi-Stage Production With Rework Through Simulation Mustafa, Shaliza Azreen TJ1-1570 Mechanical engineering and machinery A recent globalization challenge compels manufacturing industries to offer a large variety of products with varied demands to suit their customers’ needs. However, these complex scenarios have led to high work-in-process (WIP) and defects, thus inspires many researches to investigate the optimum ways to manage this complex manufacturing system within the scope of production control system (PCS). Most research in PCS has previously focused on the ideal production system and rework is seldom being considered.This study aims to develop and to evaluate the performance of a new hybrid PCS known as Parallel Kanban-Base stock (PKB) system to regulate a multi-product multi-stage production with the entrance of rework. In contrast to the original hybrid kanban-base stock system, PKB system takes into account of three variants. First variant are two classes of the product families known as high-runner (HR) and low-runner (LR) based on the demand of the product mix. The second variant is the variations of dispatch rules to regulate product families categorized as high runner-low runner (HL) and low runner-high runner (LH). Third variant considered was two rework entrance policies classified as merge (MR) and original (OR). The studied systemshave been modeled using discrete-event simulation. The simulation results are analyzed based on statistical methods including analysis of variance, regression and response surface methodology. The selection of related parameters, variables and performance measures is relatively based on literature study and current practice of a case study company. This study has been divided into three cases. For Case 1, among rework entrance policies, predominantly MR rework entrance policy yields more desirable results as observed within the performance measures, compared to OR rework entrance policy. For Case 2, the results revealed that PKB system with different customer demands shows HL dispatch rule is superior to LH dispatch rule. For Case 3, PKB-HL-MR gives the optimum results compared to other models. Overall findings show that PKB system possesses the advantage of a Base stock System (for LR) by causing an approximately 1.3% higher total output and the advantage of a Kanban System (for HR) by having controllable WIP levels. Significantly, this research contributes to the knowledge in the area of PCS in multi-product multi-stage environment considering reworking process.For future research, this work can be extended to the analysis of more complicated system configurations such as a machine breakdownand run the simulation model for various types of industries. 2016 Thesis NonPeerReviewed application/pdf en http://eprints.usm.my/41278/1/SHALIZA_AZREEN_BINTI_MUSTAFA_24_Pages.pdf Mustafa, Shaliza Azreen (2016) Comparison Of Parallel Kanban-Base Stock System To Control Multi-Product Multi-Stage Production With Rework Through Simulation. PhD thesis, Universiti Sains Malaysia.
spellingShingle TJ1-1570 Mechanical engineering and machinery
Mustafa, Shaliza Azreen
Comparison Of Parallel Kanban-Base Stock System To Control Multi-Product Multi-Stage Production With Rework Through Simulation
title Comparison Of Parallel Kanban-Base Stock System To Control Multi-Product Multi-Stage Production With Rework Through Simulation
title_full Comparison Of Parallel Kanban-Base Stock System To Control Multi-Product Multi-Stage Production With Rework Through Simulation
title_fullStr Comparison Of Parallel Kanban-Base Stock System To Control Multi-Product Multi-Stage Production With Rework Through Simulation
title_full_unstemmed Comparison Of Parallel Kanban-Base Stock System To Control Multi-Product Multi-Stage Production With Rework Through Simulation
title_short Comparison Of Parallel Kanban-Base Stock System To Control Multi-Product Multi-Stage Production With Rework Through Simulation
title_sort comparison of parallel kanban-base stock system to control multi-product multi-stage production with rework through simulation
topic TJ1-1570 Mechanical engineering and machinery
url http://eprints.usm.my/41278/
http://eprints.usm.my/41278/1/SHALIZA_AZREEN_BINTI_MUSTAFA_24_Pages.pdf