Agent Based Model for Complex Flow Shop Manufacturing Systems with Customer-Related Production Disruptions

Tunde Victor Adediran; Ammar Al Bazi

doi:10.1109/ICITECH.2017.8079943

Agent Based Model for Complex Flow Shop Manufacturing Systems with Customer-Related Production Disruptions

Tunde Victor Adediran, Ammar Al Bazi

Research output: Chapter in Book/Report/Conference proceeding › Conference proceeding › peer-review

3 Citations (Scopus)

51 Downloads (Pure)

Abstract

There have been number of frameworks and approaches proposed for the study of complex flow shop manufacturing systems. However, due to the continuous effects of customer disruptions such as cancellation, change in sequence and due time on flow shop production, there arise need to develop an adaptive system to respond to the effect of such disruptions. In this ongoing PhD work, we develop a Framework and Agent-Based Model to simulate flow shop production line and investigate the disruptions consequences and recovery strategy. An experimental case study using an Original Equipment Manufacturer (OEM) factory for automotive parts is adopted to verify and validate the proposed system. The new understanding presented in this work offers informed decision-making policies for manufacturing production activities.

Original language	English
Title of host publication	2017 8th International Conference on Information Technology (ICIT)
Publisher	IEEE
Pages	767-773
Number of pages	7
ISBN (Electronic)	978-1-5090-6332-1
ISBN (Print)	978-1-5090-6333-8
DOIs	https://doi.org/10.1109/ICITECH.2017.8079943
Publication status	Published - 17 May 2017
Event	ICIT 2017 The 8th International Conference on Information Technology - Al-Zaytoonah University , Amman, Jordan Duration: 17 May 2017 → 18 May 2017

Conference

Conference	ICIT 2017 The 8th International Conference on Information Technology
Country/Territory	Jordan
City	Amman
Period	17/05/17 → 18/05/17

Bibliographical note

© 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.

Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

Keywords

agent-based modeling
manufacturing systems
production disruptions

Access to Document

10.1109/ICITECH.2017.8079943

Post-PrintAccepted author manuscript, 1.01 MBLicence: CC BY

Cite this

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title = "Agent Based Model for Complex Flow Shop Manufacturing Systems with Customer-Related Production Disruptions",

abstract = "There have been number of frameworks and approaches proposed for the study of complex flow shop manufacturing systems. However, due to the continuous effects of customer disruptions such as cancellation, change in sequence and due time on flow shop production, there arise need to develop an adaptive system to respond to the effect of such disruptions. In this ongoing PhD work, we develop a Framework and Agent-Based Model to simulate flow shop production line and investigate the disruptions consequences and recovery strategy. An experimental case study using an Original Equipment Manufacturer (OEM) factory for automotive parts is adopted to verify and validate the proposed system. The new understanding presented in this work offers informed decision-making policies for manufacturing production activities. ",

keywords = "agent-based modeling, manufacturing systems, production disruptions",

author = "Adediran, {Tunde Victor} and {Al Bazi}, Ammar",

note = "{\textcopyright} 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Copyright {\textcopyright} and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders. ; ICIT 2017 The 8th International Conference on Information Technology ; Conference date: 17-05-2017 Through 18-05-2017",

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AU - Al Bazi, Ammar

N1 - © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. Copyright © and Moral Rights are retained by the author(s) and/ or other copyright owners. A copy can be downloaded for personal non-commercial research or study, without prior permission or charge. This item cannot be reproduced or quoted extensively from without first obtaining permission in writing from the copyright holder(s). The content must not be changed in any way or sold commercially in any format or medium without the formal permission of the copyright holders.

PY - 2017/5/17

Y1 - 2017/5/17

N2 - There have been number of frameworks and approaches proposed for the study of complex flow shop manufacturing systems. However, due to the continuous effects of customer disruptions such as cancellation, change in sequence and due time on flow shop production, there arise need to develop an adaptive system to respond to the effect of such disruptions. In this ongoing PhD work, we develop a Framework and Agent-Based Model to simulate flow shop production line and investigate the disruptions consequences and recovery strategy. An experimental case study using an Original Equipment Manufacturer (OEM) factory for automotive parts is adopted to verify and validate the proposed system. The new understanding presented in this work offers informed decision-making policies for manufacturing production activities.

AB - There have been number of frameworks and approaches proposed for the study of complex flow shop manufacturing systems. However, due to the continuous effects of customer disruptions such as cancellation, change in sequence and due time on flow shop production, there arise need to develop an adaptive system to respond to the effect of such disruptions. In this ongoing PhD work, we develop a Framework and Agent-Based Model to simulate flow shop production line and investigate the disruptions consequences and recovery strategy. An experimental case study using an Original Equipment Manufacturer (OEM) factory for automotive parts is adopted to verify and validate the proposed system. The new understanding presented in this work offers informed decision-making policies for manufacturing production activities.

KW - agent-based modeling

KW - manufacturing systems

KW - production disruptions

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M3 - Conference proceeding

SN - 978-1-5090-6333-8

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BT - 2017 8th International Conference on Information Technology (ICIT)

PB - IEEE

T2 - ICIT 2017 The 8th International Conference on Information Technology

Y2 - 17 May 2017 through 18 May 2017

ER -

Agent Based Model for Complex Flow Shop Manufacturing Systems with Customer-Related Production Disruptions

Abstract

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Bibliographical note

Keywords

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