A MULTI-STAGE OPTIMISATION METHOD FOR THE MANAGEMENT OF AN ON-DEMAND FIXTURE MANUFACTURING CELL FOR MASS CUSTOMISATION PRODUCTION SYSTEMS

The implementation of reconfigurable fixtures is a major facilitator of mass customisation. Traditional scheduling techniques do not consider reconfigurable fixtures comprehensively. This paper describes a multi-stage optimisation method that manages the recirculation of reconfigurable fixtures in a...

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Main Authors: Naidoo, Enrico, Padayachee, Jared, Bright, Glen
Format: Article
Language:English
Published: Stellenbosch University 2018-08-01
Series:South African Journal of Industrial Engineering
Subjects:
Online Access:http://sajie.journals.ac.za/pub/article/view/1824
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spelling doaj-fd46d642f100490494608c096131e53d2020-11-25T03:52:32ZengStellenbosch UniversitySouth African Journal of Industrial Engineering1012-277X2224-78902018-08-01292526410.7166/29-2-1824A MULTI-STAGE OPTIMISATION METHOD FOR THE MANAGEMENT OF AN ON-DEMAND FIXTURE MANUFACTURING CELL FOR MASS CUSTOMISATION PRODUCTION SYSTEMSNaidoo, Enrico0Padayachee, Jared 1Bright, Glen2University of KwaZulu-Natal, South AfricaUniversity of KwaZulu-Natal, South AfricaUniversity of KwaZulu-Natal, South AfricaThe implementation of reconfigurable fixtures is a major facilitator of mass customisation. Traditional scheduling techniques do not consider reconfigurable fixtures comprehensively. This paper describes a multi-stage optimisation method that manages the recirculation of reconfigurable fixtures in a mass customisation production system. The method was based on an on-demand fixture manufacturing cell that served a part processing cell. The method consists of three stages: using established techniques such as k-means clustering and hierarchical clustering; and a novel mixed integer linear programming (MILP) model to optimise operation sequences. Minimisation of total idle time (and thus makespan) was used as the measure of performance.http://sajie.journals.ac.za/pub/article/view/1824mass customisationreconfigurable fixturesscheduling and optimisationcellular manufacturing systemscluster analysismixed integer linear programming
collection DOAJ
language English
format Article
sources DOAJ
author Naidoo, Enrico
Padayachee, Jared
Bright, Glen
spellingShingle Naidoo, Enrico
Padayachee, Jared
Bright, Glen
A MULTI-STAGE OPTIMISATION METHOD FOR THE MANAGEMENT OF AN ON-DEMAND FIXTURE MANUFACTURING CELL FOR MASS CUSTOMISATION PRODUCTION SYSTEMS
South African Journal of Industrial Engineering
mass customisation
reconfigurable fixtures
scheduling and optimisation
cellular manufacturing systems
cluster analysis
mixed integer linear programming
author_facet Naidoo, Enrico
Padayachee, Jared
Bright, Glen
author_sort Naidoo, Enrico
title A MULTI-STAGE OPTIMISATION METHOD FOR THE MANAGEMENT OF AN ON-DEMAND FIXTURE MANUFACTURING CELL FOR MASS CUSTOMISATION PRODUCTION SYSTEMS
title_short A MULTI-STAGE OPTIMISATION METHOD FOR THE MANAGEMENT OF AN ON-DEMAND FIXTURE MANUFACTURING CELL FOR MASS CUSTOMISATION PRODUCTION SYSTEMS
title_full A MULTI-STAGE OPTIMISATION METHOD FOR THE MANAGEMENT OF AN ON-DEMAND FIXTURE MANUFACTURING CELL FOR MASS CUSTOMISATION PRODUCTION SYSTEMS
title_fullStr A MULTI-STAGE OPTIMISATION METHOD FOR THE MANAGEMENT OF AN ON-DEMAND FIXTURE MANUFACTURING CELL FOR MASS CUSTOMISATION PRODUCTION SYSTEMS
title_full_unstemmed A MULTI-STAGE OPTIMISATION METHOD FOR THE MANAGEMENT OF AN ON-DEMAND FIXTURE MANUFACTURING CELL FOR MASS CUSTOMISATION PRODUCTION SYSTEMS
title_sort multi-stage optimisation method for the management of an on-demand fixture manufacturing cell for mass customisation production systems
publisher Stellenbosch University
series South African Journal of Industrial Engineering
issn 1012-277X
2224-7890
publishDate 2018-08-01
description The implementation of reconfigurable fixtures is a major facilitator of mass customisation. Traditional scheduling techniques do not consider reconfigurable fixtures comprehensively. This paper describes a multi-stage optimisation method that manages the recirculation of reconfigurable fixtures in a mass customisation production system. The method was based on an on-demand fixture manufacturing cell that served a part processing cell. The method consists of three stages: using established techniques such as k-means clustering and hierarchical clustering; and a novel mixed integer linear programming (MILP) model to optimise operation sequences. Minimisation of total idle time (and thus makespan) was used as the measure of performance.
topic mass customisation
reconfigurable fixtures
scheduling and optimisation
cellular manufacturing systems
cluster analysis
mixed integer linear programming
url http://sajie.journals.ac.za/pub/article/view/1824
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