Process variability analysis in make-to-order production systems

Vehicle license number plate production in Nigeria faces high variability in terms of process times and inter-arrival times, resulting in poor production schedule reliability. This study aims to clarify the level of such variation and to provide process improvement strategies within plate production...

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Main Authors: S.C. Nwanya, C.N. Achebe, O.O. Ajayi, C.A. Mgbemene
Format: Article
Language:English
Published: Taylor & Francis Group 2016-12-01
Series:Cogent Engineering
Subjects:
Online Access:http://dx.doi.org/10.1080/23311916.2016.1269382
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author S.C. Nwanya
C.N. Achebe
O.O. Ajayi
C.A. Mgbemene
author_facet S.C. Nwanya
C.N. Achebe
O.O. Ajayi
C.A. Mgbemene
author_sort S.C. Nwanya
collection DOAJ
description Vehicle license number plate production in Nigeria faces high variability in terms of process times and inter-arrival times, resulting in poor production schedule reliability. This study aims to clarify the level of such variation and to provide process improvement strategies within plate production. The specific objectives herein include identifying assignable variables, estimating variability indices and minimizing variation by developing solutions to improve system performance. This study explores the variability pooling method in assessing potential cost-effective process improvements and a case study is conducted on four Nigerian vehicle license number plate production plants in order to demonstrate the applicability of the proposed technique. Structured questionnaires were circulated to plant workers and data collected from plant production records from 2012 to 2015 in seven production lines were analyzed. A preliminary study on the production lines revealed the coefficient of variation (CV) for the Awka, Gwagwalada, Lagos and Lagos State Plants, showing measured variability levels of 0.62, 0.67, 0.60 and 0.78, respectively. Comparatively, the results obtained after the variability pooling showed a significant improvement in performance characteristics, such as low CV levels, enabling a 68% increase in net annual income for each plant, as well as enhanced machine utilization.
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spelling doaj.art-6ba27e092291425197e1153fafa720082023-08-02T02:40:33ZengTaylor & Francis GroupCogent Engineering2331-19162016-12-013110.1080/23311916.2016.12693821269382Process variability analysis in make-to-order production systemsS.C. Nwanya0C.N. Achebe1O.O. Ajayi2C.A. Mgbemene3University of NigeriaUniversity of NigeriaCovenant UniversityUniversity of NigeriaVehicle license number plate production in Nigeria faces high variability in terms of process times and inter-arrival times, resulting in poor production schedule reliability. This study aims to clarify the level of such variation and to provide process improvement strategies within plate production. The specific objectives herein include identifying assignable variables, estimating variability indices and minimizing variation by developing solutions to improve system performance. This study explores the variability pooling method in assessing potential cost-effective process improvements and a case study is conducted on four Nigerian vehicle license number plate production plants in order to demonstrate the applicability of the proposed technique. Structured questionnaires were circulated to plant workers and data collected from plant production records from 2012 to 2015 in seven production lines were analyzed. A preliminary study on the production lines revealed the coefficient of variation (CV) for the Awka, Gwagwalada, Lagos and Lagos State Plants, showing measured variability levels of 0.62, 0.67, 0.60 and 0.78, respectively. Comparatively, the results obtained after the variability pooling showed a significant improvement in performance characteristics, such as low CV levels, enabling a 68% increase in net annual income for each plant, as well as enhanced machine utilization.http://dx.doi.org/10.1080/23311916.2016.1269382capability indicescontinuous improvementmake-to-ordervariability poolingvehicle license
spellingShingle S.C. Nwanya
C.N. Achebe
O.O. Ajayi
C.A. Mgbemene
Process variability analysis in make-to-order production systems
Cogent Engineering
capability indices
continuous improvement
make-to-order
variability pooling
vehicle license
title Process variability analysis in make-to-order production systems
title_full Process variability analysis in make-to-order production systems
title_fullStr Process variability analysis in make-to-order production systems
title_full_unstemmed Process variability analysis in make-to-order production systems
title_short Process variability analysis in make-to-order production systems
title_sort process variability analysis in make to order production systems
topic capability indices
continuous improvement
make-to-order
variability pooling
vehicle license
url http://dx.doi.org/10.1080/23311916.2016.1269382
work_keys_str_mv AT scnwanya processvariabilityanalysisinmaketoorderproductionsystems
AT cnachebe processvariabilityanalysisinmaketoorderproductionsystems
AT ooajayi processvariabilityanalysisinmaketoorderproductionsystems
AT camgbemene processvariabilityanalysisinmaketoorderproductionsystems