Improvement of production process variations of bolster spring of a train bogie manufacturing industry: a six-sigma approach.
Daniyan, Ilesanmi Adeodu, Adefemi Mpofu, Khumbulani Maladzhi, Rendani Kanakana-Katumba, Grace Mukondeleli
Daniyan, Ilesanmi
Adeodu, Adefemi
Mpofu, Khumbulani
Maladzhi, Rendani
Kanakana-Katumba, Grace Mukondeleli
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Abstract
The need for improved productivity without sacrificing quality, which is in line the prime target of many manufacturing industries. The aim of this study is to investigate the causes of production variation: a case study of the rail manufacturing industry, South Africa. In this study, the six-sigma Define, Measure, Analyse, Improve and Control (DMAIC) phases were applied to enhance the process capability (long term) in the production of bolster compression springs in the main line of bogie secondary suspension system. In every phase of DMAIC method,
a combination of both qualitative and quantitative techniques was utilized. First, process capability index Cpk of the current process was computed which was found less than 1. The results obtained indicated that the process capability index values were found to be 1 after the improvement phase. Hence, significant improvement was achieved in the area of reduction in process variation and product quality after taking corrective actions. From outcomes of the study, it can be concluded that process performance of a train manufacturing plant can be improved significantly by implementing six-sigma DMAIC methodology. The novelty of this study lies in the fact that the implementation of the six-sigma DMAIC phases to enhance the
process capability (long term) and minimise variations in the production of bolster compression springs has not be sufficiently highlighted by the existing literature.
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Date
2022-11-29
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Taylor and Francis Group
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Keywords
DMAIC, Process capability index, Process variation, Six-sigma