Application of Six Sigma methodology in a small-scale foundry industry

E.V. Gijo · Shreeranga Bhat · N.A. Jnanesh

64 citations0/0 files storedInternational Journal of Lean Six Sigma

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Quality and Supply Management Management and Optimization Techniques Management Systems and Quality Improvement

Abstract

Purpose – The purpose of this article is to illustrate how the Six Sigma methodology was applied to a small-scale foundry industry to reduce the rejections and rework in one of its processes. Design/methodology/approach – The research reported in this paper is based on a case study carried out in an industry using the Six Sigma Define-Measure-Analyze-Improve-Control (DMAIC) approach and its application in improving the leaf spring manufacturing process of a foundry shop. Findings – The root causes for the problem of rejection and rework were identified through data-based analysis at different stages in the project. The process parameters were optimized and measures for sustainability of the results were incorporated in the process. As a result of this study, the overall rejection was reduced from 48.33 to 0.79 per cent, which was a remarkable achievement for this small-scale industry. This was leading to improvement in on-time delivery to the customer. The finance department of the company estimated the annualized savings due to the reduction in rejection and was to the tune of USD8,000 per year. Research limitations/implications – The paper is based on a single case study executed in a company, and hence, there is limitation in generalizing the specific results from the study. However, the approach adopted and the learning from this study can be generalized. Originality/value – This article illustrates the step-by-step application of Six Sigma DMAIC methodology in a small-scale foundry industry to solve an age-old problem in the organization. Thus, this article will be helpful for those professionals who are interested in implementing Six Sigma to such industries.

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References

1992Introduction to Statistical Quality Control 1991Quality Engineering Using Robust Design 1989Taguchi Techniques for Quality Engineering 2001Experiments - Planning, Analysis and Parameter Design Optimization 2000Implementing Six Sigma: Smarter Solutions Using Statistical Methods 2004Benefits, obstacles, and future of six sigma approach 2010Lean Six Sigma – getting better all the time 2002Critical success factors for the successful implementation of six sigma projects in organisations

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2019Quality management for sustainable manufacturing: Moving from number to impact of defects 2018Critical review and analysis of measuring the success of Six Sigma implementation in manufacturing sector 2015Six Sigma through Poka-Yoke: a navigation through literature arena 2020MDAIC – a Six Sigma implementation strategy in big data environments 2016The underlying factorial structure and significance of the Six Sigma difficulties and critical success factors

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