Six Sigma implementation in a manufacturing unit - a case study

Hemadri Chadalavada, D. Samuel Raj and M. Balasubramanian

International Journal of Productivity and Quality Management, 2016, vol. 19, issue 4, 409-422

Abstract: The Six Sigma approach has been increasingly adopted in the manufacturing sector in order to make the process robust to quality variations, thereby, improving the quality and performance. In any manufacturing industry, Shainin Six Sigma methodology is highly adopted because of lesser data collection required for the study. Six Sigma improves the process performance of the critical operational process, leading to better utilisation of resources, decrease in variations and maintaining consistent quality of the process output. The DMAIC approach has been followed here to solve an underlying problem of reducing process variation and the associated high defect rate. This paper describes an application of Six Sigma define, measure, analyse, improve and control (DMAIC) methodology in a manufacturing unit, which provides a framework to identify, quantify and eliminate sources of variation in an operational process to improve the quality. The current investigation focuses on using DMAIC methodology to reduce the rejections in the pasting process during product X manufacturing, resulting in a saving of Rs. 3.96 lakhs per annum

Keywords: six sigma; DMAIC; Shainin DOE; design of experiments; process improvement; manufacturing industry; case study. (search for similar items in EconPapers)
Date: 2016
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=80150 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijpqma:v:19:y:2016:i:4:p:409-422

Access Statistics for this article

More articles in International Journal of Productivity and Quality Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().