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International Business Management

ISSN: Online
ISSN: Print 1993-5250
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Application of Six-Sigma for Process Improvement in Manufacturing Industries: A Case Study

Manmeet Mahinderjit-Singh, Maran Marimuthu and Rohail Hassan
Page: 676-691 | Received 21 Sep 2022, Published online: 21 Sep 2022

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Abstract

This is an era of quality management and quality is a parameter for the selection of a product or service because the customer wants a defects free product or service. Six-Sigma is a quality improvement approach that aims to reduce the number of defects up to 3.4 parts per million. In the last three decades, it helped several companies to enhance the capability of their processes and to increase the level of quality of their product or service. This case study based research deals with application of DMAIC (Define, Measure, Analyze, Improve and Control) methodology of Six-Sigma to reduce the machine downtime for process improvement. The tools and techniques used during the analysis are Process Mapping (SIPOC Diagram), Process Flow Chart, Process Capability Analysis, Histogram, Pareto Chart, Pie Chart, Cause and Effect Diagram, Brainstorming, Affinity Diagram and ANOVA. The results of this study show that sigma value has improved from 2.79-2.85 Sigma. This study also highlighted the five critical problems (reasons) of downtime which are, i.e., electricity problem, shortage of material, quality issues, machine fault and reactive maintenance. The valuable principles and practices of Six-Sigma will do well by continuously refining the organizational culture. Time and commitment both are required and compulsory to bring change in cultural before they are strongly implanted into the organization. I do assure that this research study will provide opportunities to the organizations for the better implementation of Six-Sigma projects.


How to cite this article:

Manmeet Mahinderjit-Singh, Maran Marimuthu and Rohail Hassan. Application of Six-Sigma for Process Improvement in Manufacturing Industries: A Case Study.
DOI: https://doi.org/10.36478/ibm.2016.676.691
URL: https://www.makhillpublications.co/view-article/1993-5250/ibm.2016.676.691