Improving the Quality of Manufacturing Process through Six Sigma Application in the Automotive Industry

Abstract:

Six Sigma is one of methodologies of the quality management for the process improvement. It can be used in manufacturing companies, in order to achieve certain criteria established by management or customer requests. Six Sigma is based on the assumption that opportunities for success are hidden in every process and it gives the company a common tool for defining of corporate objectives. Implementation of this methodology lies in the integrated approach in solving the problems of business processes, which can represent significant benefits in production processes as well as various non-production processes. Six Sigma is based on the principle of measuring, monitoring and controlling processes with possible application of statistical methods, different tools and techniques. If the Six Sigma methodology is used properly and rationally, companies can save considerably with this effort the measurable financial resources. Its application leads to a cost reduction in inefficient processes, contributes to the production quality, better performance and to the satisfaction of internal and/or external customers.The objective of the paper is to present base theoretical aspects of Six Sigma framework and its principles. Followed with methodology of Six sigma and in addition is addressed a concrete application for statistical process control of the lacquering process within silencers manufacturing for a company in the automotive industry. The practical contribution of the project provides an improvement of the process, which means to improve the product quality, achieve cost reduction and better customer satisfaction.

• Periodical: Applied Mechanics and Materials (Volume 693)
• Pages: 147-152
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.693.147
• Online since: December 2014
• Authors: Marta Kučerová, Helena Fidlerová
• Keywords: CTQ, DMAIC, Process Improvement, Quality Management, Six Sigma, Statistical Process Control

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