The appropriateness of the Design of Experiments to support Lean Six Sigma for variability reduction

• Main Author: Robert W.D. Zondo
• Format: Article
• Language: English
• Published: AOSIS 2018-09-01
• Series: The Journal for Transdisciplinary Research in Southern Africa
• Subjects: automotive component manufacturers; design of experiment; functional areas of business; Lean Six Sigma; variation reduction
• Online Access: https://td-sa.net/index.php/td/article/view/469

A Design of Experiment (DoE) is a strategy for planning, conducting, analysing and interpreting the experiment so that valid conclusions can be drawn efficiently and economically. It has the ability to reduce product and process variability. Hence, this study examined if DoE is an appropriate tool to support Lean Six Sigma in selected automotive component manufacturing companies in South Africa. The automotive component manufacturing sector uses various tools aimed at reducing variability. This includes Lean Six Sigma. Consequently, companies that participated in the study have (over and above Lean Six Sigma) adopted a DoE strategy. Thus, the study was designed to establish if DoE is an appropriate tool to support Lean Six Sigma. Of the 123 participants identified, 107 completed the questionnaires. Middle managers of four automotive component manufacturing companies in the eThekwini District Municipality participated in the study. The study investigated production and the related experiences of the automotive component manufacturing companies. Descriptive and correlation were used to analyse data. Results indicated that the appropriateness of DoE to support Lean Six Sigma in various business activities (like finance, strategy and product development) has no relation to both product improvements through reformulation during product development and process optimisation using quality control tools. However, study participants provided a number of reasons for implementing DoE in the automotive component manufacturers. It is advised that the automotive component manufacturers develop a comprehensive variability reduction policy that aligns DoE tools to business performance.