Application of robust experiment to develop quality improvement in weaving production

Abstract

Purpose – The purpose of this research is to formulate a robust experiment in weaving production in Indonesia that effectively managed disruptive factors and reduced errors. Design/methodology/approach – The data recorded from September to November 2023 showed a 23% increase in process defects, facing a lack of use of statistical tools and techniques for collecting and analyzing data. Furthermore, this research used an experiment design that includes an analysis of variance and the evaluation of disruptive factors (signal to noise [S/N] ratio) as integral components of the design process. Using robust design principles and Minitab software, the industry identified seven control factors as the highest contribution to the result. Using a “Smaller is Better” approach to achieve optimal design. Sample data from the confirmation experiment were shown and provided a real representation of the result when the predicted optimal conditions were implemented. Findings – Using these data, the confidence interval range of the predicted mean (μprediction) overlapped with the confidence interval range of the confirmation experiment (μconf irmation). This overlap meant that the results were consistent and reproducible, supporting the reliability and additive nature of the experimental findings. Originality/value – This research was used to guide the industries in developing a systematic procedure, process specifications and process tolerance.