Can geometric distance provide a better way to assess manufactured product quality? This research introduces a new process control variable, geometric distance (GD), for assessing the quality of manufactured products. Aiming to reduce dimensionality and improve process capability analysis, the method offers a practical alternative for industries seeking continuous improvement and diagnostics of part failure. The study investigates the theoretical distribution of geometric distance and proposes a suitable performance metric for multivariate process data. By using GD, the research seeks to address the lack of consensus in multivariate quality control methodologies. The paper demonstrates the potential of the proposed method to serve as a critical first step in instituting an effective multivariate control scheme. Ultimately, the effectiveness of the proposed method is demonstrated using real-world data. The research provides a valuable tool for evaluating the quality of manufactured products, with implications for enhancing competitive benchmarking and diagnostics of part failure in modern manufacturing industries. This approach contributes to a more efficient and reliable process control system.
This paper is published in the International Journal of Reliability, Quality and Safety Engineering. The journal focuses on the reliability, quality and safety of engineering. The aim of the paper is to quantitatively assess the quality and uses this assessment for competitive benchmarking and diagnostics of manufactured part failure, which are very important for continuous improvement in modern manufacturing industries and are related to the topic of this journal.