Application of Low Volume Statistical Process Control
compared against the methodology proposed by BS ISO
7870-8:2017

Abstract

The introduction of Statistical Process Control (SPC) by Shewhart [1] in the early 1920s demonstrated significant potential for improving quality parameters in high-volume production. However, since the original SPC concepts were primarily designed for mass production, numerous methods have been developed and adapted for low-volume scenarios starting from the 1970s. Statistical Process Control (SPC) methods have been developed and adapted to low-volume scenarios. These include short-run production with multiple products and parts and a just-in-time methodology to ensure quality control. However, current methods often generate numerous charts, leading to interpretation issues and significant time waste[2]. The BS ISO 7870-8 standard, issued in 2017, provides a framework for addressing deviations from the target in the application of statistical methods rather than focusing on individual values. However, it is essential to note that this standard is designed primarily for one-off quantities. It advises seeking specialized advice for other production volumes, which does not offer a comprehensive solution. This limitation highlights the need for a more inclusive approach. To address this gap, a case study will be conducted on Rotary Power, a UK based company that manufactures engines and hydraulic pumps. The objective is to analyze how the company could manage the absence of a standard guideline for applying statistical methods to all short-run scenarios. Currently, no such comprehensive guideline exists, posing a significant challenge. The approach will prioritize deviation from the target as the primary value, rather than the measured value, to more accurately display process performance. This will enable data collection from various production stages while precisely monitoring process performance. In this study, the term “data transformation” will refer to values derived from deviations from the target, which are applied in the Statistical Process Control (SPC) methods presented in this work. Utilizing production data from Rotary Power, this research will evaluate the effectiveness of various control charts compared to the methodology proposed by the British Standard BS ISO 7870-8:2017. Specifically, the study will compare the effectiveness of the BS ISO 7870-8:2017 methods against the Q Chart, CUSUM, EWMA, and Moving Average methods. In conclusion, the methods successfully highlight potential risks and offer an efficient approach to identifying and managing these risks, promising an improvement in process quality for low-volume situations. Nevertheless, additional research is necessary to cover a wider variety of low-volume cases, since the BS ISO 7870-8:2017 standard is limited to scenarios where the size of each sample equals one and does not adequately address many real industry scenarios.