Ensuring the stability of manufacturing processes based on statistical process control (SPC) and measurement systems analysis (MSA)
Keywords:
SPC, MSA, statistical process control, measurement system, repeatability, reproducibility, GRR, X̄-R control chart, Cp, Cpk, Pp, Ppk process stability, automotive industryAbstract
The article examines the scientific and practical aspects of applying Statistical Process Control (SPC) and Measurement Systems Analysis (MSA) methods to ensure the stability of manufacturing processes. A controlled dimensional parameter of the "COVER ASM - STRG COL LWR" component, used in the automotive industry, was selected as a case study. Process stability was evaluated using X̄-R control charts, while process capability (Cp and Cpk) and process performance (Pp and Ppk) indices were also assessed. The reliability of the measurement system was determined based on repeatability (EV), reproducibility (AV), their combined metric (GRR), and the number of distinct categories (ndc). Based on 125 measurement results, the process mean was 3.9988 mm, with Cp=1.319 and Cpk=1.835; no instances of the process exceeding statistical control limits were detected on the control charts. The MSA study yielded the following results: %EV=20.22%, %AV=3.20%, %GRR=20.47%, and ndc=6.74. These results indicate that the measurement system possesses sufficient discrimination capability for process analysis, although there is room for improvement regarding the repeatability component. The proposed SPC-MSA sequence makes it possible to distinguish actual process variation from measurement error when evaluating quality indicators and to enhance the reliability of management decisions
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