Author
Listed:
- Aleksy Kwilinski
(The London Academy of Science and Business, London, UK)
- Maciej Kardas
(WSB University in Dabrowa Gornicza, Dabrowa Gornicza, Poland)
Abstract
Process Capability Indices such as Process Capability Index (Cp) and Corrected Process Capability Index (Cpk), along with Process Performance Index (Pp) and Process Performance Corrected Index (Ppk), are most commonly used tools in quality management within manufacturing processes. They determine whether a process is capable of producing products within established tolerance limits, addressing both short-term and long-term variability. Despite widespread use, the analysis of Process Capability Indices often overlooks special variability within processes, which may lead to misleading interpretations of a process's capability, especially when the determination of tolerance limits is inadequately conducted. This article aims to verify the hypothesis that current analyses of Process Capability Indices fail to consider special variability, which could mislead the interpretation of a process's ability to meet its specifications. Statistical analyses were conducted using the Minitab software, based on dynamic viscosity measurements from the production process of solvent-based paint, to explore the implications of special variability on the interpretation of Process Capability Indices. The study revealed that while Process Capability Indices are useful for identifying quality management opportunities, their effectiveness is limited when special variability is present, often resulting in misinterpretations of a process's true capabilities. The findings highlight the need for methodologies that incorporate considerations of all forms of variability to ensure accurate process capability assessments. This gap in traditional analyses can affect the strategic decision-making in quality management, suggesting a critical area for further research and methodological development. The research confirms the need for a revised approach in analyzing Process Capability Indices, advocating for advanced methods that accurately reflect all forms of variability to improve quality management practices. Future research should focus on developing these methodologies to ensure more reliable and effective use of Process Capability Indices in quality management.
Suggested Citation
Aleksy Kwilinski & Maciej Kardas, 2023.
"Enhancing Process Stability and Quality Management: A Comprehensive Analysis of Process Capability Indices,"
Virtual Economics, The London Academy of Science and Business, vol. 6(4), pages 73-92, December.
Handle:
RePEc:aid:journl:v:6:y:2023:i:4:p:73-92
DOI: 10.34021/ve.2023.06.04(5)
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