Enhancing Pharmaceutical Manufacturing through Statistical Process Control: An Industrial Engineering Approach to Quality Assurance
DOI:
https://doi.org/10.38032/jea.2025.04.001Keywords:
Statistical Process Control (SPC), Industrial Engineering, Quality Engineering, Process Capability, Sixpack AnalysisAbstract
In modern manufacturing, particularly within the process-driven healthcare industry, maintaining stringent control over critical quality attributes is paramount for ensuring product integrity and safety. This study demonstrates the application of Statistical Process Control (SPC), a core methodology in industrial and production engineering, to monitor and manage key process parameters: pH and the concentration levels of preservatives Methyl Paraben (MP) and Propyl Paraben (PP). Utilizing a comprehensive sixpack analysis, this research provides an engineering-focused framework for achieving optimal product quality. The study conducted a retrospective analysis of 184 measurements for each parameter from a healthcare product's routine quality control data. Due to the non-normal distribution of raw data, a Johnson SU transformation was applied to ensure the validity of the statistical analysis. The results revealed process instabilities despite some parameters showing acceptable capability indices (Pp and Ppk). The pH process was marginally capable (Pp=1.32, Ppk=1.21) but out-of-control, with a high defect rate. The MP assay showed good potential (Pp=1.70) and capability (Ppk=1.44) but exhibited instability, while the highly capable PP assay (Pp=2.00, Ppk=1.61) also showed signs of a process mean shift. This investigation demonstrated that while all tested products did not show out-of-specifications results, they pinpointed to the hidden signs of processes that need re-examination for significant improvements.
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