Statistical Process Control (SPC) is indispensable in the medicinal chemical industry for maintaining pharmaceutical product quality and consistency. Background: With complex chemical processes and stringent regulatory standards, robust quality control measures are essential. SPC enables monitoring and control of key process parameters, identification and correction of process variations, and ensuring final product compliance with specifications. This study evaluates the quality and capability of a process measuring medicinal raw material quality from an international chemical manufacturing company.
Methods: Data collected from the conductivity measurement process were analyzed using Minitab software. The process specification was fixed at 30 µS·cm-1 as a maximum permissible limit, with 33 subgroups of size one. The computation of the capability six-pack and analysis generated six plots providing insights into process stability, recent behavior, and capability against specifications, distribution verification and capability indices. Minitab® version 17.1.0 software was used to perform a process capability six-pack analysis, including various charts and statistics to assess process stability and capability.
Results: The results indicate that while the process is stable, it lacks capability, with variations exceeding acceptable limit. The process does not meet the maximum allowable specification value, with deviations from normal distribution and following logistic dispersion pattern.
Conclusion: The study's novelty lies in its comprehensive yet concise presentation of key metrics essential for evaluating process capability and performance, providing insights for process improvement and quality control. Further investigation and improvement actions are needed to address sources of variation and enhance process capability and performance.
Key words: Statistical Process Control, Pharmaceutical Quality Control, Process Capability Analysis, Medicinal Chemical Industry, Minitab Software, Conductivity Measurement, Capability Indices, Quality Improvement
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