Six Sigma methodologies in statistical control application to improve production performance and quality in the pharmaceutical industry

This paper presents a case of applied statistical methods for the optimization of quality control process in the pharmaceutical industry. The project, developed for Zambon pharmaceutical group1 This paper refers to Total Quality Management, analyzing the production process to identify critical areas and acting proactively to optimize both qualitative and productive capacity. , is linked to performance improvement in a high spectrum antibiotic production line. Given sensitive nature of pharmaceutical products to the principles of sterility and safety, the quality control of production process is one of the main aim of the firm. Quality and production dimensions are so strongly related that a low quality level (below the regulation fixed bounds) can reduce the acceptability rate of production lot, affecting corporate performance and reputation. Firstly, hypothesis of process normality behavior are tested to verify subsistence of adequate conditions for Six Sigma methodology application, as well as errors forecasting in the distribution parameters estimation. Secondly we use the three and six sigma variability compared to Zambon previous static bounds to assess process reliability. Then, we applied the transition from total control (100% of vial weights) to statistical one (10% sampling). We have fewer weighted vials but a higher production, a more accurate control (vials are longer time on balance) and so a better population estimate. Finally we implement online control tool regarding the cumulative Cpk (process capacity), the average shift from expected weight and standard deviation trends. It allows to set production machine in real time, to control and revise process deviation and to maintain high quality standards. In conclusion, we show a careful use of quality control statistical methods consents to achieve huge results in terms of increased productivity, reduced waste, reduced downtime and greater ability to control real time process distribution