OPTIMIZATION OF PRODUCTION PROCESS UP-SCALLING OF PARACETAMOL INFUSION TO REDUCE REJECT PERCENTAGE AND COST OF POOR QUALITY - Selvi
The level of particle contamination in the product is one of product failure determinant which results in an increase of production cost. The purpose of this study is to optimize production process of paracetamol infusion to reduce the percentage of product rejection due to particle contamination in order to reduce cost of poor quality. The history of product rejection was on the range of 7,92%±5,14. The results of critical parameters identification with Ishikawa method and risk assessment with Failure Modes Effects Analysis (FMEA) show that the factor which contribute to product failure included the machine speed, ultrasonic frequency, water for injection pressure on the vial washing machine, sterilizing tunnel conveyor speed and nitrogen gas pressure on the filling machine affect the percentage of particle contamination of product. Furthermore, the factor were optimized using fractional factorial design ¼ fraction. The optimal process was obtained at speed of vial washing machine of 7 Hz, ultrasonic frequency on vial washing machine was 200 Hz, pressure of water for injection on washing machine was 20 Psi, speed of sterilizing tunnel conveyor was 30 Hz reduced the percentage of particle contamination rejects to 2.53%. The difference in nitrogen gas pressure on the filling machine does not affect the decomposition of paracetamol into paraaminophenol. Production process confirmation using optimal process parameters produce an average percentage reject of 3.20%± 0,58 with Ppk = 1.44 which means production process are capable. Based on data analysis with Kruskal –Wallis method, followed by Mann –Whitney known that the implementation of process optimization can significantly reduce the percentage of particle contamination rejects and production costs (p<0,05). The results of this optimization process can be applied in production process of paracetamol infusion with batch size of 500 liters in PTM.