DEVELOPMENT OF THE RELIABILITY ASSESSMENT IN PREVENTIVE MAINTENANCE OF HEAT, VENTILATION, AND AIR CONDITIONING (HVAC) SYSTEMS FOR THE PRODUCTION OF PHARMACEUTICAL PRODUCT.

The support system of heat, ventilation, and air conditioning (HVAC) in manufacturing plants plays an important role in the optimum efficiency of the production system. Failure to support adequate HVAC on the production floor will cause production defects, stoppage time, unplanned machine downtime, and other related issues. These issues highly affect those products that require dedicated temperature, pressure, and humidity, such as production clean rooms, food industries, and pharmaceutical products. Thus, this study aims to develop and apply the specific reliability assessment in an investigation of HVAC, focusing on the production of pharmaceutical products. In this study, the selected statistical quality tools have been applied in the evaluation and prediction of the HVAC failure and maintenance process. To ensure suitable tools and methods will be applied, a systematic approach has been developed consisting of six steps towards effective maintenance of the HVAC system. The main purpose of the application quality tools such as check sheet, Pareto chart, scatter plot, and probability plot was to evaluate the historical failure data and then to predict the potential future failure through analysis of Mean Time Between Failure (MTBF) in steps 1 to 4. To ensure the developed approach successfully implemented the Failure Mode and Effects Analysis (FMEA) in step 5, the corrective action plan was suggested in step 6. Once the systematic approach of HVAC preventive maintenance had been successfully developed, it was then implemented in the selected production floor of the pharmaceutical industry. The execution of this developed systematic approach to predicting the HVAC resulted in an increase in the total MTBF from 529.50 minutes to 778.23 minutes. It showed an improvement of 47% after the implementation of the developed systematic approach. The obtained results showed that reliability assessment was important for the optimization of production efficiency. [ABSTRACT FROM AUTHOR]