Optimization temperature level toward workers’ productivity

Abstract

Production of automotive parts is among the largest contributor to economic earnings in Malaysia. The dominant work involve in producing automotive part were manual assembly process. Where it is definitely used a manpower capability. Thus the quality of the product heavily depends on worker’s comfort in the working condition. Temperature is one of the environmental factors that contribute significant effect on the worker performance. This paper intended to present an optimization of temperature level towards the worker productivity rate at one of the Malaysian industry. An assembly automotive manufacturing industry was chosen to conduct the study by observing and measuring the temperature level and worker’s productivity rate. The data then were analyzed by using Artificial Neural Network's analysis (ANN). ANN analysis technique is commonly used to analysis and obtained the best linear relationship from the collected data. It is apparent that from the linear relationship obtained, the optimum value of production (value 1) is attained when temperature value (WBGT) is 24.5 °C. This finding was also inline when compared to the temperature range of comfort level produced from OSHA standard. The optimum value production rate (value 1) for one manual production line in that particular company is successfully achieved. Through ANN analysis, the optimum environmental factor managed to be predicted.