Optimizing humidity level and illuminance to enhance worker performance in an automotive industry

Abstract

The objective of this study is to determine the optimum values of environmental factors such as relative humidity (%) and illuminance (lux), on the operators’ productivity at Malaysian automotive industry. 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. Humidity and illuminance level can give significant effect on the worker performance. Humidity level, illuminance level and productivity rate were observed in automotive factory. An automotive manufacturing firm was chosen to observe the relative humidity level, illuminance level and worker’s productivity rate. The data were analyzed using Artificial Neural Network's (ANN) analysis. Artificial Neural Network's (ANN) analysis technique is usual analysis method used to form the best linear relationship from the collected data. It is apparent from the linear relationship, that is the optimum value of production (value?1) is attained when relative humidity is 54.86% RH and lighting value is 146.386 lux. Optimum value production rate (value?1) for one manual production line in that particular company is successfully achieved. Through ANN's system, optimum environmental factor manage to be predicted.