Effect of temperature, humidity and illuminance towards worker’s performance in automotive industry

Working environmental conditions in automotive industry are very challenging to the human workers. Meanwhile, products quality is very much dependent on workers’ health, safety and comfort in their working environment. Environmental factors, such as temperature, illuminance and humidity levels have...

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Bibliographic Details
Main Authors: Mohd Yusri Mohd Yusof,, Baba Md. Deros,, Ahmad Rasdan Ismail,
Format: Article
Language:English
Published: Universiti Kebangsaan Malaysia 2013
Online Access:http://journalarticle.ukm.my/6696/1/20_Mohd_Yusri_Mohd_Yusof.pdf
http://journalarticle.ukm.my/6696/
http://www.ukm.my/jsm/
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Summary:Working environmental conditions in automotive industry are very challenging to the human workers. Meanwhile, products quality is very much dependent on workers’ health, safety and comfort in their working environment. Environmental factors, such as temperature, illuminance and humidity levels have significant effect on workers’ performance at the production line. In this experiment, temperature, humidity, illuminance levels and productivity rate were observed in a control room. An automotive manufacturing firm production line was chosen to be simulated in the control room to observe the temperature, relative humidity, illuminance and worker’s productivity rate. The experimental data collected was analyzed using Response Surface Method (RSM). RSM is an analysis technique, which combined statistical systems and mathematical methods. It can be applied for research and development, reform and optimize a process, which involves several design variables. As a result, the combined effect of temperature, illuminance and humidity toward productivity can be clearly seen. Optimum environmental factor cannot be predicted using first order RSM analysis because it gives low reliability for obtaining the optimum level. Thus, a second order RSM analysis was generated for obtaining the optimum level of environmental factors.