Optimizing humidity level and illuminance to enhance worker performance in an automotive industry
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 Malays...
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Asian Network for Scientific Information
2010
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Online Access: | http://eprints.utm.my/id/eprint/26591/1/ARIsmail2010_OptimizingHumidityLevelandIlluminance.pdf http://eprints.utm.my/id/eprint/26591/ http://scialert.net/abstract/?doi=jas.2010.1389.1396 |
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my.utm.265912018-10-31T12:30:46Z http://eprints.utm.my/id/eprint/26591/ Optimizing humidity level and illuminance to enhance worker performance in an automotive industry Ismail, A. R. Yusof, M. Y. M. Sopian, K. Mat Rebi, Abd. Rani Makhbul, Z. K. M. Makhtar, N. K. TJ Mechanical engineering and machinery 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. Asian Network for Scientific Information 2010 Article PeerReviewed application/pdf en http://eprints.utm.my/id/eprint/26591/1/ARIsmail2010_OptimizingHumidityLevelandIlluminance.pdf Ismail, A. R. and Yusof, M. Y. M. and Sopian, K. and Mat Rebi, Abd. Rani and Makhbul, Z. K. M. and Makhtar, N. K. (2010) Optimizing humidity level and illuminance to enhance worker performance in an automotive industry. Journal of Applied Sciences, 10 (14). 1389 -1396. ISSN 1812-5654 http://scialert.net/abstract/?doi=jas.2010.1389.1396 DOI:10.3923/jas.2010.1389.1396 |
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TJ Mechanical engineering and machinery Ismail, A. R. Yusof, M. Y. M. Sopian, K. Mat Rebi, Abd. Rani Makhbul, Z. K. M. Makhtar, N. K. Optimizing humidity level and illuminance to enhance worker performance in an automotive industry |
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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. |
format |
Article |
author |
Ismail, A. R. Yusof, M. Y. M. Sopian, K. Mat Rebi, Abd. Rani Makhbul, Z. K. M. Makhtar, N. K. |
author_facet |
Ismail, A. R. Yusof, M. Y. M. Sopian, K. Mat Rebi, Abd. Rani Makhbul, Z. K. M. Makhtar, N. K. |
author_sort |
Ismail, A. R. |
title |
Optimizing humidity level and illuminance to enhance worker performance in an automotive industry |
title_short |
Optimizing humidity level and illuminance to enhance worker performance in an automotive industry |
title_full |
Optimizing humidity level and illuminance to enhance worker performance in an automotive industry |
title_fullStr |
Optimizing humidity level and illuminance to enhance worker performance in an automotive industry |
title_full_unstemmed |
Optimizing humidity level and illuminance to enhance worker performance in an automotive industry |
title_sort |
optimizing humidity level and illuminance to enhance worker performance in an automotive industry |
publisher |
Asian Network for Scientific Information |
publishDate |
2010 |
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http://eprints.utm.my/id/eprint/26591/1/ARIsmail2010_OptimizingHumidityLevelandIlluminance.pdf http://eprints.utm.my/id/eprint/26591/ http://scialert.net/abstract/?doi=jas.2010.1389.1396 |
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