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A workforce scheduling model to reduce occupational heat stress and labor cost |
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| รหัสดีโอไอ | |
| Creator | Kawalee Srinakorn |
| Title | A workforce scheduling model to reduce occupational heat stress and labor cost |
| Contributor | Kawalee Srinakorn, Sun Olapiriyakul |
| Publisher | Asia-Pacific Journal of Science and Technology |
| Publication Year | 2563 |
| Journal Title | Asia-Pacific Journal of Science and Technology |
| Journal Vol. | 25 |
| Journal No. | 1 |
| Page no. | 1-9 |
| Keyword | Occupational safety, Heat, Workforce scheduling, NIOSH, Workload |
| URL Website | https://www.tci-thaijo.org/index.php/APST |
| Website title | https://so01.tci-thaijo.org/index.php/APST/article/view/181083/163688 |
| ISSN | 2539-6293 |
| Abstract | Excessive exposure to high temperatures in the workplace is a cause of heat stress, anxiety, and fatigue in industrial workers. In workplaces in which workers are surrounded by heat sources such as furnaces and boilers, the heat exposure levels may need to be administratively controlled to adequately protect workers from excessive heat exposure. This study integrates National Institute for Occupational Safety and Health (NIOSH) recommended heat stress limits into the design of workforce scheduling models in order to mitigate the heat exposure level of workers. A binary programming model is formulated to determine the optimal workforce schedule, where the objectives are to minimize the labor cost and to minimize the temperature difference between the actual exposure levels and the recommended exposure limit adopted by NIOSH. Additional considerations include the heat tolerance of workers and task workloads. The Epsilon constraints method is used to obtain the Pareto optimal solutions. Based on the results, this study demonstrates that the average heat stress level of workers can be reduced significantly by the use of a workforce scheduling approach. In the case presented, the difference between the actual exposure levels and the recommended exposure limits of the workforce can be reduced by about 0.73 ?C per person |
