4.7 Article

Productivity model in hot and humid environment based on heat tolerance time analysis

Journal

BUILDING AND ENVIRONMENT
Volume 44, Issue 11, Pages 2202-2207

Publisher

PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.buildenv.2009.01.003

Keywords

Hot and humid environment; Thermal environment; Heat tolerance time; Productivity

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Thermal environment is one of the most important factors that have impact on workers' productivity. There are many hot and humid workshops in China, whose thermal environment characteristics are the high temperature, high humidity and little radiation intensity. Working in hot and humid environment for a long time not only can extremely do harm to human body health, but also probably induce accidents due to the fall of productivity. In this paper, human body experiment and statistics analysis with the software of EXCEL were applied to establish a heat tolerance time model and a productivity model in hot and humid environment. Firstly, a chamber stimulating hot and humid environment was built and the experiment on heat tolerance and productivity in this chamber was completed. Heat tolerance time and productivity in different environments were tested with the change of air temperature and humidity in the environment chamber. According to the experiment results, regressive formulas for heat tolerance time changing with thermal environment parameter (WBGT) in three conditions of physical labour intensity were provided by statistics methods respectively. On this basis, the function of productivity changing with heat tolerance time and thermal environment parameter (WBGT) in three conditions of physical labour intensity using multiple linear regression analysis tool of EXCEL were obtained finally. F-test was also applied to verify the significance of all the established regression equations. The result shows that the effect of curve regression is significant and the regression function gives important statistic meaning and practical value to work time determination and productivity prediction in hot and humid environment. (C) 2009 Elsevier Ltd. All rights reserved.

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