Abstract
While low air quality may have negative effect on product quality in manufacturing, it has become a social concern as there are many reports on the result of worker exposure to low air quality. Manufacturing experienced a boom increase after World War I and II due to higher demands for products that gave birth to an unhealthy environment for workers. For example, Epidemiological investigations have linked unhealthy environment (air pollution) to adverse health effects such as respiratory diseases, and increased mortality and morbidity. These manufacturing systems represented less than 14% of the private employment and accounted for 42% of the nonfatal workplace illnesses. It is evident that manufacturing systems still have significant impact on the health of workers. Therefore, this study proposes a fuzzy Bayesian air quality monitoring model that is able to mimic human-like intelligent behavior in the environmental analysis. An illustrative example is demonstrated to present the application of the model.
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Authors would like to express their sincere appreciation to anonymous referees for their valuable comments that enhanced the quality of the article.
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Jenab, K., Seyedhosseini, S.M., Khoury, S. et al. An intelligent air quality monitoring model in manufacturing. Clean Techn Environ Policy 14, 917–923 (2012). https://doi.org/10.1007/s10098-012-0467-4
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DOI: https://doi.org/10.1007/s10098-012-0467-4