Abstract
Currently, Physical Fatigue Management is considered a vital part of process industries because of the diverse work scenarios, the high degree of non-standardized operations, and the high reliance on manual labor. The way an individual's performance deteriorates with the accumulation of fatigue can vary based on both the worker and the workplace conditions. However, the widely used method for assessing physical fatigue, the ‘Borg Rating of Perceived Exertion Scale’, has several limitations. These include high subjectivity, introducing more variability among individuals in a population, and weakness in dynamic measurements, potentially missing the optimal recovery time for operators. In this study, a Principal Component Analysis (PCA)-based Fuzzy Logic Classifier has been designed to aid the development of customized warning systems for physical fatigue, and also support the intelligent decision-making process in process industries.
