The human element plays a crucial role in industries, particularly manufacturing and process. Effective management of human factors improves product quality and efficiency while reducing the risk of operational errors that may result in incidents or accidents. Even with the advancements in technology and automation, repetitive manual work and challenging tasks still strain workers, resulting in physical fatigue and increasing the chances of errors, production delays, and potential accidents. For this reason, the significance of physical fatigue on industry operations and employee well-being cannot be overstated. The implementation of wearable technology to handle physical fatigue in the industry is a cutting-edge solution. Wearable devices provide real-time data on worker physical fatigue levels, allowing employers to respond quickly to any changes in conditions that may increase the risk of accidents in the wokplace. This paper aims to present a framework for a fitness setting that simulates the repetitive movements commonly seen in the industrial sector. The data collected in this controlled environment will be used to train a physical fatigue classification model, which can then be applied in real-world industrial facilities to advance operator safety and reduce the risk of workplace accidents in future applications.