A robust job rotation schedule to minimize worker injuries

Worker assignment is an important function in a company's operations. Currently, workers are often assigned to tasks based upon their experience and skills. Working on the same task repetitively for a long period of time may cause workers to incur stress and injuries, which results in a significant amount of lost time and money. Job rotation is a method of rotating workers across various tasks that have different physical and mental demands over time. It's a promising method to manage worker fatigue, reduce worker stress and injuries, reduce errors, and increase worker satisfaction. Job rotation has been applied to many settings; however, a constructive method that can provide optimal or near optimal rotation schedules has not been developed. This research proposes a heuristic procedure to develop worker rotation schedules to minimize injuries.; To demonstrate the concept, low back pain and lifting tasks were used as an example problem. Even though the experiments were done based upon low back pain and lifting tasks, the solution methodology can be applied to other kinds of repetitive tasks and their corresponding injuries. This research simulated realistic settings by allowing uncertainty in task demands and differences in worker profiles. Uncertain task demands were simulated by using a uniform distribution with different ranges during each time period while worker profiles were randomly generated.; Three objective functions were considered in the experiment including minimizing the maximum job severity index (JSI) value, minimizing the maximum number of worker lost days, and minimizing the total number of worker lost days. Mathematical programming models were formulated based upon these objective functions and heuristic methods were developed. To evaluate the proposed heuristic methods, the deterministic version of the problem was introduced. The best solutions from the proposed heuristic method matched closely to the optimal solutions from the mathematical programming method for these problems. Worker rotation schedules for the stochastic task demand problems were found by using the central limit theorem of sums (CLTS) concept. The CLTS method generated robust rotation schedules compared to the best solutions from the full enumeration method using a real time simulation.; In addition to developing a method to generate robust rotation schedules, this research also demonstrates the quantitative results of how rotation plans can improve worker schedules. The comparison of worker schedules with and without rotation plans shows that using rotation plans reduces the JSI values and the number of lost days significantly. An analysis of rotation intervals was also performed and it was found that one or two hours was the proper length between each rotation.