Improving ergonomics in mixed-model assembly lines balancing noise exposure and energy expenditure

In the manufacturing industry, assembly processes involve most of the workforce to deal with the many manual operations. Thus, the design of workplaces must take into account ergonomics to promote workers well-being and safeguard their health and safety, also enhancing productivity. The occupational ergonomic risk not only depends on the physical workload of a task, but also on environmental characteristics of the workplace, including noise, the assessment of which may contribute to prevent workers from possible health issues associated to hearing injuries. In this regard, the present study proposes a software tool based on a genetic algorithm for solving the mixed-model assembly line balancing problem with job rotation and collaborative robots to improve workers’ ergonomics, for the evaluation of which noise exposure is also considered. In particular, the objectives of the problem concern economic aspects, which are taken into account through the optimization of the cost of the line, and ergonomics, which is pursued by reducing and smoothing both workers’ energy expenditure and noise exposure for performing operations on the line. To test the effectiveness of the proposed approach, an industrial case study is finally discussed.