An approach with genetic algorithms to improve the workstation space planning

Abstract

Abstract Industry 4.0 is characterized by the use of digital solutions and computational technologies. The proposed paper presents a workstation space plan solution using an intelligent computational approach: Genetic Algorithms. On the one hand, we have the operator’s effort represented by the motion trajectories in the normal work area. On the other hand, the production flow requires some constraints on the sequence of the assembled components or their location. Considering both the constraints and the reduction of the operator’s effort, the planning solution proposed in this paper ensures the improvement of the working process by applying the principles of motion economy under the conditions of the constraints required by the production process. The resulting sequence and type of the components and operator effort for the production process is indicated to the operator on the modular workstation. Furthermore, the component placement can be adapted to the characteristics of the production process or of the operator’s needs (left handed, has some disabilities, etc.). The solution proposed in this paper was applied in an experimental laboratory where components from the automotive industry are assembled.