Optimisation of a Robotic Workcell Layout Using Genetic Algorithms

With the advent of robots in modern-day manufacturing workcells, optimization of robotic workcell layout (RWL) is crucial in ensuring the minimization of the production cycle time. Although RWL share many aspects with the well-known facility layout problem (FLP), there are features which set the RWL apart. However, the common features which they share enable approaches in FLP to be ported over to RWL. One heuristic gaining popularity is genetic algorithm (GA). In this paper, we present a GA approach to optimizing RWL by using the distance covered by the robot arm as a means of gauging the degree of optimization. The approach is constructive: the different stations within the workcell are placed one by one in the development of the layout. The placement method adopted is based on the spiral placement method first broached by Islier (1998). The algorithm was implemented in Visual C++ and a case study assessed its performance.