A novel strategy for balancing the workload of industrial lines based on a genetic algorithm

Abstract

One major problem in industrial automation is the workload balancing problem. It consists of making the robots or, more generally, the machines, involved in the assembly process to work exactly the same, either by picking and placing the same number of pieces or by having the same number of operational cycles. This paper presents a novel strategy for solving such a problem by means of an evolutionary algorithm. The specific application of this strategy is to balance the workload of a pick-and-place process developed in the facilities of the industrial company Fameccanica Spa Data within the framework of an industrial project between the company and our research group. The novelties concerning the state-of-the-art contributions are: (1) instead of using an explicit fitness function, the candidate solutions at each iteration are evaluated by using a simulation of the entire process; (2) the parameters optimized are the velocity and acceleration of the robots involved in the line and (3) the strategy includes an algorithm for distributing the workload between the robots during the process.