Genetic algorithm modeling for the inspection allocation in reentrant production systems

One of the most important characteristics of reentrant production systems is that the products are manufactured layer-by-layer, so it is difficult to inspect some defects after they are covered by the next layer. This study proposes a genetic algorithm (GA) approach that is very suitable for solving the inspection allocation problem, because the codes used in the chromosome of the GA approach are exactly the same as the representation of the inspection allocation policy for workstations in the production system. Meanwhile, this study shows better performance than the researches done in the literature and is very much closer to the optimization method based on complete enumeration. In addition, a discussion regarding GA parameters is performed to suggest proper parameters used for various production systems. The result obtained in this study is highly practical, extensible and applicable, so it can serve as a production planning tool to solve the inspection allocation problem in reentrant production systems.