On multistage approach for flexible routing in flexible manufacturing systems

Journal Article

2016

Khadra, Jaber E Abu Qudeiri , Usama Umer , Mustufa H Abidi1 , Abdulrahman M Al-Ahmari, Fayiz Abu . 2016

Optimizing flexible routing in flexible manufacturing systems is one of the aspects that increase the efficiency of flexible
manufacturing systems especially in dynamic environment systems. This article presents a multistage approach to solve
flexible routing problem in flexible manufacturing systems. Multistage approach includes three stages; the first stage is a
production simulation system to find the fitness of the flexible manufacturing systems corresponding to different products’
routes’ groups. The second stage proposes an artificial neural network approach to predict the products’ routes’
group in flexible manufacturing systems. The last stage combines genetic algorithms and artificial neural network to optimize
proper routes for all product types in flexible manufacturing systems. Multistage approach proposed in this study
aims to reduce the computational time required to obtain and optimize the flexible routes in flexible manufacturing systems.
The results of this study show that the artificial neural network can be used efficiently to predict the flexible
routes in flexible manufacturing systems and it reduces the computational time for routes’ optimization required with
production simulation system. This characteristic improves the flexibility of flexible manufacturing systems since it can
be adapted frequently against any change in production ratios.