IJSRP, Volume 3, Issue 2, February 2013 Edition [ISSN 2250-3153]
Suman Kant, Rahul O Vaishya
In this Paper, the FMS loading problem is solved with the bi-criterion objective to minimize the system unbalance and maximizing the throughput by the use of artificial neural networkin the presence of available machine time and tool slots as constraints. The complexity of machine loading Problem in FMS is very high due to the different flexibility criteria such as part selection, operation allocation and various constraints involved such as availability of tool slot and time available on machines. This encourages various researchers to apply various heuristic techniquesto get optimal/ near optimal solution. Artificial Neural Network (ANN), inspired by the structure and functional aspects of biological neural networks which is an adaptive system changes its structure based on internal and external information flow during learning Phase. In this current decade ANN has emerged as one of the important problem solving tool for complex engineering problems. Keeping this views present research adopted ANN to solve FMS loading problem. It gave optimal/near optimal results in less computational time. It has also been found simple and naive tool for solving loading problems of FMSs.