Improved by prediction of the PFMEA using the artificial neural networks in the electrical industry

This paper presents how an improvement can be realized by using prediction in Process Failure Mode and Effects Analyze (PFMEA) with the neural networks approach to determine the fault occurrence. Neural networks have the ability to time-series data prediction, in our case series containing all values of the failures of the items. The improvement in prediction of PFMEA has followed continuously data from the workshop and it offers also the next value of occurrence (which is predicted) and it ensures a bigger period of time for implementing the action plans.