Line Balancing Based on Error Rate Estimation with Artificial Neural Networks in Assembly Line Operations

In this study, in the assembly line systems consisting of operations interaction with each other; To reduce number faulty products, to prevent poor quality and production time, Error Ratio Estimation Artificial Neural Networks probabilistic Line Balancing method have been performed. The error rate estimation provides information on which jeans models should be applied improvement work eliminate existing errors place. using Levenberg - Marquardt Learning Algorithm, machine learning was determined by experimental design method. At same it has used as an artificial intelligence algorithm multi-directional decision making stages, balancing parts. Assembly Equilibration, aimed re-stabilize unbalanced influence post-forecasting process recovery. Probabilistic because processing times are stochastic (variable) statistical data mathematical algorithms (digital can created). When results examined, a successful forecasting carried out for two different five-pocket selected seen that components enable precisely assigned stations. And given reliable results.