engleski

Two approaches for estimation of production time : robust regression analysis and neural network

A robust regression analysis model as a possible approach to time/cost estimation is used for the estimation of requested results based on the previous stochastic results and experiments. The requests for classification consideration of the product shape and process sequencing are important conditions for designing a general model for the estimation of production times. In fact, it means development of a technological knowledge base. As a result of our analysis, we created eight regression equations with the obtained index of determination, with the most important independent variables different for 2D and 3D model respectively. The observed level of subjectivity, constraints and errors were the reasons to use neural networks as the second approach to estimate production times. According to the presented results, we can conclude that the assumption on the use of a neural network for the production time estimation in relation to a robust regression analysis model is justified. For all experimental models the applied backpropagation neural network gives better values of key performance indexes (R, R2, RMSE, NRMSE).

production time; robust regression analysis; neural network

nije evidentirano