Improvement of Manufacturing Processes by Artificial Neural Networks Analysis

Year 2018, Volume: 18 Issue: 2, 261 - 271, 01.04.2018

Salih Aka Gökhan Akyüz

https://doi.org/10.21121/eab.2018237354

Abstract

Manufacturing processes consist of activities

affected by a large number of variables. The

aim of this study is to show that improvements

can be made by using artificial neural network

methods at stages of manufacturing such as

planning of processes, forecasting of the future

situation, monitoring and control. In the study, a

manufacturing process with 15 input variables was

modeled using artificial neural networks, network

training was provided, and a trained network was

used to obtain the best output performance in

the current situation. Artificial neural networks

are useful tools in finding out the consequences

of any change that may occur in variables and in

improving the processes with this way. The results

show that artificial neural network models can be

well adapted to manufacturing processes.

Keywords

Artificial neural networks, production and manufacturing processes, process improvement

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