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.
Artificial neural networks production and manufacturing processes process improvement
Birincil Dil | Türkçe |
---|---|
Konular | İşletme |
Bölüm | Araştırma Makalesi |
Yazarlar | |
Yayımlanma Tarihi | 1 Nisan 2018 |
Yayımlandığı Sayı | Yıl 2018 Cilt: 18 Sayı: 2 |