Forecasting operation times by using Artificial Intelligence

Year 2018, Volume: 2 Issue: 2, 109 - 116, 15.08.2018

Burcu Özcan , Pınar Yıldız Kumru , Alpaslan Fığlalı

Abstract

Due to
increased competition, companies must reduce delivery and costs on time and
provide the desired product characteristics. This study was carried out in a firm
that manufactures napkin machines according to the order. The most important
problem is that the suppliers cannot deliver to customers on time. For
effective production planning, it is necessary to use the correct operation times
for each machine used. The times were estimated by using the Artificial Neural
Network (ANN) approach and the Taguchi Design of Experiment was used to
estimate the optimal combination of ANN parameters. According to the results of
the research, it is found that the number of layers and neurons have
significant influence. By using the ANN method, the time spent in parameter
design is effectively reduced and the efficiency of the algorithm is increased.
Estimation performance is compared with the statistical analysis. This model
proved to be statistically reliable in estimating operation times. Thus, the
operators will be able to estimate the processing times for new designs.

Keywords

Artificial Neural Networks, Design of Experiment, Forecasting, Metaheuristics

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