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Ulaştırma ve Lojistik Kongreleri

alphanumeric journal

The Journal of Operations Research, Statistics, Econometrics and Management Information Systems

A Comparison of Artificial Neural Networks and Multiple Linear Regression Models As Predictors of Discard Rates In Plastic Injection Molding

Vesile Sinem Arıkan Kargı, Ph.D.


Abstract

In today’s global competitive environment, it is important to be able to evaluate the efficient use of a firms’ resources. The aim of this study is to predict the discard rate for headlight frames before the project of an automotive sub-industry firm in Bursa. For this prediction, the multilayer perceptron model, the radial basis function network model and multiple linear regression models were used. Matlab R2010b software was used for the multilayer perceptron model and radial basis function network solutions, and SPSS 13 packet software was used to solve the multiple linear regressions. Comparing the three models, the multilayer perceptron model was identified as the best predictive model.

Keywords: Artificial Neural Networks, Discard Rate, Multilayer Perceptron Model, Multiple Linear Regression Model, Radial Basis Function Network Model

Jel Classification: C13, C45

Plastik Enjeksiyon Kalıplamada Iskarta Oranı Tahmininde Yapay Sinir Ağları ve Çoklu Doğrusal Regresyon Modellerin Karşılaştırılması

Öz

Günümüz küresel rekabet koşullarında firmaların kaynakları etkin kullanarak değerlendirmesi oldukça önemli bir konudur. Bu çalışmanın amacı Bursa’da bir otomotiv yan sanayi firmasının proje öncesinde far çerçeve parçasının ıskarta oranını tahmin etmektir. Bu tahmin için yapay sinir ağ modellerinden çok katmanlı algılayıcı model, radyal tabanlı fonksiyon ağ modeli ve çoklu doğrusal regresyon model teknikleri kullanılmıştır. Çalışmada çok katmanlı algılayıcı model ve radyal tabanlı fonksiyon ağ model çözümleri için Matlab R2010b programı, çoklu doğrusal regresyon model çözümü için SPSS 13 paket programı kullanılmıştır. Firmanın ıskarta oranı tahmininde bu üç model kıyaslanmış ve en uygun modelin çok katmanlı algılayıcı model olduğu belirlenmiştir.

Anahtar Kelimeler: Iskarta Oranı, Radyal Tabanlı Fonksiyon Ağ Modeli, Yapay Sinir Ağları, Çok Katmanlı Algılayıcı Model, Çoklu Doğrusal Regresyon Model

Suggested citation

Arıkan Kargı, V. S. (). A Comparison of Artificial Neural Networks and Multiple Linear Regression Models As Predictors of Discard Rates In Plastic Injection Molding. Alphanumeric Journal, 3(2), 65-72. http://dx.doi.org/10.17093/aj.2015.3.2.5000149667

bibtex

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Volume 3, Issue 2, 2015

2015.03.02.STAT.04

alphanumeric journal

Volume 3, Issue 2, 2015

Pages 65-72

Received: Nov. 4, 2015

Accepted: Dec. 22, 2015

Published: Dec. 31, 2015

Full Text [823.1 KB]

2015 Arıkan Kargı, VS.

This is an Open Access article, licensed under Creative Commons Attribution-NonCommercial 4.0 International License.

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