İmalat hücresi oluşturulması için farklı kümeleme yöntemlerinin performans karşılaştırması

Year 2017, Volume: 21 Issue: 5, 1031 - 1044, 01.10.2017

Sinem Büyüksaatçı Kiriş Fatih Tüysüz

https://doi.org/10.16984/saufenbilder.310267

Cited By: 1

Abstract

Bu çalışma, hücresel imalat sistemi tasarımının temel ve önemli aşaması olan hücre oluşturmaya değinmektedir. Çalışmada hücre oluşturma uygulamalarında yaygın olarak kullanılan üç yöntem; k-ortalamalar kümeleme algoritması, ortalama bağlantılı kümeleme algoritması ve beklenti maksimizasyonu algoritmasını kullanan bulanık kümeleme algoritması incelenmektedir. Bir inşaat ekipmanı üreticisinin silindir bölümünün tasarımı için bu yöntemlerin gerçek hayat uygulaması gerçekleştirilmiştir. Uygulanan her algoritmanın performansı hücre içi boşluklar, hücre içi işlem yoğunluğu ve hücreler arası taşıma miktarı ölçütlerine göre değerlendirilmektedir. Uygulama sonuçları, klasik kümeleme algoritmalarından en çok bilinen ve en yaygın olarak uygulanan k-ortalamalar kümeleme algoritmasının hücre oluşturma için hala etkili bir yöntem olduğunu göstermektedir.

Keywords

Hücresel imalat, Hücre oluşturma, K-ortalamalar algoritması, Ortalama bağlantılı kümeleme algoritması, Beklenti maksimizasyonu algoritması

Performance comparison of different clustering methods for manufacturing cell formation

Abstract

This study refers to cell formation, which is the fundamental and important stage of cellular manufacturing system design. Three widely used methods that are K-means clustering algorithm, average-linkage clustering algorithm and fuzzy clustering using expectation maximization algorithm for cell formation problem are studied. A real life application of these methods for the design of cylinder department of a construction equipment manufacturer is performed. The performance of each applied algorithm is evaluated according to intracellular voids, intracellular processing intensity and intercellular transportation measures. The application results indicate that K-means clustering algorithm, which is the most widely applied and most known one of classical clustering algorithms, is still an effective method for cell formation.

Keywords

Cellular Manufacturing, Cell Formation, K-Means Algorithm, Average Linkage Clustering Algorithm, Expectation Maximization Algorithm

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