Endüstriyel Robot Seçiminde Hibrit Çok Kriterli Karar Yaklaşımı

Year 2020, Ejosat Special Issue 2020 (ISMSIT), 1 - 9, 30.11.2020

Mehmet Şahin

https://doi.org/10.31590/ejosat.818275

Cited By: 1

Abstract

Dünya çapında çok sayıda imalat şirketi, artan verimlilik ve karlılık gibi avantajları nedeniyle endüstriyel robotları yaygın olarak benimsemiştir. Çok çeşitli uygulamalar için çok sayıda özellik ve beceriye sahip robotlar mevcuttur. Bunlar kaynak, montaj, malzeme taşıma, yükleme ve boyama dahil olmak üzere çeşitli endüstriyel uygulamalarda çok sayıda görevi yerine getirebilirler. Belirli bir uygulama için robot seçimi, karmaşıklığı, gelişmiş özellikleri ve olanakları nedeniyle çok yönlü bir görevdir. Karar vericinin, çeşitli özellikleri dikkate alarak, faydaları en üst düzeye çıkararak ve maliyetleri en aza indirerek en uygun robotu seçmesi gerekir. Bu bağlamda, bu çalışmanın temel amacı, endüstriyel robot seçimi için bir hibrit çok kriterli karar analizi yaklaşımı sunmaktır. Optimal robot seçimi, standart sapma (SD), ortalama ağırlık (MW) ve Shannon entropisi olmak üzere üç ağırlıklandırma yöntemine ve üç çok kriterli karar verme yöntemine, yani ARAS (additive ratio assessment), SAW (simple additive weighting) ve WPM (weighted product method) dayalı olarak gerçekleştirilir. Kriter ağırlıklarını belirlerken öznel değerlendirmeleri ortadan kaldırmak için nesnel ağırlıklandırma yöntemleri, SD, MW ve Shannon entropisi benimsenmiştir. Her bir MCDA yönteminin girdisi olarak her ağırlıklandırma yönteminin çıktısını kullanarak, dokuz farklı sıralama modeli geliştirilmiştir. Tüm modeller arasındaki korelasyon, Kendall'ın korelasyon katsayıları ile incelenmektedir. Tüm yöntem çiftlerinin sonuçları, nihai bir fikir birliği sıralamasına ulaşmak için Borda yöntemiyle entegre edilir. Sonuçlar, önerilen hibrit yaklaşımın bu çalışmanın amacı için başarıyla kullanılabileceğini ve ARAS'ın en tutarlı yöntem olduğunu göstermektedir.

Keywords

Endüstriyel robotlar, Robot seçimi, Çok kriterli karar verme, Borda, ARAS

A Hybrid Multicriteria Decision Approach for Industrial Robot Selection

Abstract

Numerous manufacturing companies worldwide have widely adopted industrial robots due to their advantages, such as increased efficiency and profitability. Robots with numerous features and abilities are available for a wide variety of applications. They can handle numerous tasks in various industrial applications, including welding, assembly, material handling, loading, and painting. The selection of a robot for a particular application is a multifaceted task due to its complexity, advanced features, and facilities. The decision-maker needs to choose the most suitable robot, taking into account the various features, maximizing benefits, and minimizing costs. In this context, the main objective of this study is to present an integrated multiple criteria decision analysis (MCDA) approach for industrial robot selection. The selection of the optimal robot is conducted based on three weighting methods, namely standard deviation (SD), mean weight (MW), and Shannon entropy, and three MCDA methods, namely additive ratio assessment (ARAS), simple additive weighting (SAW), and weighted product method (WPM). The objective weighting methods, SD, MW, and Shannon entropy, are adopted to eliminate subjective evaluations while determining attribute weights. Using the output of each weighting method as the input of each MCDA method, nine different ranking models are developed. The correlation between all models is examined through Kendall’s correlation coefficients. The results of all method pairs are integrated through the Borda method to reach a final consensus ranking. The results indicate that the proposed hybrid approach can be utilized successfully for the purpose of the present study, and ARAS is the most robust method.

Keywords

Industrial robots, Robot selection, Multi-attribute decision making, Borda, Additive ratio assessment

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