Bir üretim hattında robot seçimine çok kriterli karar verme yaklaşımı

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746452 A multi-criteria decision making approach for robot selection in a manufacturing environment.pdf (3.86 MB)

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2022

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Mechatronics Engineering
(2002)
The Atılım University Department of Mechatronics Engineering started its operation in 2002 as the Education Program in Mechatronics Engineering holding a “department” status in Turkey. In addition, it is the first and the only institution for mechatronic engineering education to obtain a MÜDEK (Association for Evaluation and Accreditation of Engineering Programs) accreditation for a duration of 5 years. Mechatronics engineering is a discipline of engineering that combines mechanical, electrical and electronic engineering and software technologies on a machine or a product. These features place the field on a pedestal in today’s industry. The education at our department is also backed by substantial laboratory opportunities. Our students create interesting products of their skills and creativity for their dissertation projects. Should they wish to do so, our students may also proceed with a double-major program in the fields of Computer Engineering, Electrical - Electronics Engineering, Industrial Engineering, or Mechanical, Automotive or Software Engineering. Upon their demands, the Department of Mechatronic Engineering also offers a “Cooperative Education” program implemented in coordination with industrial institutions. Students receiving a portion of their training at industrial institutions and prepare for professional life under this program

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Bu tezde, insan tabanlı üretim hatlarının robot tabanlı otomasyon sistemleri kullanılan üretim hatlarına dönüştürülmesinde kullanılacak en uygun mekatronik sistemlerin seçilmesi için çok kriterli karar verme (MCDM) yöntemi olarak SWARA-WASPAS yöntemini uyguluyoruz. Robotlar insanlardan daha hızlı ve daha hassas hale gelmekle kalmıyor, aynı zamanda uzun vadede genellikle daha uygun maliyetli oluyorlar. Farklı görevler için kullanılan bu robotlardan yüksek verim almak ve en uygun robotu seçmek en zor problemlerden biridir. En uygun olan sistemin seçilmesi için farklı kriterler ve farklı uzmanların görüşleri dikkate alınarak, SWARA-WASPAS hibrit karar verme yöntemi, bu sistemlerin karakteristik kriterlerine göre uygulanmış ve uygulama sonunda her seçim problemi için duyarlılık analizi yapılmıştır. Tez sonucunda her bir robot seçim probleminden en uygun robotlar belirlenmiş ve her robot sınıfı için yapılan duyarlılık analizi ile en uygun robotun değişmediği, ancak diğer alternatiflerin kullanılan optimallik katsayısı değerine bağlı olarak değişebileceği görülmüştür.
In this thesis, we apply SWARA-WASPAS method as a multi-criteria decision-making (MCDM) method for selecting the most suitable mechatronic systems to be used for the conversion of human-based production lines to production lines with robot-based automation systems. Robots are becoming not only quicker and more precise than people, but they are also frequently more cost-effective in the long term. Getting high efficiency from the robots used for different missions and choosing the most suitable robot are among the most difficult problems. To select the most suitable systems among different alternatives, SWARA-WASPAS hybrid decision making method, which suggest making the most appropriate choice among different alternatives by considering different criteria and the opinions of different experts, is applied according to the characteristic criteria of these systems, and a sensitivity analysis was carried out. As a result of the thesis, the most suitable robots from each robot selection problem are determined and it is seen that the most suitable robot is not change with the sensitivity analysis made for each robot class, but the other alternatives could change depending on the combined optimality coefficient value used.

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Mekatronik Mühendisliği, Robot imalatı, Mechatronics Engineering, SWARA yöntemleri, Robot manufacturing, WASPAS yöntemi, SWARA methods, WASPAS method, Çok kriterli karar verme, Multi criteria decision making

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130

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https://hdl.handle.net/20.500.14411/5003

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Master Tezler / Master Thesis