Master'sOpen Access

Inconel 718 nikel esaslı süper alaşımın delik delme işlemlerinde kesme parametrelerinin yüzey pürüzlülüğüne etkisinin Taguchi yöntemi ve gri ilişkisel analiz ile optimizasyonu

2022
0 views
0 downloads
Advisor: Dr. Öğr. Üyesi Harun Yaka

Abstract (EN)

To make an efficient production in machining, it is necessary to reduce costs. In addition, product quality should be increased by reducing costs. In order to reduce production costs and increase product quality, the cutting tools used during machining should be selected correctly and the machining parameters should be determined accordingly. In this study, drilling was applied to Inconel 718 steel, which is a nickel-based superalloy frequently used in the manufacturing industry. Different cutting parameters and levels are used to find the best hole quality in drilling. Drilling operations were made with two separate drill bits, coated and uncoated. At the end of the experiments, the surface roughness of the holes was investigated. The test list was created with the Taguchi method and the surface roughness of the surfaces obtained at the end of the experiments was measured. The results were optimized using Taguchi and GIA (Gray Relational Analysis) methods. Optimizations were made by choosing the smallestbest signal-to-noise ratio since the smallest value of the surface roughness was desired. At the end of the experiments, the cutting parameters and levels at which we obtained the lowest surface roughness were determined. The sequence of optimum parameter levels was A2B3C1D3. The parameter affecting the surface roughness the most was determined. And the confidence level of the study was found by using analysis of variance. The most effective parameter was the cutting speed, the confidence level of the study was 84.23%.

Author

Dr. Ramazan Atılkan

How to Cite

Ramazan Atılkan (Master Thesis). Inconel 718 nikel esaslı süper alaşımın delik delme işlemlerinde kesme parametrelerinin yüzey pürüzlülüğüne etkisinin Taguchi yöntemi ve gri ilişkisel analiz ile optimizasyonu, 2022, Amasya University.

License

Tüm Hakları Saklıdır

This work is shared under the specified license terms.

More theses from Amasya University