AISI 304 ÖSTENİTİK PASLANMAZ ÇELİĞİN TORNALANMASINDA YÜZEY PÜRÜZLÜLÜĞÜNÜN VARYANS ANALİZİ İLE MODELLENMESI

Bu çalışma, AISI 304 Östenitik paslanmaz çeliğinin tornalanması sırasında yüzey pürüzlülüğünün modellenmesi ve optimizasyonu için yapılmıştır. Deney numuneleri 1050°C’de 60 dakika tavlanmış ve suya çekilmiştir. Daha sonra tavlanmış numuneler 700°C’de sırası ile 30, 90 ve 240 dakika bekletilmiş ve ardından oda sıcaklığında soğutulmuştur. Deneysel çalışmalar farklı kesme hızları, ilerleme miktarı ve bekleme süresi esas alınarak yapılmıştır. Tornalama işleminde CCMT09T308-41 kesme takımı kullanılarak yüzey pürüzlülüğünün ölçümünde tam deneysel çalışma, sinyal gürültü oranı ve varyans analizi yapılmıştır. Yapılan analizler sonucunda, yüzey pürüzlülüğüne etki eden en önemli faktörün ilerleme oranı, bekleme süresinin ikinci ve en az etkili olan parametrenin ise kesme hızı olduğu tespit edilmiştir. Aynı zamanda yüzey pürüzlülüğünü modellemek için doğrusal olmayan regresyon metoduda kullanılmıştır. Regresyon modelinin yüksek korelasyon katsayısının (0.95), gerçekleştirilen modelin yüzey pürüzlülüğünü modellemek için yeterli ve deneysel sonuçlar ile analiz sonuçlarının uyumlu olduğu görülmüştür.

Anahtar Kelimeler:

AISI304, Yüzey Pürüzlülüğü, Varyans Analizi, Regressyon Analizi, Östenitik Paslanmaz Çelik

MODELLING OF SURFACE ROUGHNESS WITH VARIANCE ANALYSIS IN TURNING OF AISI 304 AUSTENITIC STAINLESS STEEL

In this study, an attempt has been made to optimize and model to surface roughness when turning AISI 304 austenitic stainless steel. The as – received specimens were annealed at 1050˚C for 60 minutes and water quenched. Annealed specimens were then tempered at 700˚C for 30 90 and 240 minutes respectively and followed by room cooling. The experimental studies were conducted under varying cutting speed, feed rate and holding time. A full factorial experimentation, the signal – to – noise (S/N) ratio and the analysis of variance (ANOVA) were employed to the study the surface roughness in turning AISI 304 using CCMT09T308 – 41 insert cutting tools. The conclusions revealed that the feed rate was the most important factor on the surface roughness, whereas holding time was the second ranking factor and cutting speed was the least. A non – linear regression method was also used to model the surface roughness. The high correlation coefficient (0.95) of regression model showed that the model can adequately describe the performance within the limits of factors being studied. The experimental and predicted values were in a good agreement.

Keywords:

AISI304, Surface Roughness, ANOVA, Regression Analysis, Austenitic Stainless Steel,

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