Prediction of Wear Properties of Experimental Produced Porcelain Ceramics Using Artificial Neural Networks (ANN)

Year 2023, Volume: 1 Issue: 2, 66 - 74, 31.12.2023

Ahmet Gürkan Yüksek , Tahsin Boyraz , Ahmet Akkuş

Abstract

In this study, the production and wear properties of porcelain ceramics produced by powder metallurgy method were examined and modelling with artificial neural networks was studied using the experimental data obtained. Porcelain ceramics were prepared by the powder metallurgy route. Mixtures prepared by mechanical alloying method in alumina ball mills were produced by sintering under normal atmospheric conditions after being shaped in a dry press. After drying, the powders were compressed by uniaxial pressing at 200 MPa. The green compacts were sintered at 1100-1200 oC for 1-5 h in air. Then, characterization studies of the sintered samples were carried out and the wear experimental results obtained were converted into data suitable for modelling with artificial neural networks. In the continuation of the study, experimental wear results using artificial neural networks were analysed and modelled. Wear load, wear time, sintering temperature and sintering time were used as artificial neural networks input variables. Wear values were taken as output variables of artificial neural networks. An artificial neural network was established for the prediction of wear properties of porcelain ceramic composites. As a result, the training results and test results were compared with the actual values to control the network performance. A good agreement was observed between the experimental and artificial neural networks model results. After the artificial neural networks estimation, confirmation tests were performed to confirm the experimental results.

Keywords

Ceramic, Porselen, Wear, Artificial Neural Networks

Deneysel Olarak Üretilen Porselen Seramiklerin Aşınma Özelliklerinin Yapay Sinir Ağları (YSA) Kullanılarak Tahmin Edilmesi

Abstract

Bu çalışmada toz metalurjisi yöntemi ile üretilen porselen seramiklerin üretim ve aşınma özellikleri incelenmiş ve elde edilen deneysel veriler kullanılarak yapay sinir ağları ile modelleme çalışması yapılmıştır. Porselen seramikler toz metalurjisi yöntemi ile hazırlanmıştır. Alümina bilyalı değirmenlerde mekanik alaşımlama yöntemi ile hazırlanan karışımlar kuru preste şekillendirildikten sonra normal atmosferik koşullarda sinterlenerek üretilmiştir. Kurutulduktan sonra tozlar 200 MPa'da tek eksenli presleme ile sıkıştırılmıştır. Yeşil kompaktlar 1100-1200 oC'de 1-5 saat süreyle havada sinterlenmiştir. Ardından sinterlenen numunelerin karakterizasyon çalışmaları gerçekleştirilmiş ve elde edilen aşınma deneysel sonuçları yapay sinir ağları ile modellemeye uygun verilere dönüştürülmüştür. Çalışmanın devamında yapay sinir ağları kullanılarak deneysel aşınma sonuçları analiz edilmiş ve modellenmiştir. Yapay sinir ağları giriş değişkenleri olarak aşınma yükü, aşınma süresi, sinterleme sıcaklığı ve sinterleme süresi kullanılmıştır. Aşınma değerleri yapay sinir ağlarının çıkış değişkenleri olarak alınmıştır. Porselen seramik kompozitlerin aşınma özelliklerinin tahmini için bir yapay sinir ağı kurulmuştur. Sonuç olarak, ağ performansını kontrol etmek için eğitim sonuçları ve test sonuçları gerçek değerlerle karşılaştırılmıştır. Deneysel ve yapay sinir ağları model sonuçları arasında iyi bir uyum gözlenmiştir. Yapay sinir ağları tahmininden sonra, deneysel sonuçları doğrulamak için doğrulama testleri yapılmıştır.

Keywords

Porselen, Aşınma, Yapay Sinir Ağları, seramik

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