Wear Studies on Incoloy-800 and Prediction of Wear by ANN Model
- Mr.Mohit Kumar
- Prof. Subhash Chandra Bose
- Prof. B. Kotiveerachari
S/N ratio, ANOVA, Multiple Regression Model, ANN
Wear is one of the predominant mechanisms responsible for machine component failures and resulting economic loss to the industry in form of loss of material, investments on large stocks of metal cutting tools and reduction in the operating life of machinery. Many methods and techniques like alloying, melt treating, heat treating, surface coatings, etc. have been tried for maximizing wear resistance of a range of super alloys. The present work is aim to modeling & prediction of parameters affecting mechanical wear of Incoloy-800 using Taguchi’s methodology to design experiments and Artificial Neural Networking to model and predict the parameters. Wear has been defined as the progressive loss of substance from the operating surface of a body, occurring as a result of relative motion at the interface of a friction couple. Wear is quantified by volume loss per unit Newton meter. These preliminary experiments showed that the values of wear weight loss, height loss and wear rate are less at low sliding distance, low load and high speed. The final result shows that the contribution of sliding distance is 73.80%, 73.70% and 43.67% for weight loss, wear height loss and wear rate respectively
Mr.Mohit Kumar, Prof. Subhash Chandra Bose, Prof. B. Kotiveerachari. "Wear Studies on Incoloy-800 and Prediction of Wear by ANN Model".INTERNATIONAL JOURNAL OF ENGINEERING DEVELOPMENT AND RESEARCH ISSN:2321-9939, Vol.1, Issue 1, pp.1 - 12, URL :https://rjwave.org/ijedr/papers/IJEDR1301001.pdf
Volume 1 Issue 1
Pages. 1 - 12