Adhesion strength prediction of craln coating on al-si alloy (LM28): Fuzzy modelling

• Main Authors: Maher, Ibrahem, Mehran, Q. M.
• Format: Article
• Published: Korean Inst Metals Materials 2022
• Subjects: Q Science (General); TN Mining engineering. Metallurgy
• Online Access: http://eprints.um.edu.my/33836/

In this study a method of predicting the adhesion strength of Chromium aluminum nitride (CrAlN) coating on Al-Si alloy (LM28) using fuzzy logic technique was introduced. LM28 was coated with CrAlN under dissimilar coating conditions. The CrAlN coated substrates adhesion strength was determined by micro-scratch apparatus. The microstructure, topographical analysis and composition of selected coated substrates were characterized using scanning electron microscopy coupled with Energy-dispersive X-ray spectroscopy. A fuzzy logic model was applied to predict the adhesion strength of CrAlN coating on LM28. RF power, DC power, nitrogen flow rate, and temperature based on the trained data achieved from the micro scratch test were used as controllable process parameters. Then, three new experimental confirmation runs were conducted to verify the results predicted via the Fuzzy model. The predicted adhesion strength was equated with measured data. The maximum prediction error was 5.2%, while the average prediction error was 3.5%. Finally, prediction resulted in the improvement of surface hardness value from 0.9 GPa to 4.5 GPa, signifying an enhancement by 5 times. Graphic