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Journals / Sigma Mühendislik ve Fen Bilimleri Dergisi / 2018 / Cilt: 36 - Sayı: 4

PREDICTION OF SURFACE HARDNESS IN A BURNISHING PROCESS USING TAGUCHI METHOD, FUZZY LOGIC MODEL AND REGRESSION ANALYSIS

Gökhan BAŞAR
Funda KAHRAMAN
Pages
1283–1295
Publication Date
2018-12-01
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

With high correlation coefficient (R2= 97.52 %), the model was regarded adequately accurate.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The available work is aimed for comparison and estimation of surface hardness in ball burnishing process of aluminum alloy based upon the Taguchi technique, Fuzzy logic and regression models.
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Key Findings & Data:The ball burnishing parameters like burnishing speed, force, feed rate and number of passes were designed using Taguchi L25 orthogonal design matrix.
💡
Conclusion & Impact:With high correlation coefficient (R2= 97.52 %), the model was regarded adequately accurate.
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Ball burnishing · surface hardness · Taguchi method

Abstract

The available work is aimed for comparison and estimation of surface hardness in ball burnishing process of aluminum alloy based upon the Taguchi technique, Fuzzy logic and regression models. The ball burnishing parameters like burnishing speed, force, feed rate and number of passes were designed using Taguchi L25 orthogonal design matrix. Taguchi’s signal to noise ratio was used to optimize the surface hardness. The effect of burnishing parameters on surface hardness was established by analysis of variance. Fuzzy logic was conducted using Matlab Toolbox. Taguchi technique, second order regression model and variance analysis were developed using MINITAB 17. The predicted hardness values of performance parameters were operated to compare the distinct models. The results of predicted models indicated that the consistent predictive model is the fuzzy logic model. With high correlation coefficient (R2= 97.52 %), the model was regarded adequately accurate.

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Cite This Article

BAŞAR, G., KAHRAMAN, F. (2018). PREDICTION OF SURFACE HARDNESS IN A BURNISHING PROCESS USING TAGUCHI METHOD, FUZZY LOGIC MODEL AND REGRESSION ANALYSIS. Sigma Mühendislik ve Fen Bilimleri Dergisi, Cilt: 36 - Sayı: 4, 1283–1295. https://ajindex.com/articles/419011

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