Indian Journal of Science and Technology

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ANFIS based Model for Surface Roughness Prediction for Hard Turning with Minimal Cutting Fluid Application


Affiliations
1 Department of Mechanical Engineering, Karuyna University, Karunya Nagar, Coimbatore – 641114, Tamil Nadu, India
2 Department of Mechanical Engineering, Noorul Islam Centre for Higher Education, Kumaracoil – 629180, Thuckalay, Kanyakumari, Tamil Nadu, India
 

Background/Objectives: Nowadays artificial intelligence plays an important role in manufacturing sector. How to utilize that in an effective manner is a key factor of optimization. So identification of optimal modeling tool for effective manufacturing gives an extraordinary output. Methods/Statistical Analysis: This paper develops an Adaptive Neuro Fuzzy Inference System (ANFIS) model with hybrid model to predict the Surface Roughness (SR) of the H13 tool steel work piece of 45 HRC hardness value. The investigation of operation has been done in hard turning using minimal cutting fluid application. Findings: The effect of the different input parameters like cutting force, temperature and vibration has been analyzed. Here the hybrid type of ANFIS model is created with triangular membership function and the observed results indicated that the predicted output surface roughness is almost very close to the actual output obtained in the experimental work.

Keywords

Artificial Intelligence, Fuzzy Inference System, Surface Roughness, Turning
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  • ANFIS based Model for Surface Roughness Prediction for Hard Turning with Minimal Cutting Fluid Application

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Authors

R. Anil Raj
Department of Mechanical Engineering, Karuyna University, Karunya Nagar, Coimbatore – 641114, Tamil Nadu, India
M. Dev Anand
Department of Mechanical Engineering, Noorul Islam Centre for Higher Education, Kumaracoil – 629180, Thuckalay, Kanyakumari, Tamil Nadu, India
K. Leo Dev Wins
Department of Mechanical Engineering, Karuyna University, Karunya Nagar, Coimbatore – 641114, Tamil Nadu, India
A. S. Varadarajan
Department of Mechanical Engineering, Karuyna University, Karunya Nagar, Coimbatore – 641114, Tamil Nadu, India

Abstract


Background/Objectives: Nowadays artificial intelligence plays an important role in manufacturing sector. How to utilize that in an effective manner is a key factor of optimization. So identification of optimal modeling tool for effective manufacturing gives an extraordinary output. Methods/Statistical Analysis: This paper develops an Adaptive Neuro Fuzzy Inference System (ANFIS) model with hybrid model to predict the Surface Roughness (SR) of the H13 tool steel work piece of 45 HRC hardness value. The investigation of operation has been done in hard turning using minimal cutting fluid application. Findings: The effect of the different input parameters like cutting force, temperature and vibration has been analyzed. Here the hybrid type of ANFIS model is created with triangular membership function and the observed results indicated that the predicted output surface roughness is almost very close to the actual output obtained in the experimental work.

Keywords


Artificial Intelligence, Fuzzy Inference System, Surface Roughness, Turning



DOI: https://doi.org/10.17485/ijst%2F2016%2Fv9i13%2F132264