Artificial Neural Network Assisted Sensor Fusion Model for Predicting Surface Roughness During Hard Turning of H13 Steel with Minimal Cutting Fluid Application

Author:

Arulraj J. Gerald Anto,Wins K. Leo Dev,Raj Anil

Publisher

Elsevier BV

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference15 articles.

1. Development of novel sustainable neat-oil metal working fluids for stainless steel and titanium alloy machining;Abdalla;Part 1. Formulation development, Journal of Advanced Manufacturing Technology,2007

2. A comparison of statistical and AI approaches to the selection of process parameters in intelligent machining;Chryssolouris;ASME Journal of Engineering for Industry,1990

3. Role of cryogenic cooling on cutting temperature in turning steel;Dhar;Transactions of the ASME,2002

4. Intelligent process supervision for predicting tool wear in machining processes;Haber;Mechatronics,2003

5. Artificial Neural Network assisted sensor fusion model for predicting tool wear online during hard turning;Leo Dev Wins;9th international symposium on measurement and quality control (9th ISMQC), IIT Madras,2007

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