A Review of Artificial Intelligence Technologies to Achieve Machining Objectives

Author:

Deivanathan R. 1

Affiliation:

1. VIT Chennai, India

Abstract

Bridging the design, planning and manufacturing departments of a production enterprise is not a conclusive effort for the implementation of computer integrated manufacturing. Continuous interaction and seamless exchange of information among these functions is needed and requires the maintenance of a large database and user-friendly search and optimization techniques. Among several artificial intelligence techniques capable of the above task, four important and popular ones are, expert systems, artificial neural networks, fuzzy logic and genetic algorithms. In this chapter, these four techniques have been conceptually studied in detail and exemplified by reviewing an application in the manufacturing domain. Successful implementations of artificial intelligence that are recently reported in machining domain are also reviewed, suggesting potential applications in the future.

Publisher

IGI Global

Reference74 articles.

1. ANN Surface Roughness Optimization of AZ61 Magnesium Alloy Finish Turning: Minimum Machining Times at Prime Machining Costs

2. Operation sequencing and machining parameter selection in CAPP for cylindrical part using hybrid feature based genetic algorithm and expert system.;A.Agrawal;International Research Journal of Engineering and Technology,2017

3. Investigation of the effect of cutting speed on the Surface Roughness parameters in CNC End Milling using Artificial Neural Network

4. Selection of optimum cutting speed in end milling process using fuzzy logic.;N. K. A.Al-Sahib;Innovative Systems Design and Engineering,2014

5. Alharthi, N. H., Bingol, S., Abbas, A. T., Ragab, A. E., El-Danaf, E. A., & Alharbi, H. F. (2017). Optimizing Cutting Conditions and Prediction of Surface Roughness in Face Milling of AZ61 Using Regression Analysis and Artificial Neural Network. Advances in Materials Science and Engineering.

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