A comprehensive review on state-of-the-art applications of case based reasoning in aluminum foundries
1 Department of Production Engineering, KIT’S College of Engineering, Kolhapur, India.
2 Department of Computer Studies, CSIBER, Kolhapur, India.
Review Article
Global Journal of Engineering and Technology Advances, 2023, 17(03), 029–035.
Article DOI: 10.30574/gjeta.2023.17.3.0245
Publication history:
Received on 07 November 2023; revised on 18 December 2023; accepted on 21 December 2023
Abstract:
An Aluminium Foundry offers multiple opportunities for implementing expert systems across various domains, including component design, process planning, rejection reduction, and determining parameter values for Die-to-Die Design to achieve cost benefits. Considering the projected growth of the Global Aluminium Die Casting market at a 15 percent CAGR until 2025, one of the key hurdles to this growth lies in the requirement for substantial investments. This paper explores the diverse applications of expert systems in different aspects of aluminium casting, focusing on the utilization of Case-Based Reasoning (CBR) systems within Aluminium foundries. Case-Based Reasoning, a problem-solving approach, leverages past cases resembling the current problem to guide solutions for new challenges. The review encompasses various expert systems applied in aluminium casting and specifically highlights the application of Case-Based Reasoning systems. Additionally, it identifies gaps within the Die Design Support System for Gravity Die Casting utilizing Case-Based Reasoning, aiming to delve deeper into this particular area for potential improvements.
Keywords:
Aluminium Castings; Case Based Reasoning; Die Casting; Die Design; Manufacturing Optimization; Quality Improvement
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Copyright © 2023 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0