The use of Fuzzy rule-based systems in the design process of the metallic products on example of microstructure evolution prediction

Andrzej Macioł () and Piotr Macioł ()
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Andrzej Macioł: AGH University of Science and Technology
Piotr Macioł: AGH University of Science and Technology

Journal of Intelligent Manufacturing, 2022, vol. 33, issue 7, No 6, 2012 pages

Abstract: Abstract The challenge on the contemporary market of consumer goods is a quick response to customer needs. It entails time restrictions, which a semi-finished products’ (including metal products) manufacturer must meet. This issue must be addressed during a design phase, which for the most of semi-finished products suppliers, takes part during a quotation preparation process. Our research is aimed at investigating possibility of application of Fuzzy Reasoning methods for shortening of a design process, being a part of this process. We present a study on application of simplified models for solving technological tasks, allowing obtaining expected properties of designed products. The core of our concept is replacing numerical models and classical metamodels with a rule-based reasoning. A quotation preparation process can be supported by solving a technological problem without numerical experiments. Our goal was to validate the thesis basing not only on the presentation of some potential solutions but also on the results of simulation studies. The problem is illustrated with an example of thermal treatment of aluminum alloys, aimed at evaluation of a summary fraction of precipitations as a function of time and technological parameters. We assumed that it is possible to use both unstructured and point numerical experiments for knowledge acquisition. Implementation of this concept required the use of hybrid knowledge acquisition methods that combine the results of point experiments with expert knowledge. A comparison of obtained results to the ones obtained with metamodels shows a similar efficiency of both approaches, while our method is less time and laborious.

Keywords: Quotation preparation; Metal products; Fuzzy reasoning; Knowledge acquisition; Takagi–Sugeno method; Mamdani’s method (search for similar items in EconPapers)
Date: 2022
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DOI: 10.1007/s10845-022-01949-6

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