Prediction of forging dies wear with the modified Takagi–Sugeno fuzzy identification method

ABSTRACT

Modern design of technological processes employs various numerical tools. Artificial Intelligence is one of the most promising approaches. However, its application in industrial conditions is still limited. One of the important obstacles is a lack of large data sets, which are necessary for the most of AI approaches. In the paper, we present a modified Takagi–Sugeno method, one of Fuzzy Rule-Based Systems family, applied for prediction of forging dies wear. A technological process, as well as acquired data are briefly discussed. The modified Takagi-Sugeno approach is introduced. Its main advantage, acquiring knowledge from experts instead of datasets, is emphasized. Assumptions, model details, and prediction results are included.

KEYWORDS:

• Artificial
• intelligence
• AI
• fuzzy
• identification
• reasoning
• forging
• tools
• wear
• prediction

Acknowledgments

Piotr Macioł and Barbara Mrzygłód were supported by the Ministry of Science and Higher Education, project no. 16.16.110.663.

Additional information

Funding

This work was supported by the Ministerstwo Nauki i Szkolnictwa Wyższego [16.16.110.663].