Issue |
MATEC Web Conf.
Volume 357, 2022
25th Polish-Slovak Scientific Conference on Machine Modelling and Simulations (MMS 2020)
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Article Number | 04001 | |
Number of page(s) | 10 | |
Section | Advanced Industrial, Automotive and Green Energy Applications | |
DOI | https://doi.org/10.1051/matecconf/202235704001 | |
Published online | 22 June 2022 |
Intelligent System Supporting Technological Process Planning for Machining
1 Institute of Computer Science, Kazimierz Wielki University, Chodkiewicza 30, 85-064 Bydgoszcz, Poland
2 Faculty of Mechatronics, Kazimierz Wielki University, Chodkiewicza 30, 85-064 Bydgoszcz, Poland
The aim of the study was to develop a system supporting technological process planning, the functioning of which would resemble the way human experts act in their fields of expertise, one capable of gathering necessary knowledge, analysing data, and drawing conclusions to solve problems. This could be done by utilising artificial intelligence (AI) methods available within such systems. The study proved the usefulness of AI methods, and their significant effectiveness in supporting technological process planning. Technological-process planning based on an expert system is divided into the following stages: the selection of the semi-finished products; the establishing of the technological process structure, and the selection of the workpiece instrumentation, machine tools, tools, and tooling and machining parameters for each technological operation. The system-embedded knowledge takes the form of neural networks, decision trees and facts. The system is presented using the example of a real enterprise. The intelligent expert system is dedicated to process engineers who have not yet gathered sufficient experience in technological-process planning, or who have just begun their work in a given production enterprise, and are not very familiar with its machinery and other means of production.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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