Prediction of technological process parameters based on experimental data
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RIS BIB ENDNOTEPrediction of technological process parameters based on experimental data
Data publikacji: 13.01.2016
Czasopismo Techniczne, 2015, Mechanika Zeszyt 2-M (7) 2015, s. 203 - 210
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Prediction of technological process parameters based on experimental data
In studies of new materials or products, it is necessary to carry out a series of tests to determine the physical properties of the product as a function of the manufacturing process parameters. The technological process of making successive samples for both experimental and research purposes is a mechanism which is time-consuming and which usually requires considerable financial outlays. At the same time, scientific literature offers a large number of experimental results carried out for a similar range of problems. The idea conceived in this study is to create a model that, based on the results of experiments collected from the scientific literature, will reduce the number of necessary physical tests by replacing them with an effective mechanism estimating some of the technological process parameters. Consequently , the concept of an algorithm has been presented to estimate the parameters of the manufacturing process of ADI (Austempered Ductile Iron). It can operate as a fundamental part of a larger expert system, supporting the design and configuration of production processes in various industries. This article describes the results of tests showing the efficiency of the proposed solution and outlines plans for further development of the system to increase its effectiveness and usefulness.
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Informacje: Czasopismo Techniczne, 2015, Mechanika Zeszyt 2-M (7) 2015, s. 203 - 210
Typ artykułu: Oryginalny artykuł naukowy
Tytuły:
Prediction of technological process parameters based on experimental data
Prediction of technological process parameters based on experimental data
Department of Applied Computer Science and Modelling, Faculty of Metals Engineering and Industrial Computer Science, AGH University of Science and Technology, ZI-IF UJK Kielce
Department of Applied Computer Science and Modelling, Faculty of Metals Engineering and Industrial Computer Science, AGH University of Science and Technology, ZI-IF UJK Kielce
Faculty of Metals Engineering and Industrial Computer Science, AGH University of Science and Technology.
Faculty of Metals Engineering and Industrial Computer Science, AGH University of Science and Technology.
Publikacja: 13.01.2016
Status artykułu: Otwarte
Licencja: Żadna
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