The Prediction of Moulding Sand Moisture Content Based on the Knowledge Acquired by Data Mining Techniques

Author:

Regulski K.,Jakubski J.,Opaliński A.,Brzeziński M.,Głowacki M.

Abstract

Abstract The subject of the study is the improvement of the quality of moulding sand preparation. An exploration research performed on the data concerning moulding sand quality parameters was described. The aim of the research was to find relationships between various factors determining the properties of moulding sands and, based on the results obtained, build models predicting the sand moisture content with the induction of classification and regression trees. A two-match prediction approach was demonstrated and its effectiveness in evaluating the moulding sand moisture content was discussed. The knowledge in the form of rules acquired in this way can be used in the creation of knowledge bases for systems supporting decisions in the diagnostics of the moulding sand rebonding process. Formalized knowledge also facilitates further processing of the measurement data.

Publisher

Walter de Gruyter GmbH

Subject

Metals and Alloys

Reference17 articles.

1. Parametric representation of TTT diagrams of ADI cast iron of Metallurgy and;Olejarczyk;Archives Materials,2012

2. An exploratory technique for investigating large quantities of categorical data;Kass;Applied Statistics,1980

3. The Computer Support of Diagnostics of Circle Crystallizers;David;Metalurgija,2014

4. Recognition of thermal images of direct current motor with application of area perimeter vector and bayes classifier;Glowacz;Measurement Science Review,2015

5. Forward and reverse mappings in green sand mould system using neural networks;Mahesh Parappagoudar;Applied Soft Computing,2008

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