Development of an Expert System to Monitor Casting Defects in Foundries
Green sand molding is a commonly used casting technique for manufacturing steel castings. However, defects prevention and monitoring is an issue on which research is advancing continuously. The aim of this research work is to develop an expert system using C++. This system identifies the optimum input parameters, namely permeability, pouring temperature and green strength of the sand in order to give lower probability of defects. The defects used in this work are scabbing, sand fusion and blowholes. Experimental data from a foundry were collected for a period of 1 month with variations in the input parameters and analyzed for ranges of parameters in which defects are low. A rule-based expert system was written using CLIPS 2004, an expert system tool, wherein programming can be done using C++. The expert system so developed was used to predict the probability of occurrence of defects. Validation has to be done with more experimental work to fine-tune the expert system.
KeywordsExpert systems Casting defects CLIPS 2004 software
The authors acknowledge help from Hinduja Foundries for the experimental data. They also thank the Management, SSN College, for the academic freedom given to pursue research at the undergraduate level.
- 1.Sudesh, K., Prakash, G.R., Roshan, H.M.: Knowledge-based expert system for analysis of casting defects. AFS Trans. 96, 178–192 (1998)Google Scholar
- 2.Kay, I., Nagel, M.: Its time to play-name that green sand casting defect. Mod. Cast. 29–32 (2001)Google Scholar
- 3.Roy, T.: Analysis of casting defects in foundry by computerised simulations (CAE)—a new approach along with some industrial case studies. In: Transactions of 61st Indian Foundry Congress, pp. 1–9 (2013)Google Scholar
- 5.Jančíková, Z.: Utilization of artificial intelligence elements for prediction of forge ingots defects. InActa Mechanica Slovaca, 13–15 1–A(2007)Google Scholar
- 8.Rai1, A., Ganguly, S.K.: Web-based expert system for some defect in sand castings. Int. J. Adv. Eng. Res. Stud. Jan–March (2015)Google Scholar
- 10.Gavarieva, K.N., Simonova, L.A., Pankratov, D.L., Gavariev, R.V.: Development of expert systems for modeling of technological process of pressure casting on the basis of artificial intelligence. In: IOP Conference Series: Materials Science and Engineering, 240 (2017)Google Scholar