Data-driven casting defect prediction model for sand casting based on random forest classification algorithm

The complex sand-casting process combined with the interactions between process parameters makes it difficult to control the casting quality,resulting in a high scrap rate.A strategy based on a data-driven model was proposed to reduce casting defects and improve production efficiency,which includes the random forest(RF)classification model,the feature importance analysis,and the process parameters optimization with Monte Carlo simulation.The collected data includes four types of defects and corresponding process parameters were used to construct the RF model.Classification results show a recall rate above 90% for all categories.The Gini Index was used to assess the importance of the process parameters in the formation of various defects in the RF model.Finally,the classification model was applied to different production conditions for quality prediction.In the case of process parameters optimization for gas porosity defects,this model serves as an experimental process in the Monte Carlo method to estimate a better temperature distribution.The prediction model,when applied to the factory,greatly improved the efficiency of defect detection.Results show that the scrap rate decreased from 10.16% to 6.68%.

A new low-cost method of reclaiming mixed foundry waste sand based on wet-thermal composite reclamation

A lot of mixed clay-resin waste sand from large-scale iron foundries is discharged every day; so mixed waste sand reclamation in low cost and high quality has a great realistic significance. In the study to investigate the possibility of reusing two types of waste foundry sands, resin bonded sand and clay bonded sand which came from a Chinese casting factory, a new low-cost reclamation method of the mixed foundry waste sand based on the wet-thermal composite reclamation was proposed. The waste resin bonded sand was first reclaimed by a thermal method and the waste clay bonded sand was reclaimed by a wet method. Then, hot thermal reclaimed sand and the dehydrated wet reclaimed sand were mixed in certain proportions so that the hot thermal reclaimed sand dried the wet reclaimed sand leaving some water. The thermal reclamation efficiency of the waste resin bonded sand was researched at different heat levels. The optimized wet reclamation process of the waste clay bonded sand was achieved by investigating the effects of wet reclamation times, sand-water ratio and pH value on the reclaimed sand characteristics. The composite reclamation cost also was calculated. The research results showed that the properties of the mixed reclaimed sand can satisfy the application requirements of foundries; in which the temperature of the thermal reclamation waste resin bonded sand needs to be about 800 oC, the number of cycles of wet reclamation waste clay bonded sand should reach four to five, the optimal sand-water ratio of wet reclamation is around 1:1.5, and the pH value should be adjusted by adding acid. The mass ratio of hot thermal reclaimed sand to dehydrated wet reclaimed sand is about 1:2.5, and the composite reclaimed sand cost is around 100 yuan RMB per ton.