Development of a new test method for evaluating the abrasivity of granite building stones during polishing process based on weight loss of abrasive tool

Abrasivity of building stones is one of critical parameters during polishing stage in stone processing plants, which can significantly affect the abrasive tool consumption and the processing costs. Hence, the main purpose of this paper is to evaluate the building stone abrasivity based on the weight loss of abrasive tool during polishing process. For this purpose, a new laboratory test rig was developed, which can simulate the polishing process in laboratory scale as far as possible. Using this laboratory rig, a new test method was proposed, which gives an index herein called building stone abrasivity index (BSAI). This index was defined as the weight loss of abrasive tool during polishing process in order to estimate the building stone abrasivity. The proposed test method was carried out on 15 different types of Iranian granite building stones and the correlation of obtained BSAI with the physico-mechanical and petrographic properties of stone was investigated. Meaningful and reasonable relationships were observed. To evaluate the accuracy of proposed method, the correlation of BSAI with two most common abrasivity indices i.e. Schimazek abrasivity factor (F) and rock abrasivity index (RAI) was also discussed. The results indicated that there is a strong relationship between these indices, which verifies the accuracy of proposed method. Furthermore, the laboratory results were compared with data obtained from stone processing plants in order to validate the proposed test method. It was shown that the obtained BSAI has a good agreement with abrasivity of building stones in real conditions of stone processing plants. Therefore, the proposed test can be adopted as an accurate and rapid tool for evaluating the abrasivity of building stones in polishing process. Finally, relationship between BSAI and the abrasive tool lifespan (ATL) was examined and a model was suggested to predict ATL with acceptable accuracy.