Modeling and Estimation of Production Rate in Ornamental Stones Sawing Based on Brittleness Indexes

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Abstract

As for estimating the cost and planning the process of the rock sawing plants, it is significant to predict the production rate of ornamental stones sawing. To promote the efficiency in planning these rock sawing projects, scholars have been trying to find a high-accuracy method of production rate estimation. Moreover, targeting at the 28 granite and carbonates stone in the nature, this study examined the connection between two various brittleness indexes in statistics, including the ratio of compressive strength to tensile strength (B1) and places below the line of compressive strength and the line of tensile strength (B2) in rocks and production rate had been studied. Through the results of cross plots analysis, it was indicated that there existed a strong connection between production rate and the brittleness B1 and B2. Finally, in this thesis, through adding B1 factor, it has improved the estimation model for production rate which Mikaeil et al. (2013) have established. What's more, by virtue of brittleness about B1 and B2, this production rate estimation model has been established successfully for natural stone sawing. Actually, the way of estimating the production rate of 28 rock samples is to utilize the two kinds of models described before. Through the result, it is showed that the production rate estimated by the improved model corresponds to the value of production rate of rock testing. Meanwhile, the precision has been greatly improved with comparison to the model of estimating the production rate designed by Mikaeil et al. (2013). Thus, on the basis of the new model, a dependable prediction for ornamental stones production is put forward in this paper. And it is required to do a further study involving different rock types since limited rock types were used in this study.

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APA

Wang, P. (2019). Modeling and Estimation of Production Rate in Ornamental Stones Sawing Based on Brittleness Indexes. Mathematical Problems in Engineering, 2019. https://doi.org/10.1155/2019/3232517

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