Sawing of natural stones with diamond-impregnated circular saws is extensively implemented in stone processing plants in variety of applications that include sawing, cutting, splitting and trimming. Hence, the cost of diamond saws and energy have become important input in terms of estimating the hourly areal slab productions (HASPs) from the standpoint of effective cost analyses, feasible and sustainable designing of stone processing plants prior to reaching a decision for the investment. This study aimed at estimating the HASPs of the machines with circular diamond saws during the dimensioning of marble blocks quarried in Mugla (Turkey) Region. Thus, the models were generated to estimate the HASPs by artificial neural networks (ANN) and regression method (RM), based on Shore and Schmidt hardness values of rocks. Also, HASPs were acquired through in-plant measurements in order to justify the HASPs estimated by ANN and RM models. The analyses of the models generated using ANN proved to yield very strong consistencies with HASPs measured in the plants. Hence, the HASPs can be estimated reliably by the ANN models which also may be considered as a tool in designing of natural stone processing plants based on rock surface hardness.

中文翻译：

---

基于 Mugla 大理石表面硬度值的人工神经网络和回归方法对圆形金刚石锯的性能预测，土耳其

使用金刚石浸渍圆锯锯切天然石材在石材加工厂中广泛实施，其应用范围包括锯切、切割、劈开和修边。因此，在做出投资决定之前，从有效成本分析、石材加工厂的可行和可持续设计的角度来看，金刚石锯片和能源的成本已成为估算每小时面积板坯产量 (HASP) 的重要投入。本研究旨在评估在穆拉（土耳其）地区开采的大理石块尺寸测量过程中使用圆形金刚石锯的机器的 HASP。因此，基于岩石的肖氏硬度和施密特硬度值，通过人工神经网络 (ANN) 和回归方法 (RM) 生成模型以估计 HASP。还，HASP 是通过厂内测量获得的，以证明 ANN 和 RM 模型估计的 HASP 是合理的。使用 ANN 生成的模型分析证明与在工厂中测量的 HASP 产生非常强的一致性。因此，可以通过 ANN 模型可靠地估计 HASP，也可以将其视为基于岩石表面硬度设计天然石材加工厂的工具。