Stone Sawing Research Articles

Preliminary Study of Stone Sawing Sludges-based Alkali Activated Materials (AAMs) for the Conservation of Archaeological Ceramics

This paper presents research into the feasibility of using stone sawing sludge-based Alkali Activated Materials (AAMs) for conservation of Cultural Heritage. Sawing sludges are a stone processing waste product resulting from the mixing of rock powder with the water used to cool down the cutting blades. The chemical composition of the sawing sludges, when aluminosilicatic, is suitable for acting as a precursor to produce AAMs. AAMs are known for their low environmental impact and versatility since their existence is drawn from recycling waste materials. One of their possible applications is in the conservation of Cultural Heritage objects. This work presents a preliminary investigation into three sawing sludge-based AAMs with different mineralogical compositions and contributes to formulating guidelines for applying them as fillers on modern and archaeological ceramic pottery based on the evaluation of their workability, appearance and physical properties over time from the moment of application and up to 30 days. Dynamic Vapor Sorption and X-Ray Diffraction results provided an overview of the structural and mineralogical changes under high RH conditions, where the tested AAMs showed a type II isotherm curve, as expected for concrete-like materials, as well as disappearance of thermonatrite after one isothermal cycle. Ultrasonic Pulse Velocity test demonstrated the general homogeneity of the AAMs despite the lower velocity exhibited by one of the formulations, probably due to its internal pore distribution and possible presence of microstratification. The Oddy tests, application tests and colourimetric measurements evidenced the advantages and weaknesses of the AAMs, with overall encouraging results ensuing investment in further in-depth studies of these innovative conservation materials in view of their future use in the field of conservation of Cultural Heritage as a result of a circular economy model.

RESULTS OF EXPERIMENTAL RESEARCH ON OBTAINING LOW- CEMENT WALL MATERIALS FROM WASTE OF SAMING OF LOCAL LIME STONES

The results of experimental studies are presented on the production of single low-cement modified dry-pressed bricks from limestone stone sawing waste from Martakert stone quarries. The technological parameters for the manufacture of these bricks and their physical and mechanical properties have been established. A high convergence of the properties of the resulting wall material was determined in comparison with ceramic and silicate bricks used in construction. Using the method of analogy, the compliance of the quality indicators of experimentally obtained bricks with the requirements of regulatory documents was proven. The fundamental possibility of producing low- cement bricks from stone sawing waste from local quarries, as well as their use in construction, has been established. The production of low-cement bricks makes it possible to increase construction efficiency and reduce the cost of operating completed facilities. This also leads to a reduction in environmental risks from the accumulation of stone sawing waste in large areas and pollution of the air and water basins of the region.

Stone sawing machine at the Temple of Artemis in Jerash, Jordan

Stone sawing machine at the Temple of Artemis in Jerash, Jordan

Valorization of natural stone sawing waste as a functional additive in ceramic tile production

Valorization of natural stone sawing waste as a functional additive in ceramic tile production

Wear behavior and morphologic characterization of diamond segments induced by crystal plane characteristics of diamond grits in sawing hard materials

The wear of diamond grains (DGs) is a classic problem, affects the final cost, in sawing hard materials (granitic rocks) for slabs. However, the previous research rarely pays attention to study the wear of DGs considering the crystal plane characteristics. Hence, in this study, the aim is to explain the fracture morphology of DGs in sawing granitic rocks taking into account the crystal plane characteristics. The wear experiment was carried out with a frame saw. Then the surface morphology of DGs was characterized by scanning electron microscope (SEM). According to wear characteristics of DGs, the wear of DGs was divided into seven different types, including fresh, whole, micro fractured, pulled-out, flush with matrix, macro fractured and blunt. Interestingly, the bottom surface of the pulled-out DGs in contact with the matrix was mostly {100} crystal planes that account for approximately 80%. In addition, flush with matrix mostly occurred on the {111} crystal planes (account for 90%), and mostly at both ends of the diamond segments (DSs). Then, this phenomenon is explained by the interplanar spacing of DGs. Moreover, wear behavior and morphologic characterization of DGs were discussed considering the factors of stone sawing (e.g., detritus) and the characteristics of DGs (e.g., dislocation). Finally, wear evolution mechanism of DSs topography were proposed. This research enhances to deeply understand the wear of DGs in granite processing and provides guidance for the design of DSs.

Diamond tool wear monitoring by sensory analysis in milling of absolute black granite

Diamond tools suitable for machining operations of natural stones can be divided into two groups: cutting tools, including blades, the circular blades and the wires, and the surface machining ones, involving mills and grinders, that can be of different shapes. For the stone sawing process, the most adopted tool type is the diamond mill, whose duration and performance are influenced by various elements such as: the mineralogical characteristics of the material to be machined; the working conditions such as the depth of cut, the feed rate and the spindle speed; the production process of the diamond segment and the characteristics of both the matrix and the diamond, such as the size, the type and the concentration of the diamonds and the metal bond formulation hardness. This work allows to indirectly assess the wear of sintered diamond tools by signal analysis (in time and frequency domain) of the cutting force components acquired in the process. The results obtained represent a fundamental step for the development of a sensory supervision system capable of assessing the tool wear and hence to modify the process parameters in process, in order to optimize cutting performance and tool life.

The mechanics of sawing granite with diamond wire

Today, wire sawing of natural stone is undergoing widespread commercialization. In addition to rock extraction and processing with single wires, composed of a multitude of diamond-impregnated beads mounted onto a steel rope, this technology is increasingly used for slabbing of granite blocks on multi-wire machines. Evolving sophistication of stone sawing equipment dictates novel tool designs and formulations. For technologists specifying bead compositions, it is a common habit to instinctively follow the circular saw segment design guidelines. A poor tool performance is often an undesirable consequence of such an approach. To meet that challenge, theoretical models of sawing granite by means of a diamond wire saw and a diamond circular saw have been presented and contrasted with respect to diamond loading conditions. The analytical treatments are supported by scarcely available industrial quantitative assessments and qualitative observations. The evaluation of cutting forces and the identification of system characteristics affecting wire vibration and wire rotation are instrumental in both machine design and tool formulation. For practitioners working with granite, the provided knowledge is also essential to diagnose and prevent problems inherent in wire sawing, such as the high incidence of wire breakage, unsatisfactory tool life and cutting capability and eccentric bead wear.Graphical abstract

Assessing the System Vibration of Circular Sawing Machine in Carbonate Rock Sawing Process Using Experimental Study and Machine Learning

Predicting the vibration of the circular sawing machine is very important in examining the performance of the sawing process, as it shows the amount of energy consumption of the circular sawing machine. Also, this factor is directly related to maintenance cost, such that with a small increase in the level of vibration, the maintenance cost increases to a large extent. This paper presents new prediction models to assess the vibration of circular sawing machine. An evaluation model based on the imperialist competitive algorithm as one of the most efficient artificial intelligence techniques was used for estimation of sawability of the dimension stone in carbonate rocks. For this purpose, four main physical and mechanical properties of rock including Schimazek’s F-abrasivity, uniaxial compressive strength, mean Mohs hardness, and Young’s modulus as well as two operational parameters of circular sawing machine including depth of cut and feed rate, were investigated and measured. In the predicted model, the system vibration in stone sawing was considered as a dependent variable. The results showed that the system vibration can be investigated using the newly developed machine learning models. It is very suitable to assess the system vibration based on the mechanical properties of rock and operational properties.

Research on Sawing Mining Technology of Soft Dimension Stone

China is the main production and consumption country of dimension stone in the world, the development of dimension stone industry is of great significance. According to the concept, types and characteristics of dimension stone, this paper analyzes the factors affecting dimension stone mining, introduces the general technological process of dimension stone mining. On the basis of analysis, comparison and comprehensive research, combined with literature and practical experience of dimension stone exploitation, the paper puts forward more advanced, efficient and safer soft dimension stone sawing technology and various concrete schemes of soft dimension stone mining, and also discusses the advantages and disadvantages of sawing methods and the future development trends of sawing technology.

Digital twin of stone sawing processes

The industry is facing the management of manufacturing processes along the entire lifecycle of the product. It is helped by digital twin tools that may minimize the out of control of processes. Information and communication technologies help digital twin tools to monitor manufacturing performances. In this way, a continuous and unambiguous flow of information flows along the whole product lifecycle along digital process. They are based on data coming from manufacturing and inspection. Actually, no digital twin tool exists that assists machining of ornamental stones. Moreover, the models proposed by the literature take into account a unique aspect of the manufacturing process, such as the control of the cutting force and energy or the monitoring of the tool wear and, therefore, it does not exist a continuous flow of information from cutting force to tool monitoring. The present work introduces a digital twin tool to manage force, energy, and tool wear during machining of ornamental stone. It uses high-fidelity models for simulation that were widely experimentally tested. It establishes a continuous and unambiguous flow of information from machine to tool, and from cutting force and energy estimation to tool wear prediction. It was applied to two case studies and the obtained results agree with the experimental ones.

Effect of the rock properties on sawability of granite using diamond wire saw in natural stone quarries

Sawability of diamond wire saw is a cost-sensitive parameter in natural stone quarries that affects directly the production planning and equipment selection. The present study intended to investigate the effect of rock properties on sawability of diamond wire saw in granite quarries by considering the cutting rate and unit wear as the main sawability criteria. Hourly cutting rate of stone and unit wear of diamond impregnated beads of diamond wire saw were measured during the stone sawing process in 9 granite quarries. Moreover, physico-mechanical rock properties were determined in the laboratory. Statistical regression models were built to quantitatively analyze the effect of individual rock property on the cutting rate and unit wear. Further, the principal component analysis (PCA) and best subset regression with Bayesian information criterion (BIC) were performed in order to determine the combined effect of most influential rock properties on sawability. Valid for all tested granites, the experimental results indicated that the tensile strength, abrasivity, and brittleness are the most influential rock properties for the prediction of stone cutting rate, whereas compressive strength, elasticity, and abrasivity are dominant for prediction of unit wear of diamond beads.

Forces and wear in high-speed machining of granite by circular sawing

In stone sawing process, the most adopted tool type is the circular diamond blade, whose duration and performance are influenced by various elements. These factors can be grouped into four categories: the mineralogical characteristics of the material to be machined; the working conditions, such as the depth of cut, the feed rate and the cutting speed; the production process of the diamond segment and the characteristics of both the matrix and the diamond, such as the size, the type and the concentration of the diamonds and the metal bonding formulation hardness. A key factor to increase productivity and reduce processing costs is cutting speed. In fact, the current trend is to adopt ever higher cutting speeds in order to reduce production times and costs.The purpose of this work is to evaluate over time the efficiency of the granite cutting process using diamond discs according to the cutting speed. The analysis was carried out for cutting speeds higher than the parameters conventionally used in the industrial field which is about 25 m/s. The efficiency of the processing was assessed by measuring the forces and wear of the tool according to the main process parameters for different working stages. In particular, the impact of working parameters modifications on the cutting operation of an ornamental stone was studied by experimental tests carried out on a CNC working centre equipped with a data acquisition system, suitable for the registration of all the three components of the cutting force.

Combining fuzzy RES with GA for predicting wear performance of circular diamond saw in hard rock cutting process

Predicting the wear performance of circular diamond saw in the process of sawing hard dimensional stone is an important step in reducing production costs in the stone sawing industry. In the present research work, the effective parameters on circular diamond saw wear are defined, and then the weight of each parameter is determined through adopting a fuzzy rock engineering system (Fuzzy RES) based on defining an accurate Gaussian pattern in fuzzy logic with analogous weighting. After this step, genetic algorithm (GA) is used to determine the levels of the four major variables and the amounts of the saw wear (output parameter) in the classification operation based on the fixed, dissimilar, and logarithmic spanning methods. Finally, a mathematical relationship is suggested for evaluation of the accuracy of the proposed models. The main contribution of our method is the novelty of combination of these methods in fuzzy RES. Before this work, all Fuzzy RESs only use simple membership functions and uniform spanning. Using GA for spanning and normal distribution as membership function based upon our latest work is the first work in fuzzy RES. To verify the selected proposed model, rock mechanics tests are conducted on nine hard stone samples, and the diamond saw wear is measured and compared with the proposed model. According to the results obtained, the proposed model exhibits acceptable capabilities in predicting the circular diamond saw wear.

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

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.

Study on the structure and properties of autoclaved aerated concrete produced with the stone-sawing mud

The mineral composition of the stone-sawing mud is mainly quartz, containing a small amount of sodium feldspar and potassium feldspar. It could be instead of river sand to be used for preparation of the autoclaved aerated concrete (AAC). The results showed that under the same condition, the porosity rate of the AAC with stone sawing mud and river sand was 73.3% and 74.6% respectively. The average pore size was 0.82 mm and 0.95 mm respectively. The AAC prepared with stone sawing mud and river sand have good thermal insulation performance with the thermal conductivity of 0.14 W/(m·K). As the amount of stone sawing mud replacing the river sand increased gradually, the bulk density and the compressive strength of the AAC were gradually increased. The X-ray diffraction (XRD) and scanning electron microscope (SEM) showed that the amount of hydrated products of the tobermorite and the calcium silicate hydrates (C-S-H) in the AAC with stone-sawing mud were more than that in the AAC with the river sand. The crystallization of tobermorite crystals in the AAC with the stone-sawing mud grew into a leaf shape, and interleaved with each other to form a dense structure net, which made the AAC with improved mechanical properties.

Application of metaheuristic algorithms to optimal clustering of sawing machine vibration

The sawing machine vibration is a major factor to evaluate and predict the sawing performance. A few increases in sawing machine vibration cause a significant increase in the maintenance cost, which is important, because it determines the production cost. Hence, the purpose of this study is to investigate the sawing machine vibration based on rock characteristics using stochastic techniques, namely genetic algorithm (GA) and differential evolution (DE). Additionally, 12 types of rocks, including Granite, Marble and Travertine were collected and studied and laboratory tests were conducted based on physical and mechanical properties for evaluating sawing machine vibration from Iranian quarries. The results showed that the applied metaheuristic algorithms such as stochastic approaches can be very suitable to classify the ornamental stone into 2 and 3 separate categories based on vibration level by only some important physical and mechanical properties including uniaxial compressive strength, Schmiazek F-abrasivity, Mohs hardness, and Young's modulus. Although, it has been found that there is no significant difference between the two algorithms, genetic algorithm modeling is more reliable than differential evolution based on the cost function. Finally, such studies can be used by engineers to optimize the ornamental stone sawing process.

Force and segment wear in various granites cutting by diamond frame saw

Influences of cutting parameters (feed rate, cutting length, and flywheel rotation speed) and stone properties (such as quartz content, uniaxial compression strength, and bending strength) on forces in various granites cutting by diamond frame saw (diamond gang saw) were studied. Feed rate ranks first in governing cutting force compared with flywheel rotation speed and cutting length. Uniaxial compression strength affects cutting forces most compared with other stone properties. The mathematical models can predict cutting forces for manufacturers and users, as well as provide a theoretical basis for improvement and optimization of stone sawing machines. Matrix tail can form during half-cycle sawing mode, which can improve the holding force of the bond to diamonds. Segments have better sawing conditions, and the main wear mode of diamond grits are whole and microfractured crystal. Slab productivity represents a 13–21 % increase, while geometrical deviation of the slab is less than 1.5 mm/m, thus reducing subsequent processing cost, such as polishing stage.

Design of a thin circular sawblade for natural stone sawing process

The existing crisis has accentuated problems related to the energetic perspective which forces the industrial framework to take actions. Natural stone companies are those more deteriorated by the crisis since they depend on the construction sector. While it is true that embedded energy in the natural stone industry includes extraction, transport and processing stages, the abrasive effect of sawing and polishing activities is responsible for the most energy consumption in stone manufacture. For this reason, improving sawing processes could have a major impact on the natural stone sector. This article presents a design of a new thinner diamond segmented circular sawblade for marble sawing, which reduces energy consumption during the sawing process. First of all, a multi-axis force measurement system was employed to determine the cutting conditions of a conventional diamond segmented circular sawblade under a pre-set configuration. Then, the research team defined a digital prototype of a commercial diamond segmented circular sawblade, and the data extracted from experimental measurements were used to configure the simulation. The simulation provided information about the mechanical performance experienced by the circular sawblade (such as stresses, displacements and eigenfrequencies). Subsequently, the geometry of that commercial circular sawblade was optimised seeking to reduce the moment of inertia while keeping the mechanical performance within safe and functional limits. At the end of the research, it was experimentally demonstrated that the new thinner circular sawblade designed reduces energy consumption during a sawing operation compared to the commercial circular sawblade.

A new frame saw machine by diamond segmented blade for cutting granite

An investigation has been undertaken into the stone processing machines. Diamond circular saws and diamond wire saws present some technological limits, and the marble frame saw cannot process granite by now. The present work shows an innovative frame saw machine to cut granite, the eccentric hinge guide mechanism is introduced into the machine. A sawing test and a simulation were carried out to analyze the sawing trajectory, the surface topography of the segments and the percentage of worn diamond particles. In addition, both cutting efficiency and slab flatness were recorded. The results show that the contact area between the blade and granite is not following a straight line, and the time required for stone sawing is only one half of the full sawing cycle. The eccentric hinge guide mechanism facilitates the formation of both matrix tails on the segments and a group of more new micro cutting edges, which improve diamond stability as well as self-sharpening. The proportion of micro-fractured and good diamonds in the new frame saw machine are 45% and 25%, respectively, and the productivity of the new machine is between 6 and 15m2/h. These values are significantly larger than that of the marble frame saw. Thus, the new prototype machine is suitable for sawing granite.

Estimation of the Ampere Consumption of Dimension Stone Sawing Machine Using of Artificial Neural Networks

Nowadays, estimating the ampere consumption and achieve to the optimum condition from the perspective of energy consumption is one of the most important steps to reduce the production costs. In this research it is tried to develop an accurate model for estimating the ampere consumption by using the artificial neural networks (ANN).In the first step, experimental studies were carried out on 7 carbonate rock samples in different conditions at particular feed rates (100, 200, 300and 400) and depth of cuts (15, 22, 30and 35mm) using a fully instrumented laboratory rig that is enable to change the machine parameters and measure the ampere consumption. In next step, a back propagation neural network was designed for modelling the sawing process for predicting the ampere consumption. The input network consisting of two parts: machine, work piece characteristics and the output of neural network was ampere consumption. This research evaluated the competencies of neural networks to estimate the ampere consumption in sawing process. The correlation coefficient between measured and predicted data in training and testing data is 0.95 and 0.97 respectively. The root mean square error (RMSE) for train and test data is 1.2 and 0.7 respectively. The results of this study showed that the ANNs can be used to estimate the ampere consumption with high ability and low error for industrial applications. Moreover, the cost of sawing machine ampere consumption can be accurately estimated using this neural model from some important physical and mechanical properties of rock.