S. Turchetta

Cutting Force in Stone Machining by Diamond Disk

Stone machining by diamond disk is a widespread process to manufacture standard products, such as tiles, slabs, and kerbs. Cutting force and energy may be used to monitor stone machining. Empirical models are required to guide the selection of cutting conditions. In this paper, the effects of cutting conditions on cutting force and cutting energy are related to the shape of the idealized chip thickness. The empirical models developed in this paper can be used to predict the variation of the cutting energy. Therefore these models can be used to guide the selection of cutting conditions. The chip generation and removal process has been quantified with the intention of assisting both the toolmaker and the stonemason in optimising the tool composition and cutting process parameters, respectively.

Cutting force, tool life and surface integrity in milling of titanium alloy Ti-6Al-4V with coated carbide tools

Titanium alloys are widely used in aeronautics that demands a good combination of high strength, good corrosion resistance and low mass. The mechanical properties lead to challenges in machining operations, such as high process temperature as well as rapidly increasing tool wear. In this work, three carbide end mills have been used in machining of titanium alloy Ti-6Al-4V. The first tool is coated with TiAl; the second and the third are coated with multi-layers or with a single layer of TiAlN. The cutting force and the tool life have been experimentally investigated and put into relationship with the process parameters under dry cutting condition. The quality of the machined surfaces has been evaluated by measuring the roughness of the machined surfaces. Finally, the correlation among cutting force variation, tool wear propagation and surface roughness has been analyzed and discussed. These three tools demonstrate to be able to maintain their hardness and other mechanical properties at the high cutting temperatures that they encountered.

Wear progression of diamond mills

The increasing request, both in industrial field and in urbanistic furniture, of complex-shaped products in natural stone makes necessary the use of flexible and completely automatic machines, such as NC machining centres. These machines mainly use versatile tools such as synthesised diamond mills. The aim of this work is to characterise the wear of the diamond mills by variables that are easy to measure, and effective to describe wear mechanism. An optic microscope and an electronic balance have allowed both to observe the mill shape and to measure the diameter and weight changes of the mill after consecutive machining steps. An original test protocol has been developed to carry out all experimental tests. The results show how a set of variables, that are related to the macro-geometry of the diamond mill and are called macro-geometric wear variables, may be used to foresee the tool wear in a synergic way and, therefore, to improve usage of the tool.

To characterise diamond mill wear

This work shows two alternative methods to characterise diamond tool wear. The macro-geometric method involves readily measurable variables and, therefore, it requires little time. However, it allows only a partial understanding of the phenomena involved in tool wear. The micro-geometric method implies a deeper understanding of mechanical and tribological mechanisms involved in tool wear and, therefore, it requires a longer time. An optical microscope, a SEM and an electronic balance allowed the observation of the mill and diamond grit shape, and the measurement of the relevant variables. Test protocols are used to implement both the methods. The results show that two sets of quantitative variables may be used to predict the tool wear in a synergic way and, therefore, improve the tool use.

An automatic visual system for marble tile classification

Abstract The international market of ornamental stone has seen the use of materials quarrying from East Europe, Africa, Asia and South America, characterized by a low cost of labour. This event has embittered the competition in this field. Hence, it becomes fundamental to produce machined products of high quality in a more efficient way. This work aims to design and fulfil a prototype to automatically classify the Royal Perlato tiles of Coreno. It is based on artificial vision. The implemented hardware visual system is cheap because it is made up of components readily available and is easily obtainable by small and medium ornamental stone businesses. The developed software algorithm is based on a multifactor analysis of variance and a quadratic discriminant analysis. The experimental results show that the developed hardware and software system permits all the tiles of Royal Perlato of Coreno to be classified properly. Moreover, the developed system not only improves the efficiency of the selection but also reduces the controversies between the manufacturer and buyer, making tile classification more selective and increasing the number of qualitative classes taken into consideration. Finally, it allows the duplication on the selection line without altering data dispersion.

Monitoring of Diamond Mill Wear in Time Domain during Stone Cutting Using Cutting Force Measurements

The main focus of this study is to verify the possibility to monitor diamond mill wear by measuring the cutting force during stone machining. An ornamental stone was machined on an NC machining centre, retrofitted with a 3-axis dynamometer and data acquisition systems, to investigate the effects of variations in machining parameters. The sensor data include cutting force measurements, further divided into measurable components, such as x, y, and z. Those components were analysed to determine the sensory features that best correlate with diamond mill wear. Tool wear and machining parameters appeared significantly influencing cutting force signals. This suggests that even under the varying cutting conditions involving different values of process parameters, the identified cutting force feature can be used for the reliable and accurate control of diamond mill wear during stone cutting operations.

Investigation on Stone Machining Performance Using Force and Specific Energy

Cutting force and energy are often used as parameters for monitoring the stone cutting process. Empirical models are required to guide the selection of the cutting conditions. This paper shows a simple empirical model to predict the variation of the cutting energy. It puts into relationship the cutting force and the cutting energy with the idealized chip thickness. It has been tested on six different kinds of stone. The models can be used to guide the selection of cutting conditions. The chip generation and removal process has been quantified with the intention of assisting both the toolmaker and the stonemason in optimizing the tool composition and cutting process parameters, respectively.