Wear Behaviour of Hard Cr Coatings for Cold Forming Tools Under Dry Sliding Conditions

Cr hard coatings are largely used in industry in metal cutting and cold forming processes; This work on quantitative way represents improvement, in terms of wear resistance, which is obtained by depositing Cr hard coating on foundation material. Wear testing is done on tribometer with block –on –disc contact geometry at sliding contact of Cr hard coated sample with steel disc. Testing was performed in conditions without lubrication at variable value of contact parameters (normal load, sliding speed). Cr hard coatings in all contact conditions show smaller values of wear rate

Abrasive Wear Resistance of the Iron- and WC-based Hardfaced Coatings Evaluated with Scratch Test Method

Abrasive wear is one of the most common types of wear, which makesabrasive wear resistance very important in many industries. Thehard facing is considered as useful and economical way to improve theperformance of components submitted to severe abrasive wear conditions, with wide range of applicable filler materials. The abrasive wear resistance of the three different hardfaced coatings (two iron‐based and one WC‐based), which were intended to be used for reparation of the impact plates of the ventilation mill, was investigated and compared. Abrasive wear tests were carried‐out by using the scratch tester under the dry conditions. Three normal loads of 10, 50 and 100 N and the constant sliding speed of 4 mm/s were used. Scratch test was chosen as a relatively easy and quick test method. Wear mechanism analysis showed significant influence of the hardfaced coatings structure, which, along with hardness, has determined coatings abrasive wear resistance

Tribological behaviour of a356/sic nanocomposite

The paper presents tribological behaviour of aluminium nanocomposite A356/SiC produced by the compocasting process with mechanical alloying preprocessing (ball milling). Tribological tests were performed on tribometer with block-on-disc contact geometry under lubricated sliding conditions. Influence of amount of silicon carbide reinforcement (0, 0.2, 0.3 and 0.5 wt.%) on wear rate was investigated in the following testing conditions: sliding speed of 0.25 and 1.0 m/s, normal load of 40 N and 100 N and at sliding distance of 1000 m. Analysis of worn surface of nanocomposites was performed by using SEM equipped with EDS

Tribological Potential of Hybrid Composites Based on Zinc and Aluminium Alloys Reinforced with SiC and Graphite Particles

The paper reviews contemporary research in the area of hybrid composites based on zinc and aluminium alloys reinforced with SiC and graphite particles. Metal matrix composites (MMCs) based on ZA matrix are being increasingly applied as light-weight and wear resistant materials. Aluminium matrix composites with multiple reinforcements (hybrid AMCs)are finding increased applications because of improved mechanical and tribological properties and hence are better substitutes for single reinforced composites. The results of research show that the hybrid composites possess higher hardness, higher tensile strength, better wear resistance and lower coefficient of friction when compared to pure alloys

Tribological behaviour of a356/sic nanocomposite

The paper presents tribological behaviour of aluminium nanocomposite A356/SiC produced by the compocasting process with mechanical alloying preprocessing (ball milling). Tribological tests were performed on tribometer with block-on-disc contact geometry under lubricated sliding conditions. Influence of amount of silicon carbide reinforcement (0, 0.2, 0.3 and 0.5 wt.%) on wear rate was investigated in the following testing conditions: sliding speed of 0.25 and 1.0 m/s, normal load of 40 N and 100 N and at sliding distance of 1000 m. Analysis of worn surface of nanocomposites was performed by using SEM equipped with EDS

Nanoindentation of Za-27 Alloy Based Nanocomposites Reinforced with Al2O3 Particles

Nanoindentation has been widely used for material mechanical characterization. In this study, nanocompozite of ZA-27 alloy matrix reinforced with different volume fractions of nanometric Al2O3 ceramic particles ranging from 0 to 5 %, were produces using compocasting technique. Nanoindentation tests were performed using Berkovich three sided diamond pyramid, with maximum load of 100 mN and maximum load holding time of 15 s. Indentation imprints were investigated using optical and atomic force microscopy (AFM). Average particle size was 20-30 nm. Nanoindentation tests showed that nanocomposites have higher values of hardness and lower values of elastic modulus in comparison to the ZA-27 matrix alloy. Obtained results have different values in comparison to the theoretical investigations

Wear Properties of A356/10SiC/1Gr Hybrid Composites in Lubricated Sliding Conditions

This paper presents basic tribological properties of A356/10SiC/1Gr hybrid composites in conditions with lubrication. Hybrid composite specimen is obtained by compocasting procedure. A356 aluminium alloy is used as a base matrix alloy, reinforced with 10wt% of SiC and 1wt% of graphite. Tribological tests are done on advanced and computer supported tribometer with block‐on‐ disc contact pair. By the experimental plan, test is conducted under three different values of sliding speed, three different values of normal load, different sliding distances, and also different lubricants. SEM and EDS are used for wear analysis. The analysis has shown the presence of MML, which means that there was transfer of material from steel disc to composite block

AFM Surface Roughness and Topography Analysis of Lithium Disilicate Glass Ceramic

The aim of this study is presenting AFM analysis of surface roughness of Lithium disilicate glass ceramic (IPS e.max CAD) under different finishing procedure (techniques): polishing, glazing and grinding. Lithium disilicate glass ceramics is all-ceramic dental system which is characterized by high aesthetic quality and it can be freely said that properties of material provide all prosthetic requirements: function, biocompatibility and aesthetic. Experimental tests of surface roughness were investigated on 4 samples with dimensions: 18 mm length, 14 mm width and 12 mm height. Contact surfaces of three samples were treated with different finishing procedure (polishing, glazing and grinding), and the contact surface of the raw material is investigated as a fourth sample. Experimental measurements were done using the Atomic Force Microscopy (AFM) of NT-MDT manufacturers, in the contact mode. All obtained results of different prepared samples are presented in the form of specific roughness parameters (Rа, Rz, Rmax, Rq) and 3D surface topography

Application of Artificial Neural Network in Biotribological Research of Dental Glass Ceramic

A tribological system is a complex non-linear system composed of the elements that are connected structurally and functionally. The aim of this paper is to present an overview of artificial neural networks, its development and applications of neural networks in the prediction of tribological properties of dental glass ceramic using a newly measured ball-on-plate nanotribometer. The possibility of artificial neural networks application to solve complex nonlinear problems and to identify tribological characteristics of dental glass ceramic in terms of wear rate and coefficient of friction is presented

Modeling of Surface Roughness in Plasma Jet Cutting Process of Thick Structural Steel

Today highly competitive market and demands for obtain high surface finish and machining of complex shape geometries replace conventional machining processes with non-conventional. Plasma jet cutting is one of these non-conventional processes that primary uses a thermal energy of highly ionized gas to cut specified material and blow molten metal away. Main advantages of plasma jet cutting process are high speed of cutting, cutting different types of materials, the quality of cut and moderate to low investment costs. This paper presents experimental results concerning the surface roughness variation at plasma jet cutting of structural steel S235JRG2 plate thickness of 15 mm. Using the experimental data artificial neural network (ANN) model was developed in order to predict the surface roughness in terms of two input parameters, cutting current and cutting speed. After the prediction accuracy of the developed model was validated, the model was used for analyzing influence of input parameters on process response values