Machined Steel Surfaces Research Articles

The analysis of the measurement information on electrical discharge machined steel surfaces

The problem of studying the characteristics of the surface of heat-resistant steel samples after electrical discharge machining is considered as one of the most common and effective methods for manufacturing hard-to-machine parts, depending on the processing parameters. For the purposes of the study, samples were processed on an electrical discharge machine in various processing modes in accordance with a full-factorial experimental plan, which makes it possible to implement all possible combinations of processing parameters. To assess the state of the treated surface, the surface roughness of all obtained samples was measured in the longitudinal and transverse directions. The results of the analysis of the evaluation of the obtained surface roughness profi les are presented. The previously known conclusion that the average height of irregularities increases with increasing pulse current is confi rmed. It has been established that, along with this, the fractal dimension of the profi le also changes in the scale range of 20–500 μm, calculated on the basis of the “area – scale” function. A spectral analysis of microroughnesses based on the accumulated spectral power of the surface roughness profi le of steel samples was carried out, as a result of which it was shown that the main contribution to their formation is made by spatial frequencies in the range up to 0.05 μm–1. The results obtained will be useful in planning the modes of electrical discharge machining, depending on the functional purpose of the surfaces.

Performance evaluation of CNN-based crack detection for electrical discharge machined steel surfaces

Electrical discharge machining (EDM) is a non-traditional machining technique that is frequently employed on hard materials. In today's industrial practice, it has been the most prevalent non-traditional material removal procedure. It allows you to process challenging materials and construct complicated forms with excellent accuracy. In the context of image pre-processing approaches to discover defective or non-defective machining pieces through EDM, the Centre of attention of this article is utilizing convolutional neural networks (CNN) to create a machinery piece defective detection approach. A total of 180 datasets of varying sizes produced from public datasets, the proposed CNN model is assessed and compared to pre-trained networks, namely the VGG-16, VGG-19, ResNet-50, and ResNet-101 models. The assessment took into crack detection outcomes, and classification parameters such as accuracy, precision, recall, and F1-score. Also, we have given the receiver operating characteristic (ROC) curve, precision–recall curve, and confusion matrices for each model for the required classification to predict the defective cracks, and also, we included the histograms to find the probabilities of defective and non-defective cracks. The suggested model can discriminate between pictures that are cracked and those that are not. According to the findings, VGG-16 has the best accuracy out of all of these models. In comparison to prior conventional procedures, the proposed EDM crack defective detecting methodology gives great accuracy.VGG-16 attains 93% accuracy, 93% of F1-score, 94% of precision, 93% of recall, 93% of specificity, as well as 97% of AUC, testing findings suggest that our strategy is capable of incredible performances.

Determining the influence of ultra-dispersed aluminum nitride impurities on the structure and physical-mechanical properties of tool ceramics

This paper considers features related to manufacturing the chromium oxide-based tool material. The process involved ultra-dispersed powders made of aluminum nitride. It has been established that the destruction of chromium oxide at high sintering temperatures is prevented through the reaction sintering of chromium oxide (Cr2O3) and aluminum nitride (AlN). It was established that the structure of the composite depends both on the temperature and the duration of hot pressing. Thermodynamic calculations of the interaction between Cr2O3 and AlN showed that this interaction begins at a temperature of 1,300 °C. In contrast to hot pressing in the air, no СrN and Сr2N compounds were formed in a vacuum. With increasing temperature, the content of Al2O3 in solid solution becomes maximum at a temperature of 1,700 °C in the case of hot pressing in the air while in vacuum the content of Al2O3 remains unchanged within the entire temperature range of 1,300–1,700 °C. When increasing the time of hot pressing to 30 minutes, the size of individual grains reaches 10 μm. It has been shown that in the sintering process involving Cr2O3 and AlN, the plasma-chemical synthesis produces the solid solution (Cr, Al)2O3 at the interphase boundary, which improves the mechanical properties of the material. The influence exerted on the quality of the machined surface of tempered hard steel when machining by the devised tool material based on chromium oxide with an optimal admixture of 15 wt % of ultra-dispersed aluminum nitride powder was investigated. It was determined that the quality of the machined hard steel surface improved compared to standard imported tool plates. It was established that the resulting tool material, in addition to relatively high strength and crack resistance, also demonstrates high thermal conductivity, which favorably affects the quality of the machined steel surface, given that lubricants and coolants are not used during the cutting process.

Measurement and inspection of electrical discharge machined steel surfaces using deep neural networks

We propose an industrial measurement and inspection system for steel workpieces eroded by electrical discharge machining, which uses deep neural networks for surface roughness estimation and defect detection. Specifically, a convolutional neural network (CNN) is used as a regressor in order to obtain steel surface roughness and a CNN based on spatial pooling pyramid is applied for defect classification. In addition, a new method for the region of interest selection based on morphological reconstruction and mean shift filtering is proposed for defect detection and localization. The regressor and classifier based on deep neural networks proposed here outperform state-of-the-art methods using handcrafted feature extraction. We achieve a mean absolute percentage error of 7.32% on roughness estimation; on defect detection, our approach yields an accuracy of 97.26% and an area under the ROC curve metric of 99.09%.

Al2O3–V cutting tools for machining hardened stainless steel

The paper presents research results of dry cutting performance of alumina ceramic matrix composites with the addition of vanadium phase. The main criterion for the selection of metallic phase was the ability to create metal oxides phases during cutting process that are characterized with graphite-like structure. The study focuses on examining the formation of oxide layer which acts as a lubricant on the surface of the cutting edge and contributes to lowering the friction coefficient and thereby reduces the wear of the cutting tool during machining process. The article discusses the basic performance of produced composites such as Vickers hardness, Young modulus and fracture toughness. The dry machining test on 145 CR6 steel (hardness 50±2HRC) results are also analyzed including cutting tool life and roughness parameter Ra of machined steel surface. The article also compares cutting performance of produced composites with those of commercial ceramic cutting tools.

Investigation of Precipitated Hardening Layer Performance on Machined NAK80 Steel Surface

The surface integrity of NAK80 steel by grinding and electrical discharge machining (EDM) was studied in this paper. Microhardness, 3D topography and surface roughness of machined surface precipitation hardening layer were measured respectively. And the residual stress of the machined steel surface was measured with X-ray diffraction. Further experiments indicated that, compared with EDM, grinding method can obtain better surface integrity, and lower stress concentration sensitivity of NAK80 steel. But when machining the parts with complex shapes, EDM has the unparalleled advantages to grinding method.

Characterization of the Quasi-static Deformation of LAAG Joints Adhering Machined Steel Surfaces

Light Activated Adhesive Gripper (LAAG) workholding technology is a means by which a workpiece is held by adhesive joints that can be instantaneously cured or destroyed, on demand. A LAAG joint is the adhesive bond between the gripper pin and workpiece. Due to the novelty of this concept, no knowledge exists with regard to how LAAG joints deform and fail during quasi-static loading. This paper describes an investigation that was carried out to characterize the strength, ductility, and failure modes of a LAAG joint adhering a machined, steel surface subject to axial loading and shear loading.

Structure and properties of the cutting tools made from cemented carbides and cermets with the TiN + mono-, gradient- or multi(Ti, Al, Si)N + TiN nanocrystalline coatings

In work showed, that producing many and multiple layers of type TiN + mono- or gradient(Ti, Al, Si)N + TiN and TiN + multi(Ti, Al, Si)N + TiN in CAE (cathodic arc evaporations) process (method PVD) on tools produced from cemented carbides and cermets puts into port influences on enlargement of hardness of coatings, deciding about rise of property useful tools cutting off covered with coatings of system TiN + mono- or multi(Ti, Al, Si)N + TiN, in comparison with produced on these oneself parched tool materials, but not covered or covered with straight coatings. Microhardness of the deposited coatings were examined using the scratch test method. Results of the continuous machining of the C45E steel with the indexable and disposable inserts are presented along with the roughness test results of the machined steel surface. Metallographic examinations were made of the substrate structures and coatings on the electron microscope (TEM and SEM), as well as of the wear type resulting from machining tests.

Mirror Surface Properties of Steel Containing Free-Cutting Element in Electric Discharge Machining. Compositions and Microstructure of the Steel Containing Free-Cutting Element.

In this paper we describe the effect of die-sinking EDM under mirror finishing conditions on mirror surface properties of four-different types steel, SKD11, NAK55, PX5 and SKD61, which contain the free cutting element, sulfur. In particular, the influences of the quantity of sulfur on the machined steel surface, the composition and microstructure with die-sinking EDM. The following conclusions were obtained. 1) A mirror surface of steel containing more than 0.04% sulfur could not be realized. 2) In the case of steel with 0.1% sulfur, the surface property is dependent on the machining direction. 3) Pits are generated on the machined steel surface because the aggregated part of the MnS fiber preferentially melts with the circumferential base metal. In addition, the quantity and shape of pits change according to those of MnS. In the longitudinal section, the shape of the pit is a series of channels, whereas in the transverse section it is a cirele.

Fractal characterization and simulation of rough surfaces

Roughness measurements on a variety of machined steel surfaces and a textured magnetic thin-film disk have shown that their topographies are multiscale and random. The power spectrum of each of these surfaces follows a power law within the length scales considered. This spectral behavior implies that when the surface is repeatedly magnified, statistically similar images of the surface keep appearing. In this paper the fractal dimension is identified as an intrinsic property of such a multiscale structure and the Weierstrass-Mandelbrot (W-M) fractal function is used to introduce a new and simple method of roughness characterization. The power spectra of the stainless steel surface profiles coincide at high frequencies and correspond to a fractal dimension of 1.5. It is speculated that this coincidence occurs at small length scales because the surface remains unprocessed at such scales. Surface processing, such as grinding or lapping, reduces the power at lower frequencies up to a certain corner frequency, higher than which all surfaces behave as unprocessed ones. The W-M function is also used to simulate deterministically both brownian and non-brownian rough surfaces which exhibit statistical resemblance to real surfaces.

Macroscopic and microscopic phenomena of electro-discharge machined steel surfaces: An experimental investigation

Electro-discharge machining is a thermal process with a complex metal removal mechanism, involving the formation of a plasma channel between the tool and workpiece electrodes, melting and evaporation action and shock waves, resulting in phase changes, tensile residual stresses, cracking and metallurgical transformation. These properties determine the operational behaviour of machined parts and are included in the term “surface integrity”. Experimental results pertaining to the physico-chemical changes occurring during electro-discharge machining of steel (structural, medium-carbon and alloyed steels) surfaces are reported in this paper. Surface morphology and finish are assessed and correlated with overall process parameters and metal removal rates. Metallurgical transformations and new structures, surface damage in the form of cracking and “white layer” formation, microhardness variations and residual stress patterns are quantitatively and qualitatively examined and discussed. The results confirm the inherent complexity of the process, as well as the assumptions that must be made in order to achieve acceptable predictions of the mechanical and physico-chemical characteristics of the machined surfaces.

放電硬化面の超音波ハンマリング

Electrodischarge hardening or coating process being used to elongate steel tool life has a demerit of rough surface finish compared with its thin thickness.In order to get more smooth surface without removing its material ultrasonic hammering process is investigated.A diamond ball fixed on an ultrasonic vibrating tool was pressed onto the electrodischarge machined surface or the electrodischarge coated surface of the work on the vibrating table.Experiments were carried out under the following conditions: diamond ball diameter 5.6mm, ultrasonic frequency 22kHz, generator output power 100-300W (tool amplitude 13-24μm), pressing force 1-3kgf, feeding speed 60mm/min, work amplitude 4mm, work frequency 950cpm.Die steel works after EDM or electrodischarge coating were finished by the ultrasonic hammering. EPMA analysis, microhardness and roughness measurements result in the followings:1) Roughness of electrodis charge machined steel surface (initially Rmax 26μm) is smoothened by ultrasonic hammering (finally Rmax 3μm) and increases its hardness (in Hv 100-200).2) Surface layer generated by the electrodischarge coating consists of the two electrode materials.3) Electrodischarge coated steel surface with a cemented carbide electrode decreases its roughness from Rmax 18μm to 3μm and increases its hardness up to Hv 1300.4) In cutting-off of mild steel rod high speed steel lathe tool increases its life in 2 times after the electrodischarge coating and 2.6 times after the ultrasonic hammering of it.