Surface Quality Parameters Research Articles

Multi-objective Optimization of Process Parameters for Surface Quality and Geometric Tolerances of AlSi10Mg Samples Produced by Additive Manufacturing Method Using Taguchi-Based Gray Relational Analysis

AbstractIn this study, it has been focused on examining the effects of production parameters on quality parameters such as surface roughness and geometric tolerances in the production of AlSi10Mg samples by the additive manufacturing method. The experimental design has been prepared according to the Taguchi L27 orthogonal array. As a result, in the production of samples, increasing laser power (P) contributed positively to surface roughness and diameter change, and increasing scanning distance (SD) negatively contributed to circularity change and concentricity. Further, it has been determined that increasing the scanning speed (SS) negatively affects the concentricity change of the produced samples. The optimum production parameters for surface roughness and diameter variation has been determined as A1B1C3. The optimum production parameters for circularity variation and concentricity have been determined as A3B3C1 and A3B1C1, respectively. According to the ANOVA analysis results, the most effective parameters for surface roughness, diameter change, circularity change and concentricity have been 53.22% P, 62.45% SD, 37.23% SS and 40.41% SD, respectively. Furthermore, as a result of the gray relationship analysis (GRA) performed for the output parameters, the optimum production parameter has been determined as A2B1C3.

Efficient part orientation algorithm for additive manufacturing in industrial applications

Over the past few decades, the scientific community’s and industry’s interest in additive manufacturing technologies has surged. This technology is distinguished by the layer-by-layer deposition of the raw materials and the piece’s growth in a predetermined build orientation. This factor impacts the process’ overall cost, surface quality, and other crucial parameters. Numerous methods to solve competing aspects have been proposed in the literature, with the more promising that iteratively uses ray-tracing techniques. Existing algorithms iterate for each discrete element of the model’s bounding box projection onto the building platform. However, when optimisation algorithms are used on real-life industrial parts, computational time problems arise due to the high number of faces in the models. A new computational technique to determine the appropriate part orientation to reduce the support volume is proposed to address the problem. The method reduces the computational time, cycling the ray-tracing only on the triangles where the model surface is discretised. This approach has been integrated into an enhanced particle swarm optimisation algorithm to prove its efficiency. The approach is intended for industrial applications where it is necessary to handle complicated geometries quickly and efficiently to find the best orientation. Based on the computer’s resources and the complexity of the faceted model, a set of case studies with an industrial engineering significance is used to demonstrate the approach’s effectiveness.

High‐Dissolution Mechanism of Ti–48Al–2Cr–2Nb Alloy in Electrochemical Machining from a Nonlinear Dynamic Perspective

High‐rate dissolution process of Ti–48Al–2Cr–2Nb alloy in electrochemical machining exhibits strong nonlinear dynamic characteristics, but the quantitative relationship between these nonlinear characteristics and surface topography, as well as the electro‐dissolution mechanism, is unknown. Therefore, the fractal and recursive features of dissolution behavior and quantitative characterization of the dissolved surface topography were investigated. Additionally, an electro‐dissolution mechanism model in electrochemical machining process was presented. Applying a higher potential of 11 V can enhance the stability of the electrochemical system, resulting in a smoother and uniform surface. The saturation correlation dimension, surface roughness, and integral area of lacunarity initially decrease before increasing with higher electrolytic pressure, while laminarity and determinism show an initial increase followed by a decrease. These five characteristic parameters reach their optimal values at an electrolyte pressure of 0.4 MPa, indicating that achieving a stable and deterministic electrochemical system is crucial for obtaining a uniform smooth surface. These nonlinear dynamic characteristic parameters can be considered as in‐situ monitoring parameters for surface quality in ECM. The anodic dissolution process comprises three stages: initial passive film dissolution and breakdown, rapid dissolving with surface coarsening, and stable dissolving with polishing.

Impact of Cutting Data on Cutting Forces, Surface Roughness, and Chip Type in Order to Improve the Tool Operation Reliability in Sintered Cobalt Turning.

The authors present the results of laboratory tests analysing the impact of selected cutting data and tool geometry on surface quality, chip type and cutting forces in the process of orthogonal turning of sintered cobalt. The selected cutting data are cutting speed and feed rate. During the experiments, the cutting speed was varied in the range of vc = 50-200 m/min and the feed rate in the range of f = 0.077-0.173 mm/rev. In order to measure and acquire cutting force values, a measuring setup was assembled. It consisted of a Kistler 2825A-02 piezoelectric dynamometer with a single-position tool holder, a Kistler 5070 signal amplifier and a PC with DynoWare software (Version 2825A, Kistler Group, Winterthur, Switzerland)). The measured surface quality parameters were Ra and Rz. The components of the cutting forces obtained in the experiment varied depending on the feed rate and cutting speed. The obtained test results will make it possible to determine the optimal parameters for machining and tool geometry in order to reduce the machine operating time and increase the life of the cutting insert during the turning of sintered cobalt, which will contribute to sustainable technology.

Prediction of microbial activity and abundance using interpretable machine learning models in the hyporheic zone of effluent-dominated receiving rivers

Serving as a vital linkage between surface water and groundwater, the hyporheic zone (HZ) plays a fundamental role in improving water quality and maintaining ecological security. In arid or semi-arid areas, effluent discharge from wastewater treatment facilities could occupy a predominant proportion of the total base flow of receiving rivers. Nonetheless the relationship between microbial activity, abundance and environmental factors in the HZ of effluent-receiving rivers appear to be rarely addressed. In this study, a spatiotemporal field study was performed in two representative effluent-dominated receiving rivers in Xi'an, China. Land use data, physical and chemical water quality parameters of surface and subsurface water were used as predictive variables, while the microbial respiratory electron transport system activity (ETSA), the Chao1 and Shannon index of total microbial community, as well as the Chao1 and Shannon index of denitrifying bacteria community were used as response variables, while ETSA was used as response variables indicating ecological processes and Shannon and Chao1 were utilized as parameters indicating microbial diversity. Two machine learning models were utilized to provide evidence-based information on how environmental factors interact and drive microbial activity and abundance in the HZ at variable depths. The models with Chao1 and Shannon as response variables exhibited excellent predictive performances (R2: 0.754–0.81 and 0.783–0.839). Dissolved organic nitrogen (DON) was the most important factor affecting the microbial functions, and an obvious threshold value of ∼2 mg/L was observed. Credible predictions of models with Chao1 and Shannon index of denitrifying bacteria community as response variables were detected (R2: 0.484–0.624 and 0.567–0.638), with soluble reactive phosphorus (SRP) being the key influencing factor. Fe (Ⅱ) was favorable in predicting denitrifying bacteria community. The ESTA model highlighted the importance of total nitrogen in the ecological health monitoring in HZ. These findings provide novel insights in predicting microbial activity and abundance in highly-impacted areas such as the HZ of effluent-dominated receiving rivers.

Optimization of laser-texturing process parameters of Ti6Al4V alloys using metaheuristic algorithms

Manufacturing microscale textures can reduce friction and wear compared with smooth surfaces. In laser surface texturing, the resulting texture geometry is directly affected by laser parameters such as laser power, scanning speed and overlap rate. Therefore, finding the optimal parameter settings to improve the process performance is crucial. One of the biggest challenges encountered during the optimization stage is accurately determining the functional relationship between surface quality and process parameters. Another significant problem is solving the nonlinear equation system. This study aims to investigate the effect of laser-textured surfaces on the tribological behavior of titanium Ti6Al4V. Optimization of laser texture process parameters using metaheuristic algorithms is a hot topic. The first contribution of this study is the modeling of the contact angle, kurtosis and skewness quality parameters of Ti6Al4V titanium alloy based on the polynomial curve fitting method as a function of laser power, laser speed and overlap rate. Another significant contribution is to optimize the proposed nonlinear regression models using metaheuristic approaches such as genetic algorithm, particle swarm optimization, whale optimization algorithm, gray wolf optimization, equilibrium optimizer, teaching-learning-based optimization, student psychology-based optimization (SPBO), slime mould algorithm and social network search. The reason for using many metaheuristics is to test the effectiveness of different metaheuristic methods in solving this problem. Analysis of variance was performed to evaluate experimental data and compare the success of optimization methods. The results revealed that the proposed metaheuristic methods can be applied to the related problem. It has been observed that the methods give identical results. Among these methods, the SPBO method provided the best performance in the optimization of all laser output parameters.

Comparative Optimisation of the Cutting Parameters for Surface Quality and Energy Efficiency during the Machining Manufacturing of Teak, Saligna and Pine Wood Materials

Comparative Optimisation of the Cutting Parameters for Surface Quality and Energy Efficiency during the Machining Manufacturing of Teak, Saligna and Pine Wood Materials

DETERMINATION OF CONTAMINATION OF COOLANT WITH MECHANICAL IMPURITIES DURING GRINDING OF ROLLS OF ROLLING MILLS

Analytical studies have been carried out and a technology and means of coolant cleaning using various physical principles have been proposed. The structure has been developed and a mathematical model of an installation with several cleaners in series-parallel connection has been developed. Based on the mathematical model, analytical dependencies were created to calculate all the main cleaning characteristics. The results of the study make it possible to predict the required values of the quality parameters of ground surfaces and make optimal decisions on the appointment of rational parameters for cutting modes, replacement or dressing of the grinding wheel, cleaning or replacement of coolant.

Optimization, formation, and evolution of the photoinduced curing gradients and in-situ lamellar gaps in additive manufacturing of ZrO2 ceramics: From curing to sintering behaviors

The photoinduced curing gradients and in-situ lamellar gaps were related to the three-dimensional curing mechanism of stereolithography and researched in this work. Based on the photocuring mathematic theories presented by our team, photoinduced curing gradients were influenced by printing parameters such as laser power and frequency, scanning angle, and printing thickness. Among these curing gradients, the inadequate curing area was the main factor affecting the surface quality and physical properties of ceramics. The in-situ lamellar gaps were derived from the inadequate curing area. The lamellar gap size of green bodies was enlarged in brown bodies (sintering at 1170 ℃) and shrunk in sintered bodies (sintering at 1500 ℃). The correlations between the surface quality and printing parameters were clarified by establishing mathematical formulations of the lamellar gap size. Furthermore, anisotropic volume shrinkage, anisotropic surface topography, and density and hardness evolutions were associated with the wrapped particle density differences induced by the photoinduced curing gradients. Finally, the optimal printing parameters (75% of laser power, laser frequency of 150 kHz, scanning angle of 90º, printing thickness of 25 μm, and scanning speed of 2.5 m/s) were obtained by the orthogonal experimental analysis. This study provides a distinct understanding of the high-quality forming and extreme-performance manufacturing of stereolithography.

Multiobjective Optimization of Stereolithography for Dental Bridge Based on a Simple Shape Model Using Taguchi and Response Surface Methods

Stereolithography (SLA) has become an essential photocuring 3D printing process for producing parts of complex shapes from photosensitive resin exposed to UV light. The selection of the best printing parameters for good accuracy and surface quality can be further complicated by the geometric complexity of the models. This work introduces multiobjective optimization of SLA printing of 3D dental bridges based on simple CAD objects. The effect of the best combination of a low-cost resin 3D printer’s machine parameter settings, namely normal exposure time, bottom exposure time and bottom layers for less dimensional deviation and surface roughness, was studied. A multiobjective optimization method was utilized, combining the Taguchi method with response surface methodology and the desirability function technique. The predicted optimal values for the cube’s dimensional deviation and surface roughness were 0.0517 mm and 2.8079 µm, respectively. The experiments’ validation of the findings confirmed the results, which were determined to be 0.0560 and 0.064667 mm and 2.770 and 2.6431 µm for the dimensional deviation and surface roughness for the cube and bridge, respectively. The percentages of prediction errors between the predicted optimum results and the printed response were 7.68% and 1.36% for dimensional deviation and surface roughness, respectively. This study demonstrates that the robust method used produced a dental bridge with good accuracy and a smooth surface.

Экспериментальные исследования режимов скоростного шлифования рельсов

Introduction. Rails’ grinding in the conditions of a railway track is a priority for extending its life cycle due to the timely removal of tread surface defects and formation of required transverse profile. Today, 14 RSHP-48 rail grinding trains are used in Russia. At the same time, most rail grinding trains are ending its service life. Therefore, the development of a fundamentally new rail grinding train with increased efficiency is an urgent task. Siberian transport university is working together with the Kaluga plant “Remputmash” to create a new rail grinding train named RSHP 2.0. The rail grinding train RSHP 2.0 is based on the technology of high-speed rail grinding, which is based on increasing working speed of rail grinding train by increasing rotational speed of grinding wheels and setting the angle of attack. The aim of this work is to study rails’ grinding modes on a specially designed installation URSH, which implements the technology of high-speed grinding rails by increasing speed of grinding wheels rotation up to 5,000 rpm. Research methods. Grinding wheel speed control was carried out by IT-5-ChM “Termit” electronic tachometer and “Megeon 18005” laser tachometer. The angle of attack of grinding wheel was measured by digital, three-axis accelerometer-inclinometer ATst 90. The force of pressing grinding wheel to the rail was evaluated by strain-resistive sensors M50-0.5-C3. The measurement of head rail transverse profile before and after grinding and evaluation of metal removal were carried out by a PR-03 rail profiler. The width of grinding track was controlled by ShTsTs-I-300-0.01 caliper. The surface roughness of rail sample after machining was measured by TR 200 portable instrument. Results and discussion. Based on research results of CRS, the parameters of the working equipment of designed grinding rail train, which implements the technology of high-speed rail grinding, the influence of grinding modes on the formation of the quality parameters of the machined rail surface are established, and the optimal values of the forces of pressing the grinding wheel to the rail are determined.

INNOVATIVE METHODS OF MONITORING THE MECHANICAL PROCESSING PROCESS

The problem of ensuring the necessary quality and exploitation of the properties of machine parts is becoming more and more important in mechanical engineering. The main idea of the work consists in the development of a fundamentally new approach to the monitoring of a machine tool complex of mechanical processing, the essence of which is the organization of the method of controlling the mechanical processing process on the basis of a single integrated information environment adapted to the universal complex of computer modeling Matlab/Stateflow and Matlab/Simulink, with structural representations of all components of the mechanical processing process and modeling as a problem-solving tool that expands the functionality of machine tool complexes. However, until now, generalized theoretical relationships between surface quality parameters, processing accuracy, operational properties of parts and parameters of mechanical processing processes, which allow solving the problem of technological support of given operational properties of parts. Management of the process of forming a surface with the necessary properties is carried out mainly by using partial experimental dependencies and tables of processing modes. The complexity of the problem lies in the fact that when processing parts, it is necessary to establish such processing conditions that would provide a set of requirements for tool wear, processing accuracy, surface quality characteristics, productivity, etc. The areas of the most effective use of production systems are primarily determined by the technological equipment that is a component of the system, the nomenclature of processed parts and the automated control system. which allow to solve the problem of technological provision of given operational properties of parts.

MACHINING OF TOOTH PROFILES ON CNC MACHINES

Conventional methods of tooth machining using worm modular milling cutters, gear wheels and gear combs have common disadvantages - they require specialized equipment, are characterized by complex readjustment and relatively low productivity, which are eliminated in skiving. This paper views the possibilities for machining tooth profiles by means of skiving on CNC turning and milling machines. A new version of the kinematics of the process upon cutting inclined teeth has been implemented, where the feed is in the direction of the tooth, no correction in the angular speed is required and a skiving tool profiled according to the profile of the machined surface is used. Meshing of a tooth pair with crossed axes is reproduced. As a result of the crossing, slipping of the profiles occurs, which is the main cutting motion. The cutting speed, as a determining mode factor, can vary widely and depends on a number of design and technological parameters. Single-factor experiments have been conducted to determine the influence of the conditions of the implementation of the skiving process (the crossing angle of the tool axes and the workpiece, determining the magnitude of the cutting speed, and feed rate) on the quality parameters of the machined surfaces (tooth profile deviation, tooth direction deviation, accumulated pitch error, largest pitch difference and radial runout error) and the corresponding graphical dependencies have been constructed. A 7- 12 degree of accuracy of the machined tooth profiles has been ensured.

Application of a neural network for predicting cutting surface quality of punching processes based on tooling parameters

Punching represents one of the most frequently used manufacturing processes in the sheet metal processing industry. Thereby, one of the most important quality criteria for such punching processes constitutes the geometric shape of the cutting surface. High cutting surface qualities are usually characterized by the lowest possible edge draw in, a high clean cut, as well as a small fracture surface and a low burr height. In this respect, conventional punching processes can only produce clean cut proportions (CCP) up to 20-50% of the sheet thickness. By means of the so called “concave punch nose design” developed at the Institute for Metal Forming Technology, the geometry of conventional punches could be optimized in such a way that the clean-cut proportion along the cutting surface is significantly increased. The findings reported about in this paper show that the quality parameters of the sheared component edges thereby show highly nonlinear relationships to the tooling and sheet metal material parameters used. In order to quantify these effects, the data from several numerical punching simulations is used to pretrain an artificial neural network (ANN). Input data for the neural network included features of the punch geometry, the size of the clearance, the sheet thickness and the material data of the semi-finished product. The output of the neural network is precise predictions of the achievable cutting surface quality parameters. The experimentally validated findings presented in this paper show that the process design for novel punching processes such as cutting with concave punch nose design is possible, when using a modern machine learning approach.

Comparative Analysis of Finite Element Simulation and Experiment on the Polished Surface Quality of Hard Anodized Film of Aluminum Alloy

According to the abrasive morphology and distribution of sandpaper surface, the finite element model of hard anodic oxide film polishing was established by using ABAQUS finite element software, and the hard anodic oxide film and aluminum alloy matrix were defined respectively. The effects of hard anodic oxide film polishing process, polishing surface quality and polishing parameters on the polishing force were simulated. The polishing surface quality and polishing force simulated by finite element model were verified by experiments. The results show that in the polishing process, the residual stress of polishing surface is mainly distributed in the range of 0.0034mm, and the chips produced by polishing are mainly broken and long strips with microscopic morphology, and polishing mainly depends on the front part of abrasive particles in the feeding direction of sandpaper. Under the action of abrasive particles of sandpaper, the results of finite element simulation and test show that there are certain grooves on the surface of oxide film. The finite element simulation of the normal polishing force of hard anodic oxide film is consistent with the polishing test results. During the process of polishing hard anodic oxide film, the normal polishing force increases as the polishing speed increases; the normal polishing force increases as the polishing removal amount increases; the polishing removal amount parameter has a greater degree of influence on the polishing force.

Combined analysis of acoustic emission and vibration signals in monitoring tool wear, surface quality and chip formation when turning SCM440 steel using MQL

With modern production, Minimum Quantity Lubricant (MQL) technology has emerged as an alternative to conventional liquid cooling. The MQLs is an environmentally friendly lubricant method with low cost while meeting the requirements of machining conditions. In this study, the experimental and analytical results show that the obtained acoustic emission (AE) and vibration signal components can effectively monitor various circumstances in the SCM440 steel turning process with MQL, such as surface quality and chip formation as cutting tool conditions. The AE signals showed a significant response to the tool wear processes. In contrast, the vibration signal showed an excellent ability to reflect the surface roughness during turning with MQL. The chip formation process through the cutting mode parameters (cutting speed, feed and depth of cut) was detected through analysis amplitude of the vibration components Ax, Ay and Az and the AE signal. Finally, Gaussian process regression and adaptive neuro-fuzzy inference systems (GPR-ANFIS) algorithms were combined to predict the surface quality and tool wear parameters of the MQL turning process. Tool condition monitoring devices assist the operator in monitoring tool wear and surface quality limits, stopping the machine in case of imminent tool breakage or lower surface quality. With the unique combination of AE and vibration analysis model and the training and testing samples established by the experimental data, the corresponding average prediction accuracy is 97.57 %. The highest prediction error is not more than 3.8 %, with a confidence percentage of 98 %. The proposed model can be used in industry to predict surface roughness and wear of the tools directly during turning

EXPERIMENTAL ANALYSIS AND OPTIMIZATION OF THIN-WALLED TUBULAR PARTS MILLING

A certain percentage of mechanical parts in the engineering (parts in automotive industry, medical and measuring devices, parts in energetic sector, and etc.), refers to thin-walled structures with optimized shapes and dimensions. In addition to the requirements for a special shape of the structure, there are also requirements related to the dimensional accuracy and surface quality. In this paper, the milling of thin-walled tubular parts is analyzed. Workpiece of mentioned parts was C45E (AISI 1045) steel. Experimental analysis and optimization is based on Taguchi's experimental plan. The influence of cutting process parameters, depth of cut, feed per tooth and radial depth of cut, was analyzed. As the output cutting parameters, the dimensional accuracy and machined surface quality parameters, were measured and analyzed. Based on experimental data, modeling and optimization were performed. The obtained results defined the optimal input cutting process parameters, which give the best results in milling.

Numerical Simulation Analysis on Surface Quality of Aluminum Foam Sandwich Panel in Plastic Forming

The surface quality of an aluminum foam sandwich panel (AFSP) is very important for its appearance and application. This paper mainly studies the surface quality of AFSP after plastic forming. Combined with three-dimensional (3D) scanning technology, the normal deviation between the experimental AFSP and the target surface was obtained, and the surface quality parameters Sq, Sz and dmax were calculated to evaluate surface quality. The AFSP models with cubic-spherical (CS) and tetrakaidecahedral (TKD) as foam structures were established respectively. A series of numerical simulations of multi-point forming (MPF) were then carried out. Equivalent strain and deformation characteristics of spherical and saddle-shaped AFSP were discussed. The main surface defects produced by AFSP in plastic forming, such as surface wrinkle, the local straight face effect and surface dimpling were analyzed. Finally, MPF experiments were carried out, and it was found that the numerical simulation results were significantly corresponded to the experimental AFSP in terms of the degree and distribution of normal deviation and surface quality evaluation parameters. The TKD model was more consistent with the experimental results than the CS model. Moreover, the results show that the surface quality can be improved by thicker face sheets and smaller core cell sizes.

Technological Methods of Ensuring the Reliability of Lock Connections in Marine Gas Turbines

Abstract The article presents the test results of the surface quality parameters after broaching of heat-resistant steels of grades: 1.7335 (13CrMo4-5) and 1.4841 (X15CrNiSi25-20). The aim of the work is to determine the technological methods of obtaining the lowest treated surface roughness, surface layer hardening and the elimination of surface defects after broaching. To investigate the influence of cutting conditions (cutting speed, tool geometry and feed) on surface roughness and hardness, the physical modeling method of the broaching was used. As a result of the research, recommendations for improvement of the main parameters of the surface layer quality when broaching samples from selected grades of heat-resistant steels.

THE NEW IMPLEMENTATION METHODS MANAGEMENT MECHANICAL CUTTING AND VIBRO PROCESS

The problem of ensuring the required quality and operation of the properties of machine parts is becoming increasingly important in mechanical engineering. However, to date, no generalized theoretical relationships between surface quality parameters, machining accuracy, performance properties of parts and parameters of machining processes, which allow to solve the problem of technological support of the specified performance properties of parts. The control of the surface formation process with the required properties is carried out mainly by using partial experimental dependences and tables of processing modes. The complexity of the problem is that when machining parts it is necessary to establish such processing conditions that would provide a set of requirements for tool wear, machining accuracy, surface quality characteristics, productivity and more. Working machines of special and general purpose, their separate knots and mechanisms are constantly improved, thus increase of a technical level of machines is carried out by introduction of new technical decisions, use of modern technologies and scientific developments. The experience of development and operation of mechanisms of parallel kinematics confirms their high efficiency and prospects of this direction of mechanical engineering. Due to the design features of the layout, the mechanisms of parallel kinematics have closed kinematic chains that form spatial structures. As a rule, these structures are based on triangular rod systems. They have high rigidity characteristics, provide high speeds and acceleration of working bodies. Accordingly, these capabilities can significantly increase the static and dynamic accuracy of positioning mechanisms. The lack of theoretical foundations for the development of mechanisms, in particular high-precision mechanisms, hinders the widespread introduction of parallel kinematics mechanisms. Improving accuracy requires a comprehensive study of kinematics and work processes, taking place in their main nodes. Therefore, studies aimed at improving the parameters of static and dynamic accuracy of spatial mechanisms of parallel kinematics are relevant.