Surface Roughness Of Parts Research Articles

ИССЛЕДОВАНИЕ ВЛИЯНИЯ ГЕОМЕТРИЧЕСКИХ ПАРАМЕТРОВ АБРАЗИВНЫХ ЗЕРЕН ХОНИНГОВАЛЬНЫХ БРУСКОВ НА МИКРОГЕОМЕТРИЮ ПОВЕРХНОСТИ ДЕТАЛЕЙ

The static theory of honing has not been sufficiently developed, since the process of mass cutting with abrasive grains is random by its nature. This fact complicates the mathematical description of this phenomenon. The research aim was to develop a technique for modeling honing to calculate the process parameters, taking into account the elastic deformations of the abrasive tool. To solve the problems of statistical theory (analyzing the microgeometry of a machine part, metal removal and cutting forces), the studies involved probabilistic analysis and Monte Carlo simulation. Based on the distribution probability of abrasive grains over the cutting layer of the tool and the process kinematics, the law of distribution of the heights of part microroughnesses was determined. Using the distribution law, the authors found the parameters of the surface roughness of the part and the cutting process characteristics: the area of cuts, the number of contact grains, etc. A mathematical relationship has been established between the distribution of abrasive grains along the height and the distribution of the depth of scratches left by the tool on a polished sample. The geometric parameters of the cutting surface of diamond bars were determined taking into account their discrete model. Comparison of the calculated and experimental values of the bar parameters proved the correctness of the proposed methodology. Analytical dependences were obtained in general form for determining the parameters of the surface roughness of the machine part, the metal removal rate, cutting forces, cut areas, the number of contact grains, etc. The developed honing modeling technique helps determine the process parameters taking into account elastic deformations of the abrasive tool. Taking into account the characteristics of the bars, the average profile of the grains and the density of their distribution along the height, we can determine all the parameters of the machine part microgeometry. The results of the conducted probabilistic research are also applicable to other types of abrasive processing.

Optimization of single point incremental forming process through experimental investigation on SS 304 DDQ steel

Sheet Metal Single Point Incremental Forming (SPIF) is a flexible novel forming process to meet the growing demands of the manufacturing industry and the development of latest sheet metal based products. The SPIF process is used for rapid prototyping and sheet metal forming in batch production and is more economical than traditional stamping processes. The current study looks into the effects of process variables such as rpm, feeds, and step size on forming time, surface quality, and formed part thinning. Octagonal shape of part is formed from SS 304 DDQ steel sheet of 1 mm thickness. This process is performed by the CNC Vertical Machining Center (VMC). For this task, the fixture used for forming and tools with hemispherical edges are designed and manufactured. Experiments are performed based on design of experiments using orthogonal L9 arrays with Taguchi methods. The ideal process factors on response, such as forming time, surface roughness, and formed part thinning, were determined using analysis of variance (ANOVA). To determine the optimal level of process parameters, the signal-to-noise ratio (S/N) is used. The results show that step size has the greatest impact on forming time, followed by feed rate and a minimal effect from rotational speed. The feed rate has been found to have the greatest impact on the part's surface roughness, followed by speed and step size. Furthermore, the most important parameter that affects thinning of the created portion is step size, which is followed by rate of feedand spindlespeed in controlling overall variability.

Comparison of Two-Step Surface Treatment on Surface Roughness and Corrosion Resistance of Tc4 Alloy Parts Prepared by Slm and Sebm

Comparison of Two-Step Surface Treatment on Surface Roughness and Corrosion Resistance of Tc4 Alloy Parts Prepared by Slm and Sebm

Improvement of the Surface Roughness of a 3d Stereolithographic Part for a Molded Interconnect Device

Improvement of the Surface Roughness of a 3d Stereolithographic Part for a Molded Interconnect Device

Influence of different build orientation and laser scan strategies on surface quality, Mechanical and Material Characteristics of 18 Ni-300 maraging steel processed through DMLS

ABSTRACT Direct metal laser sintering (DMLS) is a method used to fabricate metal parts through laser sintering. In this research, experiments are designed to study how scanning patterns and build orientation affect the properties of printed maraging steel (MS1) parts. The mechanical and physical properties of DMLS manufactured parts depend primarily on the building direction and scanning strategies. Three different scanning patterns and build orientations were adopted in this research. Tensile, hardness, the surface roughness of DMLS parts were studied and almost entirely dense under different orientations and strategies and generally higher in horizontal orientation with cross-directional strategy because of thermal history variation. The Uniaxial tensile test findings exhibit that MS has significant anisotropic tensile characteristics, dependent on the specimen orientation and scan strategy. Despite the scanning strategy utilised, the vertical orientation produced the lowest mechanical performances of MS1 parts in terms of strength values recorded compared to all other orientations. Microstructural characterisation is carried out on a sample by using a scanning electron microscope (SEM) and optical microscope (OM) to analyse the fractured surface defects and pores, and X-ray diffraction (XRD) is used to determine the phase transformations. Understanding the impact of various build orientations in tensile, hardness, Surface quality shall enable the manufacturer to use the DMLS process to produce higher-quality MS1 parts.

Digital twin-driven surface roughness prediction and process parameter adaptive optimization

In the process of parts machining, the real-time state of equipment such as tool wear will change dynamically with the cutting process, and then affect the surface roughness of parts. The traditional process parameter optimization method is difficult to take into account the uncertain factors in the machining process, and cannot meet the requirements of real-time and predictability of process parameter optimization in intelligent manufacturing. To solve this problem, a digital twin-driven surface roughness prediction and process parameter adaptive optimization method is proposed. Firstly, a digital twin containing machining elements is constructed to monitor the machining process in real-time and serve as a data source for process parameter optimization; Then IPSO-GRNN (Improved Particle Swarm Optimization-Generalized Regression Neural Networks) prediction model is constructed to realize tool wear prediction and surface roughness prediction based on data; Finally, when the surface roughness predicted based on the real-time data fails to meet the processing requirements, the digital twin system will warn and perform adaptive optimization of cutting parameters based on the currently predicted tool wear. Through the development of a process-optimized digital twin system and a large number of cutting tests, the effectiveness and advancement of the method proposed in this paper are verified. The organic combination of real-time monitoring, accurate prediction, and optimization decision-making in the machining process is realized which solves the problem of inconsistency between quality and efficiency of the machining process.

Investigation on surface roughness of injection molded polypropylene parts with 3D optical metrology

Investigation on surface roughness of injection molded polypropylene parts with 3D optical metrology

Towards the Determination of Machining Allowances and Surface Roughness of 3D-Printed Parts Subjected to Abrasive Flow Machining

Abrasive flow machining (AFM) is considered as one of the best-suited techniques for surface finishing of laser powder bed fused (LPBF) parts. In order to determine the AFM-related allowances to be applied during the design of LPBF parts, a numerical tool allowing to predict the material removal and the surface roughness of these parts as a function of the AFM conditions is developed. This numerical tool is based on the use of a simplified viscoelastic non-Newtonian medium flow model and calibrated using specially designed artifacts containing four planar surfaces with different surface roughnesses to account for the build orientation dependence of the surface finish of LPBF parts. The model calibration allows the determination of the abrasive medium-polished part slip coefficient, the fluid relaxation time and the abrading (Preston) coefficient, as well as of the surface roughness evolution as a function of the material removal. For model validation, LPBF parts printed from the same material as the calibration artifacts, but having a relatively complex tubular geometry, were polished using the same abrasive medium. The average discrepancy between the calculated and experimental material removal and surface roughness values did not exceed 25%, which is deemed acceptable for real-case applications. A practical application of the numerical tool developed was demonstrated using the predicted AFM allowances for the generation of a compensated computer-aided design (CAD) model of the part to be printed.

Impact of inkjet printing parameters and environmental conditions on formation of 2D and 3D binder jetting geometries

While Binder Jet Additive Manufacturing (BJAM) has great potential, its implementation is limited by defects in the finished parts. An improved understanding of how printing parameters impact the quality of the printed parts is needed. Prior work on the droplet/powder interactions in BJAM printing focused on individual lines, this work shows that successful layer formation favors larger droplet spacing than is viable in individual lines. When printing layers, the first printed layer was significantly rougher than the spread bed indicating significant powder ejection. However, this difference was eliminated after printing 1–4 additional layers. These results show that prior printed layers have a strong impact on droplet impact and imbibition and that simple droplet or line geometries are not effective for testing printing parameters. The roughness of the first layer may contribute to large pores observed between layers. This paper further examines the impact of key printing parameters including layer thickness, droplet/line spacing, and droplet inter-arrival time on the effective saturation and surface roughness of 2D and 3D parts. The droplet inter-arrival time (print frequency) had negligible impact on surface roughness and saturation under the conditions tested. Printed layers behaved similarly at droplet spacing values comparable to the droplet diameter (44 μm). In contrast, droplet spacing of 60 μm, produced substantially lower saturation. Effective saturation generally increases with increased number of layers. Ambient humidity exposure during printing is shown to have a negligible impact on printing outcomes though higher moisture levels from steam exposure dramatically alter saturation. Drying powder before spreading reduced variation in the printed parts. All tests were based on gas atomized −22 μm 316 SS powder.

Dual-frequency ultrasonic cleaning with diluted phosphoric acid solution for removing oxide scale of uncoated steel sheets in hot stamping

Dual-frequency ultrasonic cleaning with a diluted phosphoric acid solution was developed to remove oxide scales on surfaces of hot-stamped parts from uncoated steel sheets, and conventional shot blasting processes are omitted. The removal of the oxide scale by ultrasonic cleaning is accelerated by the phosphoric acid solution and the dual frequency. The removing time for the phosphoric acid solution was shorter than that for a hydrochloric acid solution, and rust appearing for leaving after cleaning was prevented by generating an iron phosphate layer. In dual-frequency ultrasonic cleaning with the diluted phosphoric acid solution, the oxide scale was dissolved, and then the oxide scales were exfoliated from the thin scale and high-pressure portions. The removing time decreased with decreasing pH and oxide scale thickness and with increasing solution temperature. The surface roughness and distortion of an ultrasonic-cleaned hot-stamped part were smaller than those for shot blasting, and the weldability and paintability were similar. The oxide scale of a hot-stamped part having a nonuniform distribution of oxide scale thickness was successfully removed by dual-frequency ultrasonic cleaning with the diluted phosphoric acid solution.

On-machine non-contact roughness verification system based on Conoscopic holography

The surface quality verification of mechanical components is an essential activity in many applications where surface performance plays an important role in the functional behaviour of the part. Although many of the verification techniques commonly employed are based on the use of contact roughness profilometers, there are some limitations related to the morphological filtering effect associated to the stylus tip radius, as well as the difficulty in using these type of styli to carry out on-machine surface verification. The use of non-contact digitizing techniques helps to overcome some of these drawbacks, although the verification of surface quality using these non-contact systems still requires the development of scanning and data processing procedures similar to those described in the international standards for contact probing techniques. This work analyses the use of a non-contact sensor, based on Conoscopic Holography and integrated in a 3-axis machining centre, applied to the verification of the surface roughness of parts machined by face and cylindrical milling processes. After the calibration of the integrated system, a high-frequency noise filtering procedure specifically designed for roughness verification is proposed. The results demonstrate the feasibility of the system for verifying surface roughness grades from N5 to N12 in the two milling processes. Finally, specific filtering recommendations for each roughness grade of both milling processes as well as a surface verification procedure are provided.

Improving surface roughness of polylactic acid (PLA) products manufactured by 3D printing using a novel slurry impact technique

Purpose Fused deposition modeling (FDM) is one of the most adopted additive manufacturing techniques to produce prototypes and/or final parts regardless of geometrical complexity restrictions. One of the most challenging aspects of this technology is the attainable roughness. The purpose of this study is to evaluate the capability of the slurry impacts to improve the surface roughness of parts fabricated using FDM. Moreover, a regression model for predicting the values of surface roughness was developed. Design/methodology/approach The developed technique imposes a silica–water mixture which softens the staircase on the surface and leaves it smoother. The process introduces three main factors: building orientation; layer thickness; and impact angle of the slurry particles. Experimentally, a test rig was used to evaluate the effect of these factors on surface roughness. Statistically, Analysis of variance (ANOVA) and regression analysis were conducted to study the contribution of the individual factors on the roughness. Findings The results reveal that the effect of slurry impacts has a good impact on surface roughness, and the three factors have significant effect on surface roughness. Originality/value This paper contributes to new knowledge by providing a new technique for enhancing the surface roughness of FDMed products. ANOVA and regression analysis is a useful tool to parametrically study the surface roughness in terms of building and testing factors.

Influence of Part Orientation on the Surface Roughness in the Process of Fused Deposition Modeling

The article focused on the influence of part orientation on the surface roughness of cuboid parts during the process of fabricating by FDM technology. The components, in this case, is simple cuboid part with the dimensions 15 mm x 15mm x 30 mm. A geometrical model is defined that considers the shape of the material filaments after deposition, to define a theoretical roughness profile, for a certain print orientation angle. Five different print orientations in the X-axis of the cuboid part were set: 0°, 30°, 45°, 60°, and 90°. According to previous research in the field of FDM technology by the author, the internal structure (infill) was set at the value of 70%. The method of 3D printing was the Fused Deposition Modeling (FDM) and the material used in this research was thermoplastic ABS (Acrylonitrile butadiene styrene). For each setting, there were five specimens (twenty five prints in total). Prints were fabricated on a Zortrax M200 3D printer. After the 3D printing, the surface “A” was investigated by portable surface roughness tester Mitutoyo SJ-210. Surface roughness in the article is shown in the form of graphs (Fig.7). Results show increase in part roughness with increasing degree of part orientation. When the direction of applied layers on the measured surface was horizontal, significant improvement in surface roughness was observed. Findings in this paper can be taken into consideration when designing parts, as they can contribute in achieving lower surface roughness values.

Multi-objective process parameters optimization of SLM using the ensemble of metamodels

Selective laser melting (SLM) is one of the most common additive manufacturing (AM) technologies that shows great potential for intelligent and clean manufacturing. The process parameters involved in the SLM process have a significant impact on the part quality and energy consumption during the printing process. Since the relationships between the process parameters and various part quality characteristics cannot be expressed explicitly, it is impractical to decide the optimal process parameters intuitively. In this work, a hybrid multi-objective optimization approach by combining the ensemble of metamodels (EM) and non-dominated sorting genetic algorithm-II (NSGA-II) is proposed to generate optimal process parameters to improve the energy consumption, the tensile strength, and the surface roughness of the as-built parts. First, the Taguchi experiment design is adopted and the corresponding SLM experiments are conducted to obtain the experimental results. Second, the correlations between the process parameters (i.e., laser power, layer thickness, scanning speed) and the three responses are fitted using the proposed EM. The comparative results show that the prediction ability of the EM outperforms the stand-alone metamodels. Then, the NSGA-II is used to search for multi-objective Pareto optimal solutions based on the constructed EM. Finally, the verification experiments were conducted to verify the optimal results obtained by the proposed multi-objective optimization approach. Results indicate that the optimal process parameters are effective and reliable. Besides, the main effects of process parameters on the responses are analyzed. Overall, the proposed hybrid multi-objective optimization method exhibits great ability to improve the effectiveness of SLM.

Curved-layered material extrusion modeling for thin-walled parts by a 5-axis machine

PurposeThe purpose of this paper is to solve the problems of poor mechanical properties, high surface roughness and waste support materials of thin-walled parts fabricated by flat-layered additive manufacturing process.Design/methodology/approachThis paper proposes a curved-layered material extrusion modeling process with a five-axis motion mechanism. This process has advantages of the platform rotating, non-support printing and three-dimensional printing path. First, the authors present a curved-layered algorithm by offsetting the bottom surface into a series of conformal surfaces and a toolpath generation algorithm based on the geodesic distance field in each conformal surface. Second, they introduce a parallel five-axis printing machine consisting of a printing head fixed on a delta-type manipulator and a rotary platform on a spherical parallel machine.FindingsMechanical experiments show the failure force of the five-axis printed samples is 153% higher than that of the three-axis printed samples. Forming experiments show that the surface roughness significantly decreases from 42.09 to 18.31 µm, and in addition, the material consumption reduces by 42.90%. These data indicate the curved-layered algorithm and five-axis motion mechanism in this paper could effectively improve mechanical properties and the surface roughness of thin-walled parts, and realize non-support printing. These methods also have reference value for other additive manufacturing processes.Originality/valuePrevious researchers mostly focus on printing simple shapes such as arch or “T”-like shape. In contrast, this study sets out to explore the algorithm and benefits of modeling thin-walled parts by a five-axis machine. Several validated models would allow comparability in five-axis printing.

Impact of process variables on surface roughness in negative incremental forming process

A pivotal development of the obsolescence of conventional methods of sheet forming has enhanced the need of augmenting an agile and novel method of fabricating the tailored components according to the requirements of customers and users. Moreover, businessmen are interested to promote their businesses by manufacturing the tailored and customized parts of intricated and complex geometries at a lower cost and with negligible waste. Single Point Incremental Forming (SPIF), also known as “negative incremental forming”, avoids the direct use of any kind of specific die-sets and produces the user-ready parts. The investigation of the surface quality of the formed specimen is important to study the suitability of this process for industrial applications. This paper explores the effects of the interactions of tool radius and forming angle on the surface roughness of parts formed by the SPIF process. A full factorial approach was taken into account as DOE. The average roughness was found to rise with the rise in forming an angle. On the other hand, the increase in tool diameter resulted in the decrease of Ra value of formed components because the increase in the tool diameter allows the decrease in the waviness on the surface of the specimen. It was observed that the Ra value of formed components was decreased by 83.87% when the experimental condition was changed from the combination of higher levels of wall angle (68°) and lower level of tool diameter (7.52 mm) to the combination of lower levels of wall angle (60°) and a higher level of tool diameter (19.50 mm).

SURFACE ROUGHNESS MODELING DURING ELECTRIC DISCHARGE GRINDING WITH VARIABLE POLARITY OF ELECTRODES

The article presents the probabilistic-statistical modeling of surface roughness in the process of electric discharge grinding with the variable polarity of electrodes. The correlation between electric modes of machining and indicators of the quality of the machined surface was established. A probabilistic-statistical model of part surface roughness formed during grinding is obtained, which establishes the correlation between high-altitude surface parameters and electrical machining modes. The developed model makes it possible to calculate the height parameters of the part roughness depending on the electrical modes of grinding. The height of microroughness is determined by the same machining conditions as the depth of erosion pits. It is possible to obtain low roughness if electrical machining modes are reduced.

Surface roughness of PLA parts by FDM with chemical treatment

Chemical treatment can effectively reduce the surface roughness of fused deposition modeling (FDM) parts. An effort is made in this study to appraise the surface finish of poly lactic acid (PLA) parts by FDM with hot vapor smoothing treatment. The tests were designed as per the Taguchi L16 orthogonal array based factorial design of experimentation while varying process parameters such as time, temperature and solution concentration of hot vapor smoothing. The surface roughness of PLA parts after chemical treatment reduces in different degrees compared with FDM prototypes. The results of the statistical study indicate that the surface roughness is affected by treatment temperature. The optimum parameters that have been verified by performing the experiments may provide a theoretical basis for FDM parts in practical application.

Multi-Objective Optimization of Process Parameters to Enhance Efficiency in the Shoe-Type Centerless Grinding Operation for Internal Raceway of Ball Bearings

In this article, new research on the multi-objective optimization of the process parameters applied to enhance the efficiency in the shoe-type centerless grinding operation for the inner ring raceway of the ball bearing made from SUJ2 alloy steel is presented. The four important input parameters for this process, which included the normal feed rate of fine grinding (Snf), the speed of the workpiece (Vw), the cutting depth of fine grinding (af), and the number of ground parts (Np), were investigated. The aim of the study was to find the most appropriate value set of process parameters in order to, simultaneously minimize the grindstone wear (Gw), maximize the material removal rate (MRR) and the total number of ground parts in a grinding cycle (N’p), while guaranteeing other technology requirements such as surface roughness Ra ≤ 0.5 (µm), oval level Op ≤ 3 (µm), etc. In order to solve the problem, based on the experimental data, in which the grindstone wear was measured online by a measuring system consisting of two pneumatic probes, the optimization of the target functions of Gw, N’p, and MRR and mathematical models that express the dependencies of outcome parameters Gw, Ra, Op, MRR, etc. on the process parameters were determined. Therefore, a global optimal solution of such a discrete and nonlinear multi-objective optimization problem was solved by using a genetic algorithm, presenting the most appropriate process parameters as follows: Snf = 15.38 (µm/s), Vw = 6.00 (m/min), af = 11.76 (µm), and Np = 20 (parts/cycle). In addition, the impact of the four process parameters (Snf, Vw, af, Np) on the wear of the grinding wheel (Gw), the oval level of parts (Op), and the surface roughness of parts (Ra) was evaluated. The discovered technology mode has been applied to the real machining process for the inner ring raceway of the 6208_ball bearing made from SUJ2 alloy steel, and the outcome showed a much better result in comparison with default setting modes, while still ensuring the technology requirements. The difference between the predicted values and the real values of the parameters Gw, Ra, Op, and MRR were controlled within 5% of the ranges.

Use of machine learning algorithms for surface roughness prediction of printed parts in polyvinyl butyral via fused deposition modeling

Machine learning algorithms for classification are employed in this study to generate different models that can predict the surface roughness of parts manufactured from polyvinyl butyral by means of Fused Deposition Modeling (FDM). Five input variables are defined (layer height, print speed, number of perimeters, wall angle, and extruder temperature), and 16 parts are 3D printed, each with three different surfaces (48 surfaces in total). The print values used to print each part were defined by a fractionated orthogonal experimental design. Using a perthometer, the average value of surface roughness, Ra, on each surface was obtained. From these experimental values, 40 models were trained and validated. The model with the best prediction results was the one generated by bagging and Multilayer Perceptron (BMLP), with a Kappa statistic of 0.9143. The input variables with the highest influence on the surface finish are the wall angle and the layer height.