Turning inserts the selection approach based on fuzzy comprehensive evaluation

Tool selection is a multi-criteria decision-making problem in the presence of various selection criteria and a set of alternatives, but previous works are limited to evaluating the tools within the workshop tool library. To intelligently select proper inserts across suppliers under the Internet environment, an insert data format based on ISO 513 was established, and a framework was then designed to obtain a set of alternatives from different suppliers based on fuzzy intervals. Then, knowledge was described with convenient language and the simple membership function to build an intelligent system, which would infer the matching degree of insert characteristics to the machining conditions. Furthermore, analytic hierarchy process was applied to sort the alternatives. Finally, the case study shows that compared with previous works and machinists, this work not only obtains a set of alternatives from all suppliers who uploaded their product data with the designed format but comprehensively evaluates the insert (take finishing low-carbon steel as an example, both cemented carbide and cermet are recommended, the nose radius reduces 25%, the environmental index increases 25%, while the rake reduces 11.25%, when compared with machinists who tend to select the larger rake angle foe finishing). A platform was also developed based on Visual Studio 2015 and SQL Server 2012 to improve selection efficiency for inexperienced CNC operators, purchasers, and vendors.

OPTIMIZATION OF PROCESS PARAMETERS AFFECTING CUTTING FORCE, POWER CONSUMPTION AND SURFACE ROUGHNESS USING TAGUCHI-BASED GRAY RELATIONAL ANALYSIS IN TURNING AISI 1040 STEEL

This study focuses on optimization of cutting conditions and modeling of cutting force ([Formula: see text]), power consumption ([Formula: see text]), and surface roughness ([Formula: see text]) in machining AISI 1040 steel using cutting tools with 0.4[Formula: see text]mm and 0.8[Formula: see text]mm nose radius. The turning experiments have been performed in CNC turning machining at three different cutting speeds [Formula: see text] (150, 210 and 270[Formula: see text]m/min), three different feed rates [Formula: see text] (0.12 0.18 and 0.24[Formula: see text]mm/rev), and constant depth of cut (1[Formula: see text]mm) according to Taguchi L18 orthogonal array. Kistler 9257A type dynamometer and equipment’s have been used in measuring the main cutting force ([Formula: see text]) in turning experiments. Taguchi-based gray relational analysis (GRA) was also applied to simultaneously optimize the output parameters ([Formula: see text], [Formula: see text] and [Formula: see text]). Moreover, analysis of variance (ANOVA) has been performed to determine the effect levels of the turning parameters on [Formula: see text], [Formula: see text] and [Formula: see text]. Then, the mathematical models for the output parameters ([Formula: see text], [Formula: see text] and [Formula: see text]) have been developed using linear and quadratic regression models. The analysis results indicate that the feed rate is the most important factor affecting [Formula: see text] and [Formula: see text], whereas the cutting speed is the most important factor affecting [Formula: see text]. Moreover, the validation tests indicate that the system optimization for the output parameters ([Formula: see text], [Formula: see text] and [Formula: see text]) is successfully completed with the Taguchi method at a significance level of 95%.

Mechanistic modeling of cutting forces in high-speed microturning of titanium alloy with consideration of nose radius

Microturning is a micromechanical machining process used to produce microcylindrical or axially symmetrical parts. Microcylindrical parts are mainly used in microfluidic systems, intravenous micromotors, microsurgical applications, optical lens applications, and microinjection systems. The workpiece diameter is very small in microturning and therefore is greatly affected by the cutting forces. For this reason, it is important to predict the cutting forces when machining miniature parts. In this study, an analytical mechanistic model of microturning is used to predict the cutting forces considering the tool nose radius. In the semi-empirically developed mechanistic model, the tool radius was considered. A series of semi-orthogonal microturning cutting tests were carried out to determine the cutting and edge force coefficients. The mechanistic model was generalized depending on the cutting speed and depth of cut by performing multilinear regression analysis. In the study, the depth of cut (ap = 30–90 µm) and feed values (f = 0.5–20 µm/rev) were selected considering the nose radius and edge radius of the cutting tool. The experiments were carried out under high-cutting speeds (Vc = 150–500 m/min) and microcutting conditions. Ti6Al4V alloy was used as the workpiece material and the tests were carried out under dry cutting conditions. Validation tests for different cutting parameters were carried out to validate the accuracy of the developed mechanistic model. The results showed that the difference between the mechanistic model and the experimental data was a minimum of 3% and a maximum of 24%. The maximum difference between the experimental and the model usually occurs in forces in the tangential direction. It has been observed that the developed model gives accurate results even at a depth of cut smaller than the nose radius and at feed values smaller than the edge radius.

A Systematic Study on the Effects of Process Parameters on Spinning of Thin-Walled Curved Surface Parts With 2195 Al-Li Alloy Tailor Welded Blanks Produced by FSW

The manufacturing process is inevitably accompanied with the production of scraps, which leads to resource waste and environmental pollution. Recycling and remanufacturing are the most commonly used approaches for metal scraps due to their well-established advantages from economic and environmental perspectives. In this study, spinning experiments with 2195 Al-Li alloy tailor welded blanks produced by friction stir welding from metal scraps were conducted under different process parameter designs. And then the effects of various process parameters on spinning of thin-walled curved surface parts were systematically studied. The results of the corresponding experimental groups show that the roller attack angle, the spinning clearance, and the installation method of tailor welded blanks have the most significant effect on the weld torsion angle. In addition, it was found that along the longitude direction of spun parts, the surface roughnesses of the weld of spun parts were greatly improved under the roller nose radius of 10 mm, the spinning clearance of 1.0 mm, the constant linear velocity, and the installation method of tailor welded blanks (the lower surface of tailor welded blanks is spun by rollers), while the process parameters have little significant effect on the surface roughness along the latitude direction of spun parts. Furthermore, it can be concluded that the forming profiles of spun parts fitted the mandrel well under the roller nose radius of 6 mm, double rollers, the roller attack angle of 30° and 45°, spinning clearance of 1.5 mm, and the installation method of tailor welded blanks (the upper surface of tailor welded blanks is spun by rollers). The research results will provide guidance for the precise spinning of thin-walled curved surface parts with tailor welded blanks. Thereby, it is also beneficial for green manufacturing involving recycling and remanufacturing of metal scraps.

Numerical simulation of the influence of tool geometry on energy consumption during micro turning of titanium alloy

Fabrication of an axisymmetric biomedical implant with good dimensions, form and surface integrity features are a challenging task in the micro-manufacturing industry. This is due to workpiece deflection, vibrations, tool wear and adhesion of the chip on the cutting inset during the micromachining process. So experimental evaluation on the variation of tool geometry is expensive and difficult as stated in prior literature. So, in this work, a finite-element method simulation is developed to comprehend the physics of the process and predict the energy consumption by incorporating the effect of material strengthening caused by shearing of material across the grain, shear band pattern upon strain rate and tool geometry such as edge radius, nose radius and rake angle. The modified Johnson-Cook material model is used to state the flow stress and an adaptive remeshing technique is utilized to model the plastic deformation at a higher strain rate during the simulation process. Initially, the model is developed in a transient state and then modified to a steady-state to obtain the output process parameters. The proposed model is calibrated and validated with experimental results reported in the literature. It is inferred that the cutting force, thrust force and feed force acquired from finite-element method simulation have been confirmed experimentally with prediction accuracy of 94%, 82.66% and 87.02%, respectively. It is also inferred that energy consumption during machining reduces with an increase in rake angle because of the sharpness of the cutting edge and less friction between tool and chip. An increase of nose radius and edge radius produces high thrust force and energy consumption and impedes high radial depth of cut. For the same machining parameters with the increase of edge radius and decrease of rake angle the mechanism of material removal changes from shearing to ploughing.

Evaluation of: MOSSA, MOALO, MOVO and MOGWO Algorithms in Green Machining for High Production Performance in Turning of X210Cr12 Steel

The current study investigates the Wet and MQL machining, when turning of X210Cr12 steel, using a multilayer-coated carbide insert (GC-4215) with various nose radius, the consideration of the tool geometry with different cooling modes allow as to assess the comportment of the machined steel against the cutting combinations. The response surface methodology (RSM) has been used for regression analysis and to evaluate the contribution of the cutting parameters on surface roughness, tangential force and cutting power using ANOVA analysis. The developed models have been used to predict the studied output factors according to the selected cutting parameters for wet and MQL machining. A comparative between the cooling techniques have been established to determine the most effective technique in terms of part quality, lubricant consumption and power consumption. Finally, four new optimization technics have been used for the process optimization using the MQL models for an environment-friendly machining.

Roller Design and Optimization Based on RSM with Categoric Factors in Power Spinning of Ni-Based Superalloy

Power spinning is a single point high pressure forming process which is usually studied with ideal regular billet. However, in some cases, the billet adopted in this process is from conventional spinning process with non-uniform wall thickness and springback. Therefore, the forming accuracy is low because this unpredictable spun billet. In this paper, cone, step and arc rollers are compared and the length change of deformation zone is calculated to further understand the forming mechanism of different roller shapes. Multi-step process simulation considering conventional spinning and power spinning is established. The influence of roller parameters such as roller nose radius, straightening zone in step roller and bite angle on the maximum roller force are discussed. In addition, the continuous factors such as installation angle and discrete factor roller shape are studied based on the response surface method (RSM) with categoric factors. The results show that roller shape have a big influence on the workpiece forming quality in power spinning process. Step roller is more suitable for use in this work. The roller nose radius and installation angle have great impacts on the maximum roller force.

Parameter Selection to Ensure Multi-Criteria Optimization of the Taguchi Method Combined with the Data Envelopment Analysis-based Ranking Method when Milling SCM440 Steel

SCM440 steel is a commonly used material for making plastic injection molds and components such as gears, transmission shafts, rolling pins, etc. Surface roughness has a direct influence on the workability and durability of the parts and/or components, while the Material Removal Rate (MRR) is a parameter that is used to evaluate the productivity of the machining process. Furnished products with small surface roughness and large MRR is the desired result by all milling processes. In this paper, the determination of the values of input parameters is studied in order to ensure that during the process of milling SCM440 steel, it will have the smallest surface roughness and the largest MRR. There are five parameters that are required to be determined, namely the cutting insert material, the tool nose radius, the cutting speed, the feed rate, and the cutting depth. The Taguchi method was applied to design the experimental matrix with a total of 27 experiments. Result analysis determined the influence of the input parameters on surface roughness and MRR. The Data Envelopment Analysis-based Ranking (DEAR) method was applied to determine the optimal value of the input parameters, which were used to conduct the milling experiments to re-evaluate their suitability.

Mapping Ductile-To-Fragile Transition And The Effect of Tool Nose Radius In Diamond Turning of Single-Crystal Silicon

Although it has long been known that tools with more negative rake angles allow the ductile regime to be achieved when machining monocrystalline silicon; little has been discussed about the tool-material interaction in terms of the microgeometric contact of the tool tip at this interface. In this paper, the tool rake angle was varied in order to change the undeformed chip thickness value once the tool cutting radius, formed in front of the tool rake face, changes when the tool rake angle becomes more negative. Based on the statistical design of the experiment applied to cutting tests, a map relating values of transition pressure and different crystallographic directions is built to assist in determining machining conditions with a ductile response within a wider spectrum based on tool rake angle under different machining conditions. The results obtained allowed to answer questions under which machining conditions and tool geometry account for better surface finishes, lower machining forces, and lower residual stresses. The response surfaces generated provided answers capable of establishing under which cutting radii yielded more ductile mode material removal and avoided a brittle response, related to anisotropic response due to change in the crystallographic direction. Finally, we used the brittle-to-ductile transition map to determine a more suitable machining condition to diamond turn Fresnel lenses in single crystal silicon.

INVESTIGATION OF WIPER INSERTS EFFECTS IN TURNING AND MILLING PROCESSES

The surface roughness is a crucial factor in machining methods. The most effective factors on surface roughness are feed rate and tool nose radius. Due to the many advantages of wiper (multi-nose radius) inserts, their importance and use has been increasing recently. The purpose of this paper is to investigate the effect of wiper inserts on surface roughness and tool wear. In this study, conventional inserts and wiper inserts were experimentally compared separately in milling and turning operations. Compared to conventional inserts, the surface roughness values obtained using wiper inserts improved by 33% in turning operations and approximately 40% in milling operations. It was observed that the production time in the turning process was reduced by about 25% in the case of using wiper inserts compared to the use of conventional inserts. In milling, this ratio was determined to be approximately 43% due to the fact that it has multiple cutting edge. It has been observed that the use of wiper inserts in machining methods creates a significant time and cost saving advantage.