Deformable 3D Research Articles

FEM Simulation on First-Step Drawing Process of Platinum-Clad Nickel Bars

The purpose of this study is to investigate the effects of semi-angle and platinum tube wall thicknesses on the first-step drawing process of platinum-clad nickel bars using finite element simulation. Three different semi-angles of die (3°, 5°, 7°) and three different platinum tube wall thicknesses (0.275 mm, 0.3 mm, 0.325 mm) were selected in the study. The effects of semi-angle and platinum tube wall thicknesses on drawing force, equivalent stress, cladding behavior and damage coefficients during the first-step drawing process were discussed in detail. The simulated results of cladding condition and damage obtained from Deform 3D V11 software are validated with experimental results, and it was found that the results were in good agreement. The results of this study may provide a reference for the practical production of platinum-clad nickel wires.

Multi‐Material 3D Microprinting of Magnetically Deformable Biocompatible Structures

AbstractTwo‐photon polymerization (2PP) allows precise 3D printing at the micrometer scale, and by associating it with magnetic materials, the creation of remotely actuatable micro‐structures. Such structures attract a growing interest for biomedical applications, thanks to their size and to the biocompatibility of some photoresist materials. Gelatin methacryloyl (Gel‐MA) is one such material, and can be used to create physiological scaffolds for cell culture. Here, the physico‐chemical properties of two resins are exploited, the first being a silica‐based hybrid polymer, the OrmoComp, and the second a Gel‐MA‐based hydrogel. A 2PP manufacturing protocol is defined and designed to print both materials in succession as a single structure, which is then linked to a neodymium‐iron‐boron (NdFeB) magnetic bead for actuation. By this combination, a magnetically deformable 3D culture substrate is created to study cells in an environment that mimics soft, curved, and dynamic properties of tissues in vivo. The structure is actuated via an external magnetic field and bends back and forth along its longest axis. Lastly, preliminary cell culture trials are conducted showing the proliferation of cells on the structures.

Modified Arrhenius constitutive model and simulation verification of 2A12-T4 aluminum alloy during hot compression

An accurate constitutive model is imperative to describe the deformation behavior of aluminum alloy in numerical simulation of thermal plastic forming process. In this study, isothermal uniaxial compressions of 2A12-T4 aluminum alloy were conducted by Gleeble-3500 thermal-mechanical simulator under the temperature of 300–450 °C and strain rate of 0.01–10 s−1. Three different Arrhenius constitutive models, including strain compensation (SC), genetic algorithm (GA) and K-function modification (KM), were established basing on the double correction of the true stress–strain curve by considering the effect of temperature variation and interfacial friction. The prediction accuracy of three models were assessed by the correlation coefficient (R), average absolute relative error (AARE) and the logarithm of the mean square error (ln (MSE)). The results show that the newly KM constitutive model considering the coupling effect of temperature and strain rate showed excellent agreement with the experimental data and best prediction capability with lowest error. Hot processing map based on the Murty-Rao criterion shows that high temperature and low strain rate is suitable for stable forming. In order to verify the reliability of the proposed model in numerical simulation, the established KM Arrhenius constitutive equation is secondarily developed in DEFORM 3D software and used in the hot compression process under the stable forming conditions obtained from hot processing map. The simulated force–displacement curves and maximum load values under forming conditions were well match with the experiment trends, which proved the reliability of the KM constitutive equation in the finite element numerical simulation.

Optimization of the First-Step Drawing Parameters for Platinum-Clad Nickel Bar Based on FEM Simulation

The first-step drawing process of the platinum-clad nickel composite bar was numerically simulated using DEFORM 3D finite element analysis software. The Taguchi method was used to study the effect of the first-step drawing parameters (the semi-angle of die α, the friction coefficient between the platinum tube and die μ1, the friction coefficient between the platinum tube and nickel rod μ2 and the outer diameter of the original platinum tube D) on the effective stress of platinum-clad nickel bar. Then, the optimal combination of parameters (D = 7.55 mm, μ1 = 0.2, μ2 = 0.3, α = 3°) was obtained. Furthermore, the results of the deformation behavior, cladding behavior, stress effectiveness and the distribution of the damage of the composite bar using optimization schemes were compared and analyzed with Numerical Simulations 8, which showed the worst result. Meanwhile, the experimental results were in general agreement with the simulation results of optimal combination of parameters, indicating that our simulation results are plausible. This has certain guidance significance to improve the quality of platinum-clad nickel composite wires in actual production.

Localization and Registration of 2D Histological Mouse Brain Images in 3D Atlas Space.

To accurately explore the anatomical organization of neural circuits in the brain, it is crucial to map the experimental brain data onto a standardized system of coordinates. Studying 2D histological mouse brain slices remains the standard procedure in many laboratories. Mapping these 2D brain slices is challenging; due to deformations, artifacts, and tilted angles introduced during the standard preparation and slicing process. In addition, analysis of experimental mouse brain slices can be highly dependent on the level of expertise of the human operator. Here we propose a computational tool for Accurate Mouse Brain Image Analysis (AMBIA), to map 2D mouse brain slices on the 3D brain model with minimal human intervention. AMBIA has a modular design that comprises a localization module and a registration module. The localization module is a deep learning-based pipeline that localizes a single 2D slice in the 3D Allen Brain Atlas and generates a corresponding atlas plane. The registration module is built upon the Ardent python package that performs deformable 2D registration between the brain slice to its corresponding atlas. By comparing AMBIA's performance in localization and registration to human ratings, we demonstrate that it performs at a human expert level. AMBIA provides an intuitive and highly efficient way for accurate registration of experimental 2D mouse brain images to 3D digital mouse brain atlas. Our tool provides a graphical user interface and it is designed to be used by researchers with minimal programming knowledge.

The effect of rolling temperature on the microstructure and properties of multi pass rolled 7A04 aluminum alloy

The current research on 7-series aluminum alloys mainly focuses on solid solution and aging treatments, as well as the flow stress during the deformation process. There are limited researches on the influence of thermal deformation temperature on the microstructure and properties of the aluminum alloy during multi-pass hot rolling process. In this study, the as-cast 7A04 aluminum alloy was subjected to homogenization treatment, followed by multi-pass hot rolling. The effects of different deformation parameters on dislocation density were analyzed. Microstructural characterization of the deformed alloy was performed using optical microscopy (OM), scanning electron microscopy (SEM) with energy-dispersive spectroscopy (EDS), X-ray diffraction (XRD), and micro-hardness tester. The optimal microstructure of the deformed alloy was selected based on the size of recrystallization. Subsequently, the Deform–3D finite element simulation software was used to analyze the multi-pass hot rolling process. The influence of deformation parameters on the uniformity of equivalent strain distribution within the samples was investigated. The results showed that at the deformation temperature of 430 °C, a significant amount of recrystallized microstructure appeared in the alloy, resulting in the lowest dislocation density and a significant reduction in the quantity of coarse precipitates. Finite element numerical simulation revealed that the deformation temperature had a certain influence on the uniformity of strain distribution within the alloy. However, this influence was mostly eliminated when the deformation temperature exceeded 380 °C. Meanwhile, the distribution of strain within the alloy was found to be related to the temperature distribution.

DOVE: Learning Deformable 3D Objects by Watching Videos

Learning deformable 3D objects from 2D images is often an ill-posed problem. Existing methods rely on explicit supervision to establish multi-view correspondences, such as template shape models and keypoint annotations, which restricts their applicability on objects “in the wild”. A more natural way of establishing correspondences is by watching videos of objects moving around. In this paper, we present DOVE, a method that learns textured 3D models of deformable object categories from monocular videos available online, without keypoint, viewpoint or template shape supervision. By resolving symmetry-induced pose ambiguities and leveraging temporal correspondences in videos, the model automatically learns to factor out 3D shape, articulated pose and texture from each individual RGB frame, and is ready for single-image inference at test time. In the experiments, we show that existing methods fail to learn sensible 3D shapes without additional keypoint or template supervision, whereas our method produces temporally consistent 3D models, which can be animated and rendered from arbitrary viewpoints. Project page: https://dove3d.github.io/.

A finite element based investigation of tool wear rate via machining of Al6061 alloys using deform-3D

The application of finite elements using Deform 3D in the turning of metals is very significant because it helps in the forecasting analysis before the production of products is made. This will help to eliminate material adhesion issues during the turning process, especially when working with aluminium materials. The aluminium 6061 alloys are extensively used in the engineering industry due to their lightweight and long-lasting properties, and it is one of these alloys that is regularly used due to its desirable qualities. Al6061 alloy, which is widely used in aerospace and building, needs precise machining to guarantee the best surface superiority. Tool wear sustained during machining has a direct impact on the surface quality of a machined component. This research utilized a finite element-based method using Deform 3D to investigate tool wear rate via machining of AL6061 alloys and also investigate the interactions between process parameters and tool wear with turning time analysis. The factors considered were depth of cut, cutting speed, and feed rate, and the response study was also analysed with regard to turning time. The L9 Taguchi orthogonal array was engaged in the methodology to design the experiments for the simulation study. The results obtained show that the time of machining and the internal machining factors are very important in resolving the problem of tool wear during the manufacturing of the mechanical device. At the highest variation time of cut, the optimal process parameters of 1800 rpm cutting speed, 3 mm depth of cut, and 2 mm/rev feed rate resulted in the lowest tool wear rate.

An Efficient Accelerator Based on Lightweight Deformable 3D-CNN for Video Super-Resolution

Deformable convolutional networks (DCNs) have shown outstanding potential in video super-resolution with their powerful inter-frame feature alignment. However, deploying DCNs on resource-limited devices is challenging, due to their high computational complexity and irregular memory accesses. In this work, an algorithm-hardware co-optimization framework is proposed to accelerate the DCNs on field-programmable gate array (FPGA). Firstly, at the algorithm level, an anchor-based lightweight deformable network (ALDNet) is proposed to extract spatio-temporal information from the aligned features, boosting the visual effects with low model complexity. Secondly, to reduce intensive multiplications, an innovative shift-based deformable 3D convolution is developed using low-cost bit shifts and additions, maintaining comparable reconstruction quality. Thirdly, at the hardware level, a dedicated critical processing core, together with a block-level interleaving storage scheme, is presented to avoid dynamic and irregular memory accesses caused by the deformable convolutions. Finally, an overall architecture is designed to accelerate the ALDNet and implemented on an Intel Stratix 10GX platform. Experimental results demonstrate that the proposed design can provide significantly better visual perception than other FPGA-based super-resolution implementations. Meanwhile, compared with the prior hardware accelerators, our design can achieve 2.75 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times$</tex-math> </inline-formula> and 1.63 <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\times$</tex-math> </inline-formula> improvements in terms of throughput and energy efficiency, respectively.

EVALUATION OF THE STRESS-STRAIN STATE OF MAGNESIUM AND BIMETALLIC BALLS LOADED WITH PRESSURE IN A DRILLING WELL

In the oil industry, soluble balls made of magnesium alloys serve as plugs for temporary sealing of various sections wells. It is noted that magnesium is a metal with a low density, and therefore the gravitational force may not be enough to tightly press the ball against the valve seat. Therefore, the development of methods aimed at weighing the balls is relevant. This is achieved, for example, by manufacturing bimetallic balls, the shell of which is made of a degradable material, for example, magnesium or its alloys, a non-degradable material, for example, steel, is placed inside the shell. The purpose of the work is to compare the stress-strain state of magnesium and bimetallic (the shell is made of magnesium, inside the shell is a steel ball) balls during operation in an oil well. The scheme of operation and testing balloons under the influence of liquid under pressure is considered. The simulation was carried out in the DEFORM 2D software module. The size of the balls is selected from the actual application condition, in addition, in the case of a bimetallic ball, the diameter of the steel ball located inside the magnesium shell is set less than the inner diameter of the seat. This guarantees the passage of the ball through the seat hole after the dissolution of the magnesium shell. Calculations of the degree and rate of deformation, the average normal stress and the stress state index of magnesium and bimetallic balls are performed. The dangerous zone of the balls from the position of cracking is revealed — the zone of contact with the saddle, where the deformation is localized. In addition, it was found that in the case of loading a bimetallic ball, all deformation is concentrated in the magnesium shell, and the steel ball does not deform at all and in this case acts as a mandrel. The stress state turns out to be more favorable at the periphery of the balls, however, the maximum of the average voltage modulo a bimetallic ball is 16 % higher than this value of a magnesium ball. The center of the magnesium ball is subject to tensile stresses, which is not observed in a bimetallic ball. According to the results of the calculation of the stress state indicator in the dangerous zone of the balls, the level of σ/T of a bimetallic ball is on average 20 % higher than this indicator of a magnesium ball. Thus, a bimetallic ball in the process of loading with a liquid under pressure has a more favorable stress-strain state compared to a magnesium ball.

Photo-thermoelastic wave propagation with changing thermal conductivity on excited pulsed laser nanoscale microelongated semiconductor material

Indroduction: The novel model of a non-local elastic semiconductor material that is microelongated is created. The process of photothermal transfer is responsible for the stimulation of the material. Photo-thermoelastic theories are used when the thermal conductivity is changed for the non-local medium. Under the influence of laser pulses, the effective framework describes the nanoscale microelongation instance as well as the interference between the photo-thermoelastic propagation waves in the non-local medium. It is possible to think of thermal conductivity as a linear function of temperature when electronic and thermoelastic deformation mechanisms are described. Two-dimensional deformation (2D) is used to extract the main fields, which obtained in non-dimension.Methods: Harmonic wave analysis, which is described by the normal mode, has been used to convert the basic equations into non-homogeneous higher-order ordinary differential equations. Applying a small subset of the possible non-local semiconductor surface conditions leads to exhaustive solutions.Result and Discussion: The outcomes of numerical simulations for silicon (Si) are graphically shown. There are comparisons made and explanations given for the investigated physical factors like their thermal conductivity, laser pulses and microelongation parameters.

3D Electronic Sensors for Bio‐Interfaced Electronics and Soft Robotics

AbstractMulti‐dimensional electronic devices for sensing applications have received immense attention in the fields of bio‐interface electronics and soft robotics to achieve structural manifolds in recent years. The structural diversities of sensors are tuned based on the environments in which they encounter multipurpose and complex form factors of electronics. 3D electronics are one of the emerging sensor platforms characterized by structural adaptability and compatibility on free target surfaces, resulting in unprecedented improvement of spatial resolution. Herein, the recent progress made in the fabrication and usage of 3D electronic sensors that are classified into two groups based on the methodological concepts used for fabrication in bio‐interfaced electronics and soft robotics applications, is reviewed. The latest advances in the design and development of 3D printable and 2D to 3D shape‐deformable electronic sensors are reviewed with a focus on printable materials and deformation mechanisms, respectively. 3D printing techniques enable the facile fabrication of arbitrary and seamless electronics without the use of conventional microfabrication technologies. Deformable electronics cover their self‐tune architectures and functions depending on mechanical deformation based on buckling, origami, and kirigami fabrication strategies. Finally, the printed and deformable 3D sensors show their potential for use in next‐generation sensing platforms.

Analysis of Milling Force and Optimization of Milling Trajectory for the NC Machining of Small Integral Impeller

In order to reduce the deformation of small integral impeller and improve the surface quality of blade in the process of NC machining, the influence of trajectory parameters on the milling force in the process of impeller NC finishing is studied and the orthogonal experiment with trajectory parameters as the main influencing factor is designed. In Deform 3D process simulation system, the physical dynamic simulation of NC milling force is carried out, the influence rules of the trajectory parameters on the milling forces in X, Y and Z directions are analysed, and then the range analysis method is used to optimize the simulation data to get the optimal combination of the trajectory parameters. Taking the actual production of a small integral impeller as an example, the trajectory parameters before and after optimization are respectively applied to 5-axis NC machining and the data of product inspection show that the optimized trajectory parameters not only improve the rigidity of the blade root and reduce the overall deviation of the blade, but also verify that the small milling force is obtained after the optimization of the trajectory parameters for the finish machining aiming at the surface quality and the optimization scheme of the trajectory parameters proposed in this paper is feasible.

Hot Forging Die Design Optimization Using FEM Analysis for Near-Net Forming of 18CrNiMo7-6 Steel Pinion Shaft

The objective of the presented work was to develop a new forging process for a pinion shaft as a component of a wind turbine. A study of near-net-shape forming using Deform 3D software was performed to reduce operational cost, time, and material scrap; enhance specific properties; increase productivity. Near-net forged products have good dimensional accuracy and continuous metal flow lines, which are characteristic of improved mechanical properties. To avoid the traditional trial-and-error experimental method, the process and tool design were accomplished with a careful and detailed numerical simulation approach. In the present work, the Finite Element Method was used to develop a process model for the existing hot forging process of the 18CrNiMo7-6 steel pinion shaft used in a wind turbine. The developed numerical process model was validated via experiment including a comparison of the metal flow lines from the FEM model with the metallography results of the forged part. Two new die designs were proposed, and the simulation results were compared to the actual process to achieve improved geometry. The results for the new geometries showed improvements in terms of the die cavity filling for the new proposed dies and better results in grain flow orientation. Compared to the initial non-optimized die, the new designs improved the mechanical properties and savings associated with the lower volume of required raw material and fewer finishing operations. Considering the applied stresses and wear in the new near-net shape, the die geometry shall be updated to accommodate more severe solicitations. Naturally, all the improvements carried out are dependent on other factors such as the conditions of the equipment, operator skills, lubrication, and other variables. A surface heat treatment is also suggested for stress relief as a reliability improvement.

The New Technology of Die Forging of Automotive Connecting Rods from EN AB-71100 Aluminium Alloy Cast Preforms

This article presents a new technology for forming automotive connecting rod forgings by means of die forging from cast performs from EN AB-71100 (EN AB-AlZn10Si8Mg) aluminum alloy. A premise was made that the production process would be carried out on forging presses. The process of forming connecting rod forgings was analyzed considering different deformation rates related to the type of machine used: a crank press and a screw press. The billet in the form of in-house designed, shaped preforms cast into sand molds with two variants of geometry was used in the process. The numerical analysis of the new process was carried out on the basis of the finite element method using Deform 3D, the simulation software for metal forming. The simulations were conducted in the spatial deformation conditions, considering the full thermomechanical analysis. Based on the simulations, certain important findings concerning the novel process were acquired, including the distribution of stress, deformation, temperatures, cracking criterion and energy parameters. The results of numerical tests confirmed the possibility of producing defect-free forgings of connecting rods from EN AB-71100 aluminum alloy on forging presses by means of the proposed technology. The proposed process of forging using crank and screw presses was verified in the course of tests conducted in industrial conditions. The properly formed connecting rod forgings were subjected to quality tests in terms of their structure and mechanical properties.

Autostereoscopic 3D Augmented Reality Navigation for Laparoscopic Surgery: A Preliminary Assessment.

Since Augmented Reality (AR) and 3D visualization have proven to be of great significance to the safety and effectiveness of surgical outcomes, will autostereoscopic 3D AR without glasses bring new opportunities for surgical navigation of laparoscopic surgery? We used the CPD-based deformation registration algorithm and the proposed virtual view generation algorithm, realizing a deformable autostereoscopic 3D AR navigation framework for laparoscopic surgery. The depth perception and user experience of the 3D AR navigation were evaluated compared with the 2D AR display using an in-vitro porcine heart and offline clinical partial nephrectomy laparoscopic images. The autostereoscopic 3D AR allowed participants to have a more consistent spatial perception as well as a shorter measuring time than 2D AR with significant difference of p < 0.05. It can also improve relative depth perception for smaller distance separation of objects < = 3.28 mm. However, the autostereoscopic 3D AR perceived a worse experience compared to 2D AR in the user experience. Autostereoscopic 3D AR shows a more efficient and robust sense of spatial scale than 2D AR with better potential to shorten the operating time and improve surgical outcomes than 2D AR, but image blur and distortion are issues that must be solved to improve the perception effect. High precise registration and high fluency visualization requirements could make autostereoscopic 3D AR navigation for soft tissue more challenging. Our work lays a theoretical foundation for the further development of laparoscopic surgical navigation.

Deformable 3D medical image registration with convolutional neural network and transformer

Deformable registration of medical images based on deep learning has been the research focus this year. Convolutional Neural Network (CNN) and the transformer are the most common backbone and have been shown to enhance registration accuracy. However, CNN lacks the ability to contact long-distance information, and the transformer lacks the ability to capture local information. Whichever subtle feature loss may lead to disastrous consequences in the analysis of clinical medicine. This paper presented a novel registration network named Information Complementation Network (ICN). We aim to improve the registration accuracy by complementing the lost information. Pure transformers can establish long-distance spatial information about the image. Proposed meshing patch embedding can minimize the loss of local information and expand the receptive field to extract long-distance information. The dual-path decoder in ICN is designed to restore information furthest. We experimented on 3D brain MRI data and quantitatively compared several excellent registration models. Compared with conventional methods, the dice coefficient increased by 3%. Compared with the advanced methods, the dice coefficient increased by 1%. The number of foldings was reduced by about 50% without any loss of registration accuracy. Each evaluation metric of the trained models on liver CT images was higher than other methods. By fully complementing the lost or invalid information, ICN achieved higher registration accuracy and smoother deformation field. The innovation and contribution of this paper have the potential to be applied to clinical research or medical image processing.

Numerical study on response characteristics of a caisson-type quay wall subjected to bidirectional ground shaking

The aim of this paper is to use numerical simulations to elucidate the effect of liquid–quay wall interaction on the seismic behavior of caisson-type quay wall subjected to real ground motions, assuming irrotational and inviscid flows. Three-dimensional, time-domain, dynamic analysis of a typical caisson-type quay wall is carried out using a coupled Lagrangian-Eulerian scheme, and six real excitation records are applied as ground vibration. The geometric complexity in the bounded caisson–seawater–backfill/foundation system is handled in the finite element method (FEM) using deformable 3D mesh where each structural medium can be discretized independently. The performance of the present coupled numerical analysis approach is validated against available numerical predictions, exhibiting good agreement with benchmark data. The response is appraised in terms of excess pore water pressure generated in the porous media, soil–sea–structure's residual displacements, and induced hydrodynamic pressures during the earthquake excitation. The numerical procedure demonstrates that excitation frequency spectrum in different intensity altitudes plays a crucial role in the behavior of quay walls and special attention must be given to gain a better understanding on the dynamic responses of such coupled systems.

Preoperative Simulation of Ileal Pouch-Anal Anastomosis in Patients With Ulcerative Colitis Using a 3-Dimensional Printed Model.

During restorative proctocolectomy with ileal pouch-anal anastomosis for ulcerative colitis-associated colorectal cancer or dysplasia, ileal pouch-anal handsewn anastomosis (IAA) is preferred to avoid the risk of cancer development in the remaining rectal mucosa. However, there is a risk of the ileal pouch not reaching the anus with this procedure. Here, we created deformable 3-dimensional (3D) models for simulation. Six patients who underwent IAA without vessel ligation and 5 patients who underwent ileal pouch-anal canal double-stapled anastomosis (IACA) because the ileal pouch did not reach the anus were studied. A 3D printer was used to create deformable 3D models from the data obtained from computed tomography scans. The positional relationship among the mesenteric arteries, pubis, and coccyx were evaluated. The distance between the superior mesenteric artery root and the tip of the ileal artery was longer in the IAA group than that in the IACA group (IAA vs IACA: 26.2 ± 2.1 cm vs 20.9 ± 1.6cm). The distance from the tip of the ileal artery to the coccyx (IAA vs IACA: 6.7 ± 1.7 cm vs 12.1 ± 2.1 cm) and the distance from the tip of the ileal artery to the lower edge of the pubis (IAA vs IACA; 8.1 ± 1.3 cm vs 12.7 ± 2.4 cm) were longer in the IACA group than those in the IAA group. We established a method for creating 3D deformable models of patients with ileal pouch-anal anastomosis. These 3D models may be useful for preoperative simulation.

Experimental and numerical investigation of dry turning AISI 1030 carbon steel using CNC lathe machining

Nowadays, modern metal industries have difficulty obtaining the required surface quality during machining. This is because various process parameters affect the quality of the surface. The aim of study to examine and enhance the impact of cutting-speed, cutting-depth, and feed rate during dry turning of AISI 1030 carbon steel experimentally and numerically (by DEFORM 3D) to get a better output response like minimal surface roughness, tool temperature, and maximum MRR. Taguchi-based grey relational analysis optimization technique was used for the experimental design and to determine the optimum solution of the multi-response. ANOVA was utilized to assess the contribution of the cutting parameters. Based on the results, cutting speed was the most important parameter that influenced the multiple responses of the grey-relational analysis, with a significance of 56.85%. The optimum parametric combination of multi-responses was 90 m min−1, 0.25 mm, and 0.15 mm/rev. With a minimum average relative error, the Taguchi prediction and finite element simulation were in excellent agreement with the experimental result.