Capability study of 2D heat-assisted Mill-Bend process

In this study, a cross-flow laser with maximum out power of 5kW was applied to the welding of Fe-Mn-Si shape memory alloys (SMA). The optimal welding processing parameters of 1mm thick Fe-Mn-Si SMA were established by orthogonal experiment. With the optimal processing parameters, power 1600W, welding speed 2.2m/min, defocusing distance 0.6mm, the tensile strength of the welded joint can achieve 93.5% of the base material, and the weld undercut and reinforcement transfer smoothly on the surface of the welding seam and the cross-section of the welding seam morphology presents "X" shape. The fracture appears in the weld fusion zone, so this area is weak during the laser welding. By the metallographic observation, the weld center structure is small equated, and the region of fusion zone is thick cellular crystal that decreases the strength of the welded joint, and the X-ray diffraction (XRD) test proves that the laser welding promotes the grain refinement. The micro-hardness analysis shows that the hardness of the fusion zone is lower than the other area clearly which is also associated to the weld structure. By the fracture scanning electron microscope (SEM) analysis, it is found that the fracture of Fe-Mn-Si SMA shows many small dimples with the optimal parameters, and the result is accorded with the base material which belongs to plastic fracture.

_ Aiming at the problem of online and real-time measurement of sheet metal bending angle, a monocular vision measurement method is proposed in this paper. The principle of this method is that a light beam is projected onto a plane to form a light stripe. When the relative angle between the reflecting plane and the light beam changes, the inclination angle φ of the light stripe changes synchronously. According to this characteristic, this paper proposes to monitor the change of the light stripe through a camera, reverse study the change of the inclination angle θ of the reflecting plane, and achieve online measurement of the bending angle Φ. In this paper, the geometric relationship between the inclination angle φ of the light stripe and the bending angle Φ is derived, and a bending angle measurement model based on two-dimensional light stripe information is established. An optimized gray centroid algorithm is used to identify the light stripe centerline, and a subpixel-level light stripe center extraction algorithm is established. Intelligent algorithms are used for parameter correction to reduce the impact of calibration errors. The bending angle measurement model test was completed. The analysis results show that the method proposed in this paper is correct and feasible, and can achieve high-precision, low-cost, and rapid bending angle measurement. After further improvement, the method proposed in this paper is suitable for online measurement of bending angle and can provide a methodological basis and reference for the development of bending CNC systems. Keywords sheet metal bending, bending angle measurement, geometric model, measurement model, light stripe recognition

Investigation of the V-bending process with the effect of V-grooving insert geometries is performed through finite element analysis within ANSYS LS-DYNA. Different V-groover geometries are tested to evaluate the effect on the final bent angle and bent radius of the sheet metal part, with the objective of obtaining the minimized bent angle and bent radius results. It is also observed that the corner radius of the V-groover has a major influence on the bent angle and bent radius. Due to the removal of material in the bending region, which reduced the bending resistance, an increase in the corner radius results in a decrease in both the bent angle and radius. The shape of V-groover also affects the bending results, with variations in geometries leading to variations in both bent angle and radius. When the cutting cross-sectional area is kept constant, the bent angle shows minimal variation, while the bent radius steadily increases with the V-groover angle, reaching its maximum at 90 degrees.

Experimental investigations and statistical analysis of pulsed laser bending of AISI 304 stainless steel sheet

Setup planning for machining a part is to determine the number and sequence of setups (including machining features grouping in setups) and the part orientation of each setup. Tool accessibility plays a key role in this process. An adaptive setup planning approach for various multi-axis machine tools is proposed in this paper focusing on kinematic analysis of tool accessibility and optimal setup plan selection. In our approach, feasible Tool Access Directions (TADs) of machining features are denoted by partially sequenced unit vectors; The Tool Orientation Spaces (TOS) of different multi-axis machine tools are generated according to their configurations through a kinematic model, and represented on a unit spherical surface. Starting from a 3-axis-based machining feature grouping, all possible setup plans of a given part for different types of machine tools (3-axis, 3-axis with an indexing table, 4-axis, and 5-axis machines) can be achieved effectively by tool accessibility examination. The optimal setup plans are selected from obtained candidates by evaluating both their locating and grouping factors. A so-generated setup plan can provide not only the best coverage of machining features and the primary locating directions but the optimal orientations of the work-piece for each setup. Only prismatic parts are considered in this proof-of-concept study, and the algorithms introduced in this paper are implemented in MATLAB. A case study is conducted to validate the algorithms.

Taguchi parameter design is an efficient and effective method for evaluating and optimizing parameters for a given process. This article describes a study involving the use of Taguchi parameter design for the evaluation of pressure measurement devices used on fuel nozzle test stands. This study examines and compares the performance of a digital display pressure transducer device and a mechanical analog pressure gage, under various parameter levels and configurations. Both an inner and outer orthogonal array are used to quantify control factor variability within the pressure gage calibration and measurement process, given two noise factors. Control factors include two types of dead weight testers, two types of pressure measurement devices, and three set pressures. Two noise factors utilized here were two different operators and the change in direction of the pressure before measurement (upward or downward). Collected data are used to determine the optimal levels of three quality characteristics: pressure difference, settling time, and hysteresis. Taguchi parameter design analysis of signal-to-noise ratio (S/N ratio) found an optimal test stand configuration included a pressure transducer with digital display with any combination of the other control factors, although with some sacrifice of response time. Verification of this selected configuration was conducted through linearity studies.

Rotary bending is able to bend sheets with various bending radii and angles by controlling forming conditions. The effects of applied radial force and rotary angle on bending radius and angle are clarified to realize and a precise rotary bending system. The bending radius is determined by applied force and bending angle is determined by applied radial pressure and rotary angle. The feedback bending system for rotary bending is developed in that the bending conditions are determined by the previous measured value of bend sheets.

This article aims to investigate the means to obtain optimal hot stamping process parameters and the influence of the stochastic variability of these parameters on forming quality. A multi-objective stochastic approach, integrating response surface methodology (RSM), multi-objective genetic algorithm optimization non-dominated sorting genetic algorithm II (NSGA-II) and the Monte Carlo simulation (MCS) method is proposed in this article to achieve this goal. RSM was used to establish the relationship between the process parameters and forming quality indices. NSGA-II was utilized to obtain a Pareto frontier, which consists of a series of optimal process parameters. The MCS method was employed to study and reduce the influence of a stochastic property of these process parameters on forming quality. The results confirmed the efficiency of the proposed multi-objective stochastic approach during optimization of the hot stamping process. Robust optimal process parameters guaranteeing good forming quality were also obtained using this approach.

Optimization of Shock Loop for Least Stress in Hermetic Reciprocating Compressor

In the present work, a design of experiment (DOE) technique using Taguchi method, has been applied to optimize the properties of ODS tungsten heavy alloys(WHAs). In this work Taguchi method involves nine experiments groups for four processing parameters (compaction pressure, sintering temperature, binding material type, and oxide type) with three levels was implemented. The signal-to-noise (S/N) ratio and analysis of variance (ANOVA) were employed to obtain the optimal process parameter levels and to analyze the effect of these parameters on density, electrical conductivity, hardness and compressive strength values. The results showed that all the chosen factors have significant effects on all properties of ODS tungsten heavy alloys samples. The density, electrical conductivity and hardness increases with the increase in sintering temperature. The analysis of the verification experiments for the physical properties (density and Electrical conductivity) has shown that Taguchi parameter design can successfully verify the optimal parameters, where the difference between the predicted and the verified values of relative density and electrical conductivity is about 1.01% and 1.15% respectively.

Optimization of processing parameters of laser skin welding in vitro combining the response surface methodology with NSGA- II

Optimizing process parameters for hot forging of Ti-6242 alloy: A machine learning and FEM simulation approach

The development of intracranial internal carotid artery (ICA) stenoses may be associated with the morphology of the siphon. The aim is to quantitatively characterize the geometry of ICA, and develop a classifier of the ICA shape in relation to the location and incidence of stenoses. The ICA geometry from 74 subjects was analyzed by means of image-based computational techniques. The siphon was split into two bends, and was described in terms of curvature radius, radius of vessel, angle of bending, and length. Differences of geometry between ICA classes were assessed in control group, consisted of 30 subjects without stenoses. In stenosed group, the association between the ICA classes and the incidence of stenoses were investigated and validated by hemodynamic simulation. The curvature radius and angle of the posterior bend were significantly different between ICA classes, as well as the angle between the two bends. An innovative classifier was developed with the three geometric parameters. The ICA classification was found associated with the incidence of stenoses at the siphon. Geometric factors relative to the ICA were correlated with the location and incidence of stenoses at the siphon. The present work has potential implications in the quest for hemodynamic factors contributing to the initiation and progression of intracranial ICA stenoses.

The VDA238-100 standard for tight radius bending (v-bending) of sheet materials has received widespread acceptance with automotive suppliers and material producers to characterize local formability. However, the test fixture and tooling in the v-bend test standard is not amenable to direct strain measurement and the operator cannot terminate the test at the onset of crack initiation as the outer bend surface is not visible. Consequently, fracture is identified using a load threshold and the bend angle estimated from an analytical formula based upon the punch displacement and tooling geometry. Bend angles are not directly transferable and must be interpreted relative to the sheet thickness and bend radius unlike a strain measurement. By obtaining an in-situ strain measurement on the surface using digital image correlation (DIC), the plane strain fracture limit can be accurately identified at the onset of cracking and remove ambiguity in translating the bend angles to practical forming operations and simulations. A novel inverted VDA test frame was developed to incorporate DIC strain measurement during the bend test and a variety of advanced high strength sheet materials were evaluated. It was observed that the VDA bend test creates a homogeneous strain state of plane strain across the width of the sample along with a proportional strain path to fracture without necking that is ideal for fracture characterization. A correlation is developed to relate the bend angle with the major strain for the materials considered and accounts for the sheet thickness and bend radius. A comparison of the bend angle obtained using the formula in the VDA standard based on the punch displacement was in very good agreement with manual measurements and an algorithm to measure the bend angle using DIC analysis was developed.

As a hydraulic lifting pipeline structure widely used in deep-sea oil, gas transportation, and sediment dredging projects, the pipeline configuration is related to the improvement of transportation efficiency and pipeline safety. Particularly, the bending section consumes the most energy and withstands severe erosion. Understanding and predicting the conveying characteristics of two-phase flow in bends is therefore crucial. In this study, CFD-DEM (computational fluid dynamics-discrete element method) simulation method is employed to calculate various cases, considering five parameters: pipeline bending radius and angle, conveying velocity, particle diameter, and concentration, to explore the influence of these parameters on pressure drop and erosion rate of pipeline and result in a data set of hundreds of cases. Based on this data set, seven machine learning models are trained to predict pressure drop and erosion rate, respectively. To enhance model accuracy, the stacking method in ensemble learning is employed to combine multiple models with good performance. Additionally, the Optuna and SHAP (SHapley Additive exPlanation) methods are utilized to optimize hyperparameters and explain the degree to which parameters impact the predictions. The result demonstrates that pressure drop is almost unaffected by bending radius, while erosion rate initially decreases and then increases with bending angle, and both increase with other parameters. Among the evaluated models, artificial neural network, XGBoost, and random forest all demonstrate high prediction accuracy. The stacking model further improves the accuracy, with mean absolute error improving by 21.7% and 32.2%, and the SHAP method demonstrated good interpretability, which is basically consistent with CFD-DEM results.