Showing papers by "Jie Sun published in 2021"

Numerical investigation of thermal behavior and melt pool morphology in multi-track multi-layer selective laser melting of the 316L steel

Abstract: Rapid melting and solidification of powder particles through a high-power laser is the characteristic feature of selective laser melting (SLM), which controls the material and physical properties of fabricated components. Considering the multi-track multi-layer nature of an actual SLM process, an investigation of thermal behavior and melt pool morphology in multi-track multi-layer SLM of the 316L steel is presented in this paper. The SLM process of a four-layer component with multiple tracks was modeled. Element birth and death technique was used to simulate the layer built-up process. The established FEM model was used to investigate the variations in thermal variables and melt pool morphology with increasing number of layers. Moreover, the influence of various processing parameters in a multi-track multi-layer SLM was also studied. The results show that maximum melt pool temperature, melt pool width, and melt pool depth increase with increasing number of layers, whereas heating rates and cooling rates decrease with increasing number of layers. Compared with the previous layer, melt pool lifetime was observed to have a decreasing trend for layer 2 and increasing trend for layers 3 and 4. An increase in melt pool depth and decrease in melt pool width was observed by increasing hatch spacing. Furthermore, it was found that increasing laser power and scanning speeds both increase the heating and cooling rates.

Surface integrity evolution of machined NiTi shape memory alloys after turning process

Abstract: Owing to their shape memory effect and pseudoelasticity, NiTi shape memory alloys (SMAs) are widely used as functional materials. Mechanical processes particularly influence the final formation of the product owing to thermal softening and work-hardening effects. Surface integrity is an intermediate bridge between the machining parameter and performance of the product. In this study, experiments were carried out on turning NiTi SMAs at different cutting speeds, where surface integrity characteristics were analyzed. The results show that a higher cutting speed of 125 m/min is required to turn NiTi SMAs based on the evaluation of surface integrity. The degree of work hardening is higher at 15 m/min. Consequently, as a primary effect, work hardening appears on the plastic deformation of the machined samples, leading to dislocations and defects. As the cutting speed increases, the thermal softening effect exceeds work hardening and creates a smoother surface. A stress-induced martensitic transformation is considered during the turning process, but this transformation is reversed to an austenite from the X-ray diffraction (XRD) results. According to the differential scanning calorimetry (DSC) curves, the phase state and phase transformation are less influenced by machining. Subsequently, the functional properties of NiTi-SMAs are less affected by machining.

Optimization of Process Parameters for Turning Hastelloy X under Different Machining Environments Using Evolutionary Algorithms: A Comparative Study

Abstract: In this research work, the machinability of turning Hastelloy X with a PVD Ti-Al-N coated insert tool in dry, wet, and cryogenic machining environments is investigated. The machinability indices namely cutting force (CF), surface roughness (SR), and cutting temperature (CT) are studied for the different set of input process parameters such as cutting speed, feed rate, and machining environment, through the experiments conducted as per L27 orthogonal array. Minitab 17 is used to create quadratic Multiple Linear Regression Models (MLRM) based on the association between turning parameters and machineability indices. The Moth-Flame Optimization (MFO) algorithm is proposed in this work to identify the optimal set of turning parameters through the MLRM models, in view of minimizing the machinability indices. Three case studies by considering individual machinability indices, a combination of dual indices, and a combination of all three indices, are performed. The suggested MFO algorithm’s effectiveness is evaluated in comparison to the findings of Genetic, Grass-Hooper, Grey-Wolf, and Particle Swarm Optimization algorithms. From the results, it is identified that the MFO algorithm outperformed the others. In addition, a confirmation experiment is conducted to verify the results of the MFO algorithm’s optimal combination of turning parameters.

Investigation on machinability of NiTi shape memory alloys under different cooling conditions

Abstract: NiTi shape memory alloy products are becoming more and more popular in many areas. But owing to the unique characteristics of NiTi shape memory alloys, it is still considered restrictive by the traditional machining methods of producing NiTi shape memory alloys for finished products. Flood coolant and cryogenic with liquid nitrogen (LN2)–assisted machining is desired to improve machinability of material in the turning procedure. Experiments were conducted to examine the influence of cooling conditions (dry, flood, and cryogenic LN2) on turning NiTi shape memory alloys at different cutting speeds. Tool wear, cutting force, and surface integrity were selected as evaluation characteristics to explore the effects of different cooling methods and the stress-induced martensitic phase during the turning process. The study shows that the appearance of the stress-induced martensitic phase during the turning process harms the machinability of NiTi shape memory alloys. Flood conditions accomplish lower tool wear and cutting force at 15 m/min. Cryogenic conditions achieve higher machinability at 125 m/min.

Method of Postures Selection for Industrial Robot Joint Stiffness Identification

Abstract: Industrial robots are being widely applied to machining operations, and are gradually becoming competitive with traditional CNC machining centers. Obtaining accurate stiffness values of robotic joints is the foundation for deflections compensation in case of large cutting forces. A number of factors influence the accuracy of joint stiffness identification, especially robotic posture. This paper proposes a robust and accurate method for selecting suitable postures in the joint stiffness identification. The identification process of the joint stiffness matrix is presented, an index considering both the dexterity and the condition number of the observation matrix is then developed, and the procedure for postures selection based on it is provided. The results of simulations and experiments show that the proposed method is more robust and accurate than classical method.

Design and Analysis of a Linear Digital Variable Stiffness Actuator

Abstract: In this paper, a novel variable stiffness mechanism (VSM) based on specially designed S-springs made from shape memory alloy (SMA) is developed. Based on the stiffness model, by changing the state combination of the SMA S-springs with different thicknesses, the actuator’s stiffness can be discretely adjusted online. The stiffness adjustment range of the actuator can be conveniently extended almost from 0 N/m to infinity by changing the preset spring angle manually offline without a complex mechanical mechanism or replacing any parts. A linear digital variable stiffness actuator (LDVSA) is also designed with the VSM. Some tests of the SMA S-springs, as well as the actuator’s stiffness under different configurations, comparisons with other actuators and its trajectory tracking capacity are conducted to verify its design. Then, a dynamic model of the actuator is established and its bandwidth is analysed. Based on this, explosive experiments are designed and performed to explore the application potential of the actuator. Experimental results are provided to illustrate the explosive capacity and energy efficiency of the proposed design.

Investigation of MQL parameters in milling of titanium alloy

Abstract: Rational parameters for the minimum quantity lubrication (MQL) are essential to reduce cutting temperature and extend tool life during titanium alloys’ milling processing. However, little research has been done on the effect of nozzle elevation angle on Ti-6Al-4V milling. This article’s objective is to experimentally elucidate the impact of various MQL parameters, including oil flow rate, nozzle distance, and nozzle elevation angle in the end-milling of Ti-6Al-4V. Response surface methodology (RSM) analyzes MQL parameters’ influence on the cutting temperature, milling force, and acceleration. Results demonstrated that cutting temperature first decreases and increases with the increase of the oil flow rate increased from 30 to 250 ml/h. When the nozzle distance is either too large or too small, the measured cutting temperature, cutting force, and acceleration are higher than those measured at a nozzle distance of 60 mm. The nozzle elevation angle is the predominant factor affecting the experimental results. And proper nozzle settings can reduce the cutting temperature by 15 °C, the cutting force by at least 5.6%, and the acceleration by 8.9%.

Research on Robot Grinding Force Control Method.

Abstract: The contact force control between the tool and the workpiece in the industrial robot grinding process is essential to improve the surface quality and processing efficiency of the workpiece. This paper focus on the control of grinding force in the robot grinding process. Firstly, the grinding force control device and method are developed. Then, the force control mathematical model of the system is established and the fuzzy PID strategy of constant force control is especially designed. Finally, the force control tracking experiments has been conducted to verify the system performance. The experimental results show that the contact force control can be controlled smoothly, which can ensure the constant contact force between the workpiece and the tool of the grinding process.

Research on Tool Wear Detection Method Using Deep Residual Network

Abstract: During part machining, as the tool usage time and the number of passes increase, the cutting edge of the tool gradually wears out. As a tool for parts processing, the degree of wear of cutting tools has an important influence on the quality of parts processing. In order to understand the tool wear in time and ensure the quality of parts processing, this paper proposes a tool wear monitoring method based on deep learning. The application of deep residual network in tool wear degree monitoring is investigated, the overall scheme of tool wear degree monitoring is designed, and the deep learning scheme is implemented in the PyTorch framework. The vibration and force signals from multiple parallel experiments are first collected by sensors. The signals are analyzed in time and frequency using the short-time Fourier trans-form, after which the transform results are used as the input of the ResNet34 deep residual network for supervised training. Finally, the model effect is tested using test data. The research results show that the accuracy rate of using the deep residual network to monitor the degree of tool wear can reach 98%, which has high monitoring accuracy.

Variable Stiffness Actuator Structure for Robot.

Abstract: Based on the idea of regulating the variation on stiffness by controlling the number of springs involved in the work, this paper designs a kind of variable stiffness actuator (VSA) which can be applied to the field of robot. The variable stiffness structure takes the spiral tensile spring as the elastic element, and the number of springs Participating in the work is controlled by the push-pull electromagnet. It has the accurate positive and negative 32 kinds of stiffness adjustment values. The structure model was established by using SolidWorks. MATLAB analysis was used to optimize the design of the structure and conduct mechanical and structural stiffness analysis, and the angle range and stiffness range of the actuator were obtained, which had showed a uniform characteristic of distribution of adjustable stiffness values in stiffness range interval. The conclusion is that the VSA has the advantages of real-time and accurate change of stiffness, wide variation range of stiffness and wide adjustment range of angle.