Plasma Arc Surface Hardening Robot Technology

In national economy and national defense, a lot of ma chine components become worthless early because of wear and tear and corrode. It leads to huge loss of resource and material. Surface hardening of the steel cou ld form a hard, wearable, corrode-resisting layer on the surface to enhance the mechanical property of the machine component. From 1980s, there is a new method of surface hardening that is heating with plasma arc. It overcomes the shortage of old methods and is adopted in automotive product industry. The plasma equipm ent is small and easy to be controlled, so it could be installed on a robot and moved everywhere. This paper analyzed the character of the plasma at first, then studied the plasm a arc as Guess distribution circular heat source to create the surface hardening temperature field and heating process. The method of the plasma arc surface har dening technology is given. This paper describes hardware design of the plasma arc surface-hardening robot and analyzes its kinematics. This robot is a humanoid form robot with a mobile p latform, a 7 DOF redundancy arm and a 2 DOF trunk. The footprint is an important feature for the robot that has to move in a cluttered environment. Thus the mob ile platform of the plasma arc robot is an omni-directional mobile robot with o rthogonal-wheel assemblies. The trunk is important for keep balance of the robo t. Thus a series spring is fixed in the trunk to provide accurate force feedback at each direction and insulate the shock loads from arm and mobile platform. Th e redundancy arm configuration is similar to a broadly simplified model of the h uman arm with 7 DOF. The maximum radius is about 1 m with a maximum load of abou t 1 kg. The redundancy of the 7 DOF allows the handling of situation in whic h additional movement constraints have to meet and avoids static or dynamic obst acles. It has better adaptation to typical human environment and to allow for hu man-like behavioral strategies in solving complex tasks. This robot will be applied widely in shipbuilding industry, mining industry and automotive product industry.

Numerical Investigation of Laser Surface Hardening of AISI 4340 Using 3D FEM Model for Thermal Analysis of Different Laser Scanning Patterns

Laser surface hardening is becoming one of the most successful heat treatment processes for improving wear and fatigue properties of steel parts. In this process, the heating system parameters and the material properties have important effects on the achieved hardened surface characteristics. The control of these variables using predictive modeling strategies leads to the desired surface properties without following the fastidious trial and error method. However, when the dimensions of the surface to be treated are larger than the cross section of the laser beam, various laser scanning patterns can be used. Due to their effects on the hardened surface properties, the attributes of the selected scanning patterns become significant variables in the process. This paper presents numerical and experimental investigations of four scanning patterns for laser surface hardening of AISI 4340 steel. The investigations are based on exhaustive modelling and simulation efforts carried out using a 3D finite element thermal analysis and structured experimental study according to Taguchi method. The temperature distribution and the hardness profile attributes are used to evaluate the effects of heating parameters and patterns design parameters on the hardened surface characteristics. This is very useful for integrating the scanning patterns’ features in an efficient predictive modeling approach. A structured experimental design combined to improved statistical analysis tools is used to assess the 3D model performance. The experiments are performed on a 3 kW Nd:Yag laser system. The modeling results exhibit a great agreement between the predicted and measured values for the hardened surface characteristics. The model evaluation reveals also its ability to provide not only accurate and robust predictions of the temperature distribution and the hardness profile as well an in-depth analysis of the effects of the process parameters.

Single Track Laser Surface Hardening Model for AISI 4340 Steel Using the Finite Element Method

Laser surface hardening becomes one of the most effective techniques used to enhance wear and fatigue resistance of mechanical parts. The characteristics of the hardened surface depend on the physicochemical properties of the material as well as the heating system parameters. To adequately exploit the benefits presented by the laser heating method, it is necessary to develop a comprehensive strategy to control the process parameters in order to produce desired hardened surface attributes without being forced to use the traditional and fastidious trial and error procedures. This study presents a comprehensive approach used to build a simplified model for predicting the hardness profile. A finite element method based prediction model for AISI 4340 steel is investigated. A circular shape with a Gaussian distribution is used for modeling the laser heat source. COMSOL MULTIPHYSICS software is used to solve the heat transfer equations, estimate the temperature distribution in the part and consequently predict the hardness profile. A commercial 3 kW Nd:Yag laser system is combined to a structured experimental design and confirmed statistical analysis tools for conducting the experimental calibration and validation of the model. The results reveal that the model can effectively lead to a consistent and accurate prediction of the hardness profile characteristics under variable hardening parameters and conditions. The results show great concordance between predicted and measured values for the dimensions of hardened and melted zones.

Size Effect of Impact Abrasive Particles on Wear and Surface Hardening Behavior of High‑Manganese Steel

The size effect of impact abrasive particles on wear and surface hardening behavior of high-manganese steel was studied.Impact wear tests were carried out on MLD-10 tester with abrasive particle sizes of 6.0–0.75 mm,respectively.The results showed that the impact wear behavior and surface hardening mechanism of high-manganese steel were affected by the size of abrasive particles.A critical size of abrasive particle might exhibit to distinguish the impact wear behavior.When the abrasive particle size was larger than 0.75 mm,the wear mass loss generally showed a decreasing trend with the decrease of the abrasive particle size.Dislocation strengthening and mechanical twinning contributed to the good work hardening behavior.However,effective surface hardening layer could not be formed for sample tested with particle size of 0.75 mm and the wear mass loss was the highest among all the conditions.The weak hardening effect led to the sharp increase of the wear mass loss.Press-in abrasives could be observed on the wear surface when the abrasive particle size was larger than 0.75 mm.The press-in abrasives were peeled off from the wear surface and broken,leaving deep grooves and peeling pits.Material exchange with the sample would occur with the flow of abrasives.A large area of furrow was formed on the wear surface.For particle size of 0.75 mm,aggregated abrasives formed a dynamic buffer layer on the surface and the stress distribution was more even.The formation of buffer layer would lower the effect of the impact load and the work hardening effect could not be fully activated.The mutual extrusion among the abrasives,friction wheel and sample caused plastic deformation of the worn surface during impact test.The present study would help guiding to select the application field of high-manganese steel more precisely.

A Predictive Modeling Based on Regression and Artificial Neural Network Analysis of Laser Transformation Hardening for Cylindrical Steel Workpieces

Laser surface hardening is a very promising hardening process for ferrous alloys where transformations occur during cooling after laser heating in the solid state. The characteristics of the hardened surface depend on the physicochemical properties of the material as well as the heating system parameters. To exploit the benefits presented by the laser hardening process, it is necessary to develop an integrated strategy to control the process parameters in order to produce desired hardened surface attributes without being forced to use the traditional and fastidious trial and error procedures. This study presents a comprehensive modelling approach for predicting the hardened surface physical and geometrical attributes. The laser surface transformation hardening of cylindrical AISI 4340 steel workpieces is modeled using the conventional regression equation method as well as artificial neural network method. The process parameters included in the study are laser power, beam scanning speed, and the workpiece rotational speed. The upper and the lower limits for each parameter are chosen considering the start of the transformation hardening and the maximum hardened zone without surface melting. The resulting models are able to predict the depths representing the maximum hardness zone, the hardness drop zone, and the overheated zone without martensite transformation. Because of its ability to model highly nonlinear problems, the ANN based model presents the best modelling results and can predict the hardness profile with good accuracy.

Hardness Profile Prediction for a 4340 Steel Spline Shaft Heat Treated by Laser Using a 3D Modeling and Experimental Validation

Laser surface transformation hardening becomes one of the most effective processes used to improve wear and fatigue resistance of mechanical parts. In this process, the material physicochemical properties and the heating system parameters have significant effects on the characteristics of the hardened surface. To appropriately exploit the benefits presented by the laser surface hardening, it is necessary to develop a comprehensive strategy to control the process variables in order to produce desired hardened surface attributes without being forced to use the traditional and fastidious trial and error procedures. The paper presents a study of hardness profile predictive modeling and experimental validation for spline shafts using a 3D model. The proposed approach is based on thermal and metallurgical simulations, experimental investigations and statistical analysis to build the prediction model. The simulation of the hardening process is carried out using 3D finite element model on commercial software. The model is used to estimate the temperature distribution and the hardness profile attributes for various hardening parameters, such as laser power, shaft rotation speed and scanning speed. The experimental calibration and validation of the model are performed on a 3 kW Nd:Yag laser system using a structured experimental design and confirmed statistical analysis tools. The results reveal that the model can provide not only a consistent and accurate prediction of temperature distribution and hardness profile characteristics under variable hardening parameters and conditions but also a comprehensive and quantitative analysis of process parameters effects. The modelling results show a great concordance between predicted and measured values for the dimensions of hardened zones.

Analyse of Warm Surface Rolling on the Grooved Steel Axle

Warm surface rolling is a working process between room temperature and re-crystallization temperature.With warm surface rolling of steel grade 45 grooved axle,its fatigue lifespan was measured by the endurance bending test.The influence of surface rolling reduction on the axle fatigue life period was experimentally studied at different surface rolling temperatures.The experimental results show that the fatigue life of the steel axles can be significantly improved by the warm surface rolling process.The optimum rolling reductions for the maximum fatigue life at different warm surface rolling temperatures were explored.The microstructures of the steel axles were analyzed.The surface strength improved by refining grains after the warm surface rolling was calculated by the Hall-Petch model.These research achievements could be also valuable to the relevant works.

Combination of cold drawing and cryogenic turning for modifying surface morphology of metastable austenitic AISI 347 steel

The application of components often depends to a large extent on the properties of the surface layer.A novel process chain for the production of components with a hardened surface layer from metastable austenitic steel was presented.The investigated metastable austenitic AISI 347 steel was cold-drawn in solution annealed condition at cryogenic temperatures for pre-hardening,followed by post-hardening via cryogenic turning.The increase in hardness in both processes was due to strain hardening and deformation-induced phase transformation from y-austenite to^-martensite.Cryogenic turning experiments were carried out with solution annealed AISI 347 steel as well as with solution annealed and subsequently cold-drawn AISI 347 steel.The thermomechanical load of the workpiece surface layer during the turning process as well as the resulting surface morphology was characterized.The forces and temperatures were higher in turning the cold-drawn AISI 347 steel than turning the solution annealed AISI 347 steel.After cryogenic turning of the solution annealed material,deformation-induced phase transformation and a significant increase in hardness were detected in the near-surface layer.In contrast,no additional phase transformation was observed after cryogenic turning of the cold-drawn AISI 347 steel.The maximum hardness in the surface layer was similar,whereas the hardness in the core of the cold-drawn AISI 347 steel was higher compared to that in the solution annealed AISI 347 steel.

An internal cooling grinding wheel:From design to application

The cooling and lubrication conditions during the grinding process significantly impact the nickel-based superalloy’s final service performance.The existing jet cooling and heat pipe technology can solve the heat conduction problem in the grinding process of superalloy.Still,managing cooling,lubrication,and chip removal are difficult.This paper describes the design and fabrication of a novel central fluid-through internal cooling slotted grinding wheel with an ordered grain pattern to improve the grinding machinability of a nickel-based superalloy.The pressurized grinding fluid was ejected into the grinding zone via the pipe and tool holder from the lower-end face of the inner cooling wheel.The structure of the grinding wheel was optimized using computational fluid dynamics(CFD).The flow field in the grinding area achieved the highest overall flow rate,distribution homogeneity,and effective exit flow when the internal flow channel had four throughholes.The exit for the inner runner is located at the abrasive edge and diamond staggered pattern.Single-layer brazing was used to create cubic boron nitride(CBN)abrasive rings with various abrasive patterns.The internal cooling wheel matrix and various components were prepared according to the optimized grinding wheel geometry model.A grinding test bench was built to conduct an experimental study of grinding the nickel-based alloy GH4169.The results show that,under the same conditions,a diamond-shaped staggered pattern obtains lower grinding temperature,lower surface roughness,better surface morphology,and more significant residual compressive stress distribution than an abrasive cluster diagonal circular staggered pattern or disordered pattern.The average effective flow rate calculated by CFD is increased by 42.3%when compared to the disordered pattern.In the experiment,compared to the disordered arrangement,with the increase of grinding wheel’s rotating speed and coolant pressure,the average grinding temperature of abrasive grain with diamond-interleaved arrangement decreases by 58.2%and 51.7%respectively,and its surface hardening degree decreases by 11.1%and 11.7%respectively.