Workpiece Burn Research Articles

Physics-guided neural network for grinding temperature prediction

Creep-feed grinding is a high-efficiency, high-precision grinding process widely used in the manufacturing of aviation engines. However, the workpiece burn and other quality issues caused by high processing temperature limit the yield of grinding. Therefore, the accurate model of grinding temperature has become the key to improving processing efficiency and quality. Different from the traditional physical or data-driven models, this paper attempts to combine both perspectives based on Physics-Guided Neural Networks (PGNN) to accurately predict grinding temperature with a small number of experiments. At the level of data acquisition, real grinding experiment data was obtained and a data augmentation method had been proposed. At the level of neural network structure, optimisation processes were implemented to enhance prediction performance, and a physics-guided loss function was inserted to guide network training. The experiment results shows that PGNN had better prediction accuracy than the physical model, while also mitigating the limitations of data-driven models on small sample sets. PGNN also performed better with noisy data and predictions out of the training data range, this reveals the benefits of PGNN for small sample problems in processing scenarios.

Electrical discharge and arc milling with automatic tracking of optimal flushing direction: A novel high-efficiency compound machining method

The arc milling method has the advantages of high machining efficiency and low cost and is independent of the strength and hardness of machined materials. However, frequent electrode back-offs and the risk of workpiece burning may occur if erosion products are not removed promptly. In this study, it was found that the flushing method of the working medium had a significant impact on the machining performance of arc milling. Based on this, a novel high-efficiency compound machining method of electrical discharge and arc milling with automatic tracking of the optimal flushing direction was proposed. An automatic tracking optimizer for external working medium injection was designed to determine the optimal external flushing direction according to the feed direction. The influence of flushing methods, working mediums, and machining parameters on the machining efficiency, tool electrode wear rate, machining error, and surface integrity of titanium alloys were investigated. The results indicated that better machining performance and environmental friendliness were achieved using the compound flushing method of outer compressed air and inner deionized water. Additionally, the automatic tracking flushing method in the opposite direction of the feed direction showed superior results compared to other directions. The material removal rate with the opposite direction injection could be increased up to 1.62 times that of the same direction, and the relative electrode wear rate could be reduced by 14.76%. This novel method has broad application prospects for machining parts with difficult-to-cut materials in aerospace and military industries.

In-process detection of grinding burn using machine learning

The improvement of industrial grinding processes is driven by the objective to reduce process time and costs while maintaining required workpiece quality characteristics. One of several limiting factors is grinding burn. Usually applied techniques for workpiece burn are conducted often only for selected parts and can be time consuming. This study presents a new approach for grinding burn detection realized for each ground part under near-production conditions. Based on the in-process measurement of acoustic emission, spindle electric current, and power signals, time-frequency transforms are conducted to derive almost 900 statistical features as an input for machine learning algorithms. Using genetic programming, an optimized combination between feature selector and classifier is determined to detect grinding burn. The application of the approach results in a high classification accuracy of about 99% for the binary problem and more than 98% for the multi-classdetection case, respectively.

Grinding Energy Distributions and Wear Behaviors of Grain Cutting Edges in cBN Deep Grinding

This paper deals with the grinding energy distributions in wheel-workpiece contact zone and the wear behaviors of grain cutting edges in cBN deep grinding. By measuring the tangential grinding force distribution in the grinding zone, the grinding energy distribution form could be approximated to be triangular. However, the grinding energy distribution forms changed a little occurring workpiece burn. The wear behaviors of the grain cutting edges were observed by a Scanning Electron Microscope (SEM) and quantitatively evaluated in terms of attritious wear flat percentage. It is shown that the variation of the grinding energy distributions has an effect on the cutting edge wear characteristics.

Heat flux distribution and temperature prediction model for dry and wet cylindrical plunge grinding

The grinding heat is generally partitioned into the workpiece, wheel, chips and fluid in grinding process. The total amount of heat flux entering into the workpiece greatly affects the final workpiece surface temperature, which may cause undesirable workpiece burn. Moreover, the variable grinding chip thickness and fluid injection speed along the grinding contact zone could substantially change the specific energy and the shape of the heat source correspondingly. In this article, a Weibull heat flux distribution model for both dry and wet grinding temperature prediction was proposed by analyzing two key parameters: energy partition Rw and shape parameter k. The value of Rw was obtained by considering the real contact length, the active grits number and the average grit radius r0 on the basis of traditional formulas. The relationship between shape parameters k and useful flow was established by a FLUENT simulation of the convective grinding fluid applied in grinding contact zone with wheel-workpiece minimum clearance. The grinding temperature and grinding force experiments were conducted on a grinding machine MGKS1332/H to validate the proposed heat flux model. The calculated workpiece surface temperature distribution was obtained by using the experimental heat flux obtained by the reverse algorithm, and the error between calculated temperature and experimental temperature was analyzed. With the monitored force signals and the proposed temperature prediction model, the grinding temperature for both dry and wet grinding can be predicted, which will be helpful to the optimization and control of temperature in grinding process.

Wheel Working Surface Topography and Grinding Force Distributions in Creep Feed Grinding

This paper discusses the topographic features of wheel working surfaces and the grinding force distributions in wheel-work contact zones of creep feed grinding. Grain cutting edge wear is observed by a Scanning Electron Microscope (SEM) and quantitatively evaluated in terms of attritious wear flat percentage, which is able to characterize the wear behavior. By measuring the normal and tangential grinding force distribution in the grinding zone, the distribution form of grinding forces can be approximated to be triangular and the grinding forces increased rapidly due to workpiece burn. It is shown that the variation of the grinding force and the distribution are closely related to cutting edge wear characteristics.

Multi-Sensor Data Analytics for Grinding Wheel Redress Life Estimation- An Approach towards Industry 4.0

Grinding is an expensive and complex machining process, characterized by cutting grits undergoing non-uniform wear. The worn out grits influence the surface finish of the part, necessitating timely dressing. Conventionally, the dressing interval is decided either based on the wheel life end criteria viz. visual identification of the workpiece burn mark, chatter occurrence and deterioration in the part finish or on the number of parts produced. Improper dressing interval increases auxiliary machining time and grinding wheel wastage. Prevailing demands towards next generation smart manufacturing include product and process related benefits such as low operational cost, better customer service support, operation optimization and control. In the present work, we propose a low cost, process non-intrusive sensor technology with IoT enabled operational intelligence platform to estimate the redress life of grinding wheel based on wheel condition. Traverse grinding tests were carried out in a CNC surface grinding machine installed with Al2O3 wheel against D2 tool steel under wet condition. During experimentation, the spindle motor current, grinding forces and grinding wheel surface images were acquired using the Hall-effect sensor, dynamometer, and CCD camera respectively. Data acquisition, network connectivity, and cloud communication were empowered by serial output. Statistical time, frequency and wavelet domain features signifying the wheel life characteristic were extracted. To show the usefulness of motor current signals, the extracted features thereof were confirmed against grinding forces and wheel surface images. A time series Auto-Regressive Moving Average (ARMA) predictive model was developed to estimate the grinding wheel redress life using the selected root mean square (RMS) feature of a current signal. An android application was also developed for a graphical visualization of dressing time based on the RMS value of the spindle motor current signal. The developed methodology thus, allows operators and machines with sensors to communicate with each other and facilitates real-time traceability, visibility and control over the dressing action to perform automatic dressing before the wheel reaches its end of life.

Acoustic emission in dressing of grinding wheels: AE intensity, dressing energy, and quantification of dressing sharpness and increase in diamond wear-flat size

Abstract Although significant work has been done on the application of acoustic emission (AE) to grinding and to dressing of grinding wheels, several fundamental AE relationships between have not been established. These are: 1) the relationship between dressing energy and the measured AE signal; 2) how different diamond/grit contact modes (fracture, plastic deformation, rubbing, etc.) affect AE energy; and 3) how this can be used to quantify dressing efficiency, wheel sharpness and wear-induced changes in diamond shape. This paper describes an investigation into these fundamental concepts, with quantification of the relationship between AE intensity and dressing energy and the influence of different diamond/grit contact modes. A new parameter is introduced, the specific acoustic-emission dressing energy, which can be used to quantify dressing efficiency and wheel sharpness. Finally, the use of the AE intensity in evaluating diamond wear is explored, allowing the operator to know the size of the wear flat and when changes are necessary to avoid workpiece burn. Experimental work validates these concepts and practical recommendations are given on its application in industry.

Study on coolant-induced hydrodynamic pressure in contact zone while deep grinding with CBN wheels

ABSTRACTThe use of coolant has been considered an effective way to avoid workpiece burn in the grinding process. Hydrodynamic pressure induced by coolant in the contact zone is always measured to characterize the coolant condition in the contact zone. In this study, grinding experiments with a cubic boron nitride wheel were first performed to determine the evolution of hydrodynamic pressure during the grinding process. The experimental results showed that when burn happened, hydrodynamic pressure was at a low level and decreased gradually while the temperature and power signals fluctuated sharply. A theoretical calculation model and a 3D air–liquid two-phase numerical simulation model were subsequently constructed to predict the hydrodynamic pressure. Both theoretical calculation and numerical simulation results showed that the hydrodynamic pressure in such a case is in inverse proportion to the gap distance between the wheel and the workpiece. The theoretical calculation results are higher than the numerical simulation results. Furthermore, the experimental results correspond to the results of the 3D air–liquid two-phase simulation, which confirms the validity of this simulation. This article presents an accurate approach to predict hydrodynamic pressure, which provides an effective analytical method of studying and avoiding workpiece burn.

NEURAL NETWORK MODELING OF GRINDING PARAMETERS OF DUCTILE CAST IRON USING MINIMUM QUANTITY LUBRICATION

This paper presents the optimization of the grinding parameters of ductile cast iron in wet conditions and with the minimum quantity lubrication (MQL) technique. The objective of this project is to investigate the performance of ductile cast iron during the grinding process using the MQL technique and to develop artificial neural network modeling. In this project we used the DOE method to perform the experiments. Analysis of variance with the artificial neural network method is used to investigate significant effects on the performance characteristics and the optimal cutting parameters of the grinding process. Ductile cast iron was used in this experiment and the ethanol glycol was applied in the conventional method and compared with the MQL method. During conventional grinding, a dense and hard slurry layer was formed on the wheel surface and the performance of the ductile cast iron was very low, threatening the ecology and health of the workers. In order to combat the negative effects of conventional cutting fluids, the MQL method was used in the process to formulate modern cutting fluids endowed with user- and eco-friendly properties. Aluminum oxide was used as the grinding wheel (PSA-60JBV). This model has been validated by the experimental results of ductile cast iron grinding. Each method uses two passes - single-pass and multiple-pass. The prediction model shows that depth of cut and table speed have the greatest effect on the surface roughness and material removal rate for the MQL technique with multiple-passes by showing improved surface roughness, preventing workpiece burning and enabling a more friendly environment. Thus, various other parameters need to be added for further experiments, such as the wheel speed, distance from the wheel to the workpiece zone contact, and the geometry of the nozzle.

Application of shallow circumferential grooved wheels to creep-feed grinding

A single-point diamond dressing tool was used to cut shallow circumferential groove on aluminum oxide grinding wheels. Creep-feed grinding experiments were then carried out to compare the performance of these grooved wheels with a non-grooved wheel. The results showed that, for the conditions used in this research, a grooved wheel could remove twice as much material as a non-grooved wheel before workpiece burn occurred. The results also showed that a grooved wheel can improve grinding efficiency by reducing the consumed power by up to 61%. Although the use of grooved grinding wheels caused the workpiece surface roughness to increase slightly when compared to a non-grooved wheel, the grooved wheel enabled up to 37% more material to be removed while still maintaining workpiece surface roughness values below 0.3μm (“fine quality” surface finish), and up to 120% more material to be removed while still maintaining workpiece surface roughness values below 1.6μm (“average quality” surface finish).

Experimental Research on Dry Grinding of Titanium Alloy with Graphite Coated Brazed cBN Mounted Wheel

During dry grinding of titanium alloy, workpiece burn and chips adhesion phenomenon always takes place, which influences the surface quality of the machined components. In this paper, the solid lubricants, composed of graphite and polyvinyl butyral, are covered on the brazed cubic boron nitride (cBN) mounted wheels using the ultrasonic vibration method. Test of grinding of titanium alloy Ti6Al4V is carried out with the above tools. Comparative dry grinding tests are carried out to reveal the performance this new-type abrasive tools. Experimental study shows that the grinding temperature with the cBN grinding mounted wheels covered by graphite is lower than that of non-lubricant-covered wheels; the grinding surface with the cBN mounted wheels covered by graphite is remarkably improved with a roughness Ra lower than 1.5 μm. And graphite lubricant participates in grinding operation constantly.

A Line and Arc Transition Tool Radius Compensation Algorithm for Convex Contour

Tool radius compensation is necessary to CNC machining. However, B tool radius compensation leads to work piece burning at the sharp corner of convex contour because of the long time contacts between the work piece and tool, and C tool radius compensation frequently changes machining feed rate for its broken line tool path. This paper presents a novel tool radius compensation method suitable for high speed machining of convex contour, which have the advantages of both B and C tool radius compensation. It uses compound transition with line and arc between the adjacent blocks of CNC program. The offset tool paths of the adjacent blocks extend a small line segment respectively along their tangent direction, then insert an arc between the end points of the two extended line segments. The results of simulation and experiments show that the machining quality of the sharp corner of convex contour is improved and the machining time is shorter than C tool radius compensation.

Application of Nanofluids in Minimum Quantity Lubrication Grinding

This research investigated the wheel wear and tribological characteristics in wet, dry, and minimum quantity lubrication (MQL) grinding of cast iron. Water-based Al2O3 and diamond nanofluids were applied in the MQL grinding process and the grinding results were compared with those of pure water. During the nanofluid MQL grinding, a dense and hard slurry layer was formed on the wheel surface and could benefit the grinding performance. Experimental results showed that G-ratio, defined as the volume of material removed per unit volume of grinding wheel wear, could be improved with high-concentration nanofluids. Nanofluids showed the benefits of reducing grinding forces, improving surface roughness, and preventing workpiece burning. Compared to dry grinding, MQL grinding could significantly reduce the grinding temperature.

Automated Sensor Selection and Fusion for Monitoring and Diagnostics of Plunge Grinding

This paper deals with the development of an online monitoring system based on feature-level sensor fusion and its application to OD plunge grinding. Different sensors are used to measure acoustic emission, spindle power, and workpiece vibration signals, which are used to monitor three of the most common faults in grinding—workpiece burn, chatter, and wheel wear. Although a number of methods have been reported in recent literature for monitoring these faults, they have not found widespread application in industry as no single method or feature has been shown to be successful for all setups and for all wheel-workpiece combinations. This paper proposes a systematic approach, which allows the development and deployment of process-monitoring systems via automated sensor and feature selection combined with parameter-free model training, both of which are especially crucial for implementation in industry. The proposed algorithm makes use of “sparsity-promoting” penalty terms to encourage sensor and feature selection while the “hyperparameters” of the algorithm are tuned using an approximation of the leave-one-out error. Experimental results obtained for monitoring burn, chatter, and wheel wear from a plunge grinding test bed show the effectiveness of the proposed method.

Profiled Superabrasive Grinding Wheels for the Machining of a Nickel Based Superalloy

Machining data are presented for small diameter, profiled (fir tree root form), single layer/electroplated CBN (B46, B76 and 91) and diamond (D46) grinding wheels, when cutting Udimet 720. Spindles operating at 60,000 and 90,000 rpm were employed, with a synthetic polyalphaolefine (PAO) oil based fluid in a down grinding mode on single sided specimens. Operating parameters were selected to reflect finishing conditions. Measured tool wear was lower for CBN grit as compared to diamond however workpiece roughness was lower with Ra approaching 0.75 μm when using D46 wheels. Higher rotational speed produced lower grinding wheel wear. No workpiece burning was observed irrespective of grit type at the conditions tested.

Experimental Study on Creep Feed Deep Grinding Titanium Alloy with Slotted CBN Grinding Wheel

In order to improve the grindability of titanium alloys, the inhibition of chemical affinity between abrasives and titanium alloys and cooling enhancement in grinding zone are carried out in this paper. Slotted electroplated CBN grinding wheels with optimum topography are used, and different grinding fluid supply systems such as conventional tangential spraying coolant supply, inner chamber coolant jet impingement, radial high-pressure coolant jet impingment are employed in creep feed deep grinding experiments on titanium alloy (TC4). The experimental results show that high-pressure jet impingement has remarkable cooling effect. The temperature of the workpiece surface can be steadily kept below the critical film boiling temperature 120~130°C, while the workpiece surfaces is badly burnt with conventional coolant supply. The study will exploit an important research orientation that has great potential in high efficiency grinding. Further perfection of this study will not only enable us to increase the available material removal rate to a new level but also solve the workpiece burn problem of the difficult-to-machining materials in high efficiency grinding.In order to improve the grindability of titanium alloys, the inhibition of chemical affinity between abrasives and titanium alloys and cooling enhancement in grinding zone are carried out in this paper. Slotted electroplated CBN grinding wheels with optimum topography are used, and different grinding fluid supply systems such as conventional tangential spraying coolant supply, inner chamber coolant jet impingement, radial high-pressure coolant jet impingment are employed in creep feed deep grinding experiments on titanium alloy (TC4). The experimental results show that high-pressure jet impingement has remarkable cooling effect. The temperature of the workpiece surface can be steadily kept below the critical film boiling temperature 120~130°C, while the workpiece surfaces is badly burnt with conventional coolant supply. The study will exploit an important research orientation that has great potential in high efficiency grinding. Further perfection of this study will not only enable us to increase the available material removal rate to a new level but also solve the workpiece burn problem of the difficult-to-machining materials in high efficiency grinding.

PERFORMANCE OF A COHERENT JET COOLANT SYSTEM IN NON-CONTINUOUS DRESS CREEP-FEED GRINDING OF INCONEL 718

In this work, the effect of the degree of jet coherency on the occurrence of workpiece burn when creep-feed grinding Inconel 718 under non-continuous dress conditions is studied. Different degrees of jet coherency are compared on the basis of the maximum material removal rate achievable before workpiece burn occurs. The comparison is performed at different coolant flow rates as well as at different distances between nozzle and grinding zone. It is found that a more coherent jet results in considerably higher possible material removal rates before workpiece burn occurs. Furthermore, it is determined that nozzle distance from the grinding zone and nozzle orientation and position with respect to the grinding zone, using a coherent jet, does not affect cooling performance. It is also shown that an increase in flow rate will increase cooling performance but only up to a point.

Studies on Exploiting Further the Potential of High Efficiency Grinding

Aiming at the existent problems in the application of high efficiency grinding, some countermeasures are put forward to further exploit its potential, including the topography optimization design for high efficiency grinding wheel and cooling enhancement technology with jet impingement in grinding zone. The optimization model advanced here can be used to optimize the grinding wheel topography for different grinding processes with the minimum specific grinding energy. The cooling enhancement technology employed in creep feed deep grinding experiment of titanium alloy shows remarkable cooling capability. It is able to steadily control the temperature on workpiece surface at an extremely low lever under 100°C,when the workpiece is seriously burn with the conventional coolant supply. Further studies on the combination of these two countermeasures will not only enable us to increase the available material removal rate to a new lever but also solve the workpiece burn problem for those difficult-to-machining materials in high efficiency grinding.

Selections of working conditions for creep feed grinding. Part(II): workpiece temperature and critical grinding energy for burning

In this study, the workpiece temperature is predicted by the thermal model presented in the previous paper. Also, the grinding energy when the fluid begins to cause boiling is defined as the critical grinding energy for the workpiece burning. Thus, a sequence of experiments are performed. The results show that the predicted workpiece temperatures have great agreement with experimental and published data. Hence, the validity of the thermal model is proved. From the measured signals of grinding force and workpiece temperature, the occurrence of workpiece burning is accompanied with the abrupt rise of both signals. At the moment, the experimental grinding energy is also greater than the critical grinding energy. Thus, the workpiece burning can be predicted or evaluated so as to avoid the working conditions of burning occurrence.