Towards intelligent knowledge assistance in abrasive belt grinding via a retrieval-augmented generation chatbot with reliability support

In abrasive belt grinding, abrasive belt granularity, abrasive belt speed,feeding speed and grinding force have a great influence on the surface roughness. In order to predicate the surface roughness of Ti-6Al-4V,a response surface methodology are used to build the model to predict surface roughness,and the influence of various parameters on surface roughness was analysed. The research shows that with the abrasive belt granularity and abrasive belt speed increasing,the work piece surface roughness decreases;with the grinding force and feeding speed increasing,the work piece surface roughness increases. Through the test,the response surface methodology with high prediction accuracy,provides a theoretical basis for the reasonable selection of abrasive belt grinding parameters.

In abrasive belt grinding, abrasive belt granularity, abrasive belt speed,feeding speed and grinding force have a great influence on the surface roughness. In order to predicate the surface roughness of Ti-6Al-4V,a response surface methodology are used to build the model to predict surface roughness,and the influence of various parameters on surface roughness was analysed. The research shows that with the abrasive belt granularity and abrasive belt speed increasing,the work piece surface roughness decreases;with the grinding force and feeding speed increasing,the work piece surface roughness increases. Through the test,the response surface methodology with high prediction accuracy,provides a theoretical basis for the reasonable selection of abrasive belt grinding parameters.

Abrasive belt grinding experiments of ZrO2Engineering Ceramics are carried out by using 4 different abrasive belts. The orthogonal test with zirconia-corundum belt was to get the best grinding parameter, the amount of material removal workpiece surface roughness and belt wear were measured to get the best grinding parameter.In this paper,the influence of abrasive belt granularity and different grinding parameters to grinding efficiency and workpiece surface quality throughout the process of grinding ZrO2Engineering Ceramics was analyzed. Analysis wear mechanism of engineering ceramics based on the Abrasive cutting model by observing the surface morphology. The results show that increasing the grinding force or the abrasive belt granularity can decrease the workpiece surface roughness;With the abrasive belt speed or grinding force increasing,the material removal rate and the wear ratio to some extent, but brittle fracture is occued easily on its surface when exceeds the critical value; When the abrasive belt speed is 19m/s,the grinding force is 15N and the abrasive belt granularity is 120#, ZrO2Engineering Ceramics grinding effects reach the best.

Automation and self-monitoring implementation of manufacturing processes will support the development of interoperable ecosystem relevant to the Industry 4.0 concept. Among many industrial cases, abrasive belt grinding is a tertiary machining process used to achieve desired surface quality and to machine off features such as burrs and weld seams. Manufacturers are in the need of an ability to closely monitor and optimise the performance of abrasive belt grinding processes to meet tight tolerances. The abrasive belt grinding process is highly nonlinear due to the complexity of the underlying physical mechanisms, some of which remain unknown. Existing research in the literature on in-situ tool wear prediction were primarily focused on hard tools, but limited effort can be found on that of compliant belt tools. Although many advanced machining cells are equipped with belt grinder and robotic manipulators for surface finishing, industries still rely on skilled operators to manually remove weld seams using belt sanders. Self monitoring of such a dynamic process in industrial robot cell environment is essential in having a fully automated system. This research aims to model the robotic abrasive belt grinding process in dry conditions appropriate for monitoring purposes. The first part of this thesis discusses the influence of the process parameters on material removal and surface quality in abrasive belt grinding process. Interpretation of Taguchi's Design of Experiments (DoE) experimental results revealed that abrasive grain distribution on backing material has significant influence on material removal and surface quality. Subsequently, a systematic approach to mathematically model the belt grinding process using regression techniques based on soft computing is presented. The second part of the thesis deals with real-time monitoring of the belt grinding tool life. Predicting belt tool life helps to determine whether it is under-utilised, overused or it is due for replacement. Unlike other rigid abrasive machining tools, in abrasive belts the grains are not regenerated. The influence of grain wear on material removal mechanisms namely cutting, ploughing and rubbing were investigated with single grit scratch tests and Acoustic Emission (AE) sensor reading analysis. Having understood the effect of abrasive grain wear on belt grinding performance, a methodology to virtually monitor the coated abrasive belt tool life in real time with the help of physical sensors and machine learning classifiers is developed. In the last part of this thesis, an automated weld seam removal method is proposed. The method offers a real time endpoint verification system for weld seam removal using accelerometer, force and vision-based sensors along with machine learning and deep learning algorithms. Expectedly, this will reduce unnecessary costs and also increase the safety level of operators. In general, the proposed modelling and virtual metrology techniques will add values to the entire manufacturing process, in particular to those involving abrasive belt grinding, and will comply to Industry 4.0 objectives.

This article applies the abrasive belt grinding technology on the conventional lathe. According to the principle and characteristic of abrasive belt grinding, a device is designed using abrasive belt grinding technique. The affects on work piece surface roughness brought by performance of abrasive belt, work piece rotate speed, grinding depth and feed, hardness of contact wheel and so on are studied in experiments. The results indicate that using the abrasive belt grinding installment on the lathe to carry on the cylindrical precision grinding, can reduce the surface roughness of work pieces effectively and increase the machining precision. An effective way to reform the ordinary lathe as a grinding machine is provided.

Surface roughness prediction model of GH4169 superalloy abrasive belt grinding based on multilayer perceptron(MLP)

The abrasive belt grinding process is a highly nonlinear dynamic change process. The coupling action mechanism between mechanical field and thermal field during grinding is complex and variable. In this paper, firstly, the abrasive belt grinding experiment of titanium alloy was carried out to measure the change of temperature and force during the grinding process, and the Savitzky-Golay filter analysis was carried out on force signal. Secondly, the generation of grinding heat and force was described in detail, the equilibrium process of thermal-mechanical coupling was analyzed, and the finite element equation of thermal-mechanical coupling was deduced for abrasive belt grinding. Thirdly, the finite element simulation model of abrasive belt grinding is established to comprehensively analyze the change rule of thermal-mechanical coupling in the grinding process. Finally, the experimental results and simulation results of belt grinding are discussed and analyzed. The experimental results found that the grinding force changes are divided into three different stages, and the maximum surface temperature decreases to a certain extent with the grinding process. The simulation results show that the plastic deformation zone and “dead metal zone” are consistent with the theory in the grinding process. This study can provide a reference for relevant machining and further improve the grinding workpiece’s surface quality through thermal-mechanical optimization.

Surface formation modeling and surface integrity research of normal ultrasonic assisted flexible abrasive belt grinding

Machining processing industries have continuously developed and improved technologies and processes to transform finished product to obtain better super finished product quality and thus increase products. Abrasive machining is one of the most important of these processes and therefore merits special attention and study. Indeed, grinding is the process of removing metal by the application of abrasives which are bonded to form a rotating wheel or belt. When the moving abrasive particles contact the workpiece, they act as tiny cutting tools, each particle cutting a tiny chip from the workpiece. The abrasive belt grinding is efficient, economic, widely used and being said “universal grinding”. It can get high machining accuracy and surface quality. Surface quality is a very important aspect of machining quality and it is the most important parameter to measure the surface quality. Many factors affect the surface roughness such as performance of abrasive belt, the amount of abrasive belt grinding, hardness of contact wheel. And the most important one is the amount of grinding. For electronic packaging, before soldering, copper substrates have to be polished by both chemical and mechanical polishing. Therefore, this article is aimed at that status so that to design and manufacture a new abrasive belt grinding machine. And then the surfaces for soldering of Cu substrates are ground and polished using the machine. Finally, the surface roughness of copper substrates polished by the abrasive belt grinding machine is evaluated and compared with other grinding machines.

Deep convolutional neural network-based in-process tool condition monitoring in abrasive belt grinding

Abrasive belt grinding is a manufacturing process used to finish the surface of materials. This process uses abrasive particles of geometrically undefined cutting edges bonded to a flexible cloth. Abrasive belt grinding is often performed manually (manual grinding), and a skilled operator can achieve high quality on complex parts. In manual grinding, the user feels and adjusts the input parameters, such as the grinding force and feed rate, based on the condition of belt wear and machine vibration. How the user controls these parameters in a manual grinding process is poorly understood. One of the downsides of manual grinding is that the depth of cut is complex to maintain compared to an automated grinding process due to an uneven grain penetration in the material with a normal force. Several novel works report research on abrasive belt grinding simulations intended for robot operations, but belt grinding simulations intended for a human-centered approach have not been studied extensively. This research investigates the kinematic belt grinding simulation parameters to improve the manual belt grinding process before a belt grinding process is conducted. A belt-grinding simulation model was created and connected to a graphical user interface (GUI). The belt grinding simulation model app was designed to assist users in predicting grinding process parameters. The input parameters include abrasive belt specification (grit size and belt dimension), feed rate, and cutting speed. The simulation outputs the average surface roughness, grinding time, and depth of cut, informing the user of the process’s effectiveness. First, the user inputs the input process parameters. Then, the simulation generates the belt topography, approximating the grits as spheres, and generates a workpiece with an estimated initial surface quality. Once the belt topography is generated, the grinding process is simulated with a suggested feed rate, cutting speed, and force. The result will be compared to a grinding process to validate the simulation predictions. The novelty of the shown work is that it is a simulation tool for manual operations that allows user input and interaction with the simulation before the grinding operation is conducted. Future sensor integration and force calculations will allow better manual operations and worker training guidance.

Titanium alloys have been widely used in ships, aviation, aerospace, and other industries because of their excellent material properties. In the abrasive belt grinding of titanium alloy materials, abrasive belt grinding is a kind of flexible grinding, and its cutting force and material removal are important parameters that characterize the machining process. Powerful belt grinding can realize the removal of large materials, but ensuring its surface integrity is also crucial to the comprehensive material properties of titanium alloy materials. This paper studies the grinding amount: the effect of feed rate, linear speed, and initial grinding pressure on the grinding force, and the influence of the grinding force on the law of material removal and surface integrity. By studying the relevant parameters of abrasive belt grinding consumption, revealing its changing law, determining the best grinding range, and obtaining the best powerful grinding parameters. It is concluded that the maximum grinding force can be achieved when the maximum initial grinding pressure is 12N and the smaller feed speed is 200 mm/min and the medium-high line speed is 15.6 m/s while achieving a large margin of material removal and ensuring better surface integrity.

The current research of abrasive belt grinding rail mainly focuses on the contact mechanism and structural design. Compared with the closed structure abrasive belt grinding, open-structured abrasive belt grinding has excellent performance in dynamic stability, consistency of grinding quality, extension of grinding mileage and improvement of working efficiency. However, in the contact structure design, the open-structured abrasive belt grinding rail using a profiling pressure grinding plate and the closed structure abrasive belt using the contact wheel are different, and the contact mechanisms of the two are different. In this paper, based on the conformal contact and Hertz theory, the contact mechanism of the pressure grinding plate, abrasive belt and rail is analyzed. Through finite element simulation and static pressure experiment, the contact behavior of pressure grinding plate, abrasive belt and rail under single concentrated force, uniform force and multiple concentrated force was studied, and the distribution characteristics of contact stress on rail surface were observed. The results show that under the same external load, there are three contact areas under the three loading modes. The outer contour of the middle contact area is rectangular, and the inner contour is elliptical. In the contact area at both ends, the stress is extremely small under a single concentrated force, the internal stress is drop-shaped under a uniform force, and the internal stress under multiple concentration forces is elliptical. Compared with the three, the maximum stress is the smallest and the stress distribution is more uniform under multiple concentrated forces. Therefore, the multiple concentrated forces is the best grinding pressure loading mode. The research provides support for the application of rail grinding with open-structured abrasive belt based on pressure grinding plate, such as contact mechanism and grinding pressure mode selection.

FCSNet: A quantitative explanation method for surface scratch defects during belt grinding based on deep learning

Material removal behavior of Cf/SiC ceramic matrix composites as a function of abrasive wear during diamond abrasive belt grinding