An accuracy evolution method applied to five-axis machining of curved surfaces

Currently, some high-value-added applications involve the manufacturing of curved surfaces, where it is challenging to achieve surface accuracy, repeatability, and productivity simultaneously. Among free-form surfaces, curved surfaces are commonly used in blades and airfoils (with a teardrop-shaped cross-section) and optical systems (with axial symmetry). In both cases, multi-axis milling accuracy directly affects the subsequent process step. Therefore, reducing even insignificant errors during machining can improve the accuracy in the final production stages. This study proposes an “evolution” method to improve the machining accuracy of curved surfaces. The key is to include compensation for the machining error after the first part through profile error measurement. Thus, correction can be applied directly after the manufacturing programming is fully developed, achieving the product with the minimum number of iterations. Accordingly, this method measures the machining error and changes only one key parameter after the process. This study considered two cases. First, an airfoil in which the clamping force was corrected; the results were quite good with only one modification in the blade machining case. Second is an aspherical surface where tool path correction in the Z-axis was applied; the error was effectively compensated along the normal vector of the workpiece surface. The experimental results showed that the surface accuracy increased from 44.4 to 4.5 μm, and the error was reduced by 89.9%, confirming that the accuracy of the machine tool and process had achieved “evolution.” This technical study is expected to help improve the quality and productivity of manufacturing highly accurate curved surfaces.Open Access funding provided thanks to the CRUE-CSIC agreement with Springer Nature. This work was supported by: Natural Science Foundation of Shaanxi Province (Grant number: 2021JM010) Natural Science Foundation of Suzhou City (Grant number: SYG202018) Spanish Ministry of science and innovation (Grant number: RTC2019-007,194–4) funded by MCIN/AEI/ 10.13039/501100011033 Basque government group IT 1573-22 Fundamental Research Funds for the Central Universities (Grant No. xzy012019007) Project ITENEO Grant PID2019-109340RB-I00 funded by MCIN/AEI/ 10.13039/501100011033 Project HCTM Grant PDC2021-121792-100 funded by 702 MCIN/AEI/ 10.13039/501100011033 and by the “European Union NextGenerationEU/PRTR The Basque Government Department of Education for the pre-doctoral grant PRE_2021_1_014

Prediction of machining accuracy based on geometric error estimation of tool rotation profile in five-axis multi-layer flank milling process

In five-axis multi-layer flank milling process, the geometric error of tool rotation profile caused by radial dimension error and setup error has great influence on the machining accuracy. In this work, a new comprehensive error prediction model considering the inter-layer interference caused by tool rotation profile error is established, which incorporates a pre-existing prediction model dealing with a variety of errors such as geometric errors of machine tool, workpiece locating errors, and spindle thermal deflection errors. First, a series of tool contact points on the tool swept surface in each single layer without overlapping with others are calculated. Second, the position of the tool contact points on the overlapped layers is updated based on the detection and calculation of inter-layer interferences. Third, all evaluated tool contact points on the final machined surface are available for completing the accuracy prediction of the machined surface. A machining experiment has been carried out to validate this prediction model and the results show the model is effective

From computer-aided to intelligent machining: Recent advances in computer numerical control machining research

The aim of this paper is to provide an introduction and overview of recent advances in the key technologies and the supporting computerized systems, and to indicate the trend of research and development in the area of computational numerical control machining. Three main themes of recent research in CNC machining are simulation, optimization and automation, which form the key aspects of intelligent manufacturing in the digital and knowledge based manufacturing era. As the information and knowledge carrier, feature is the efficacious way to achieve intelligent manufacturing. From the regular shaped feature to freeform surface feature, the feature technology has been used in manufacturing of complex parts, such as aircraft structural parts. The authors’ latest research in intelligent machining is presented through a new concept of multi-perspective dynamic feature (MpDF), for future discussion and communication with readers of this special issue. The MpDF concept has been implemented and tested in real examples from the aerospace industry, and has the potential to make promising impact on the future research in the new paradigm of intelligent machining. The authors of this paper are the guest editors of this special issue on computational numerical control machining. The guest editors have extensive and complementary experiences in both academia and industry, gained in China, USA and UK

Traceability of on-machine tool measurement: a review

Nowadays, errors during the manufacturing process of high value components are not acceptable in driving industries such as energy and transportation. Sectors such as aerospace, automotive, shipbuilding, nuclear power, large science facilities or wind power need complex and accurate components that demand close measurements and fast feedback into their manufacturing processes. New measuring technologies are already available in machine tools, including integrated touch probes and fast interface capabilities. They provide the possibility to measure the workpiece in-machine during or after its manufacture, maintaining the original setup of the workpiece and avoiding the manufacturing process from being interrupted to transport the workpiece to a measuring position. However, the traceability of the measurement process on a machine tool is not ensured yet and measurement data is still not fully reliable enough for process control or product validation. The scientific objective is to determine the uncertainty on a machine tool measurement and, therefore, convert it into a machine integrated traceable measuring process. For that purpose, an error budget should consider error sources such as the machine tools, components under measurement and the interactions between both of them. This paper reviews all those uncertainty sources, being mainly focused on those related to the machine tool, either on the process of geometric error assessment of the machine or on the technology employed to probe the measurand

Simulation and Performance Test of CNC Machining Center

This project focused on checking the performance of 5 axis machining center and involved simulation of machining process and performance test of Mazak 5-axis Machining Center

Feature Based Machine Tool Accuracy Analysis Method

AbstractMachine tool accuracy is the most important performance parameters which affect the part quality. At present, a systematic machine tool accuracy evaluation method is necessary for the machine tool selection in process planning and shop-floor scheduling. This paper proposes an efficient feature based machine tool accuracy analysis method to enable machine tool capability evaluation about accuracy, and the mapping from the machine tool accuracy to the part feature tolerance is established in this method. The cutter is used as a bridge to transform the machine tool error to feature tolerance. The deviation of the cutter between the actual position & orientation and the nominal position & orientation is converted from the machine tool error according to the rigid body kinematics method. Then the feature error in the form of GD&T is calculated from the profile of the feature and the deviation of the cutter. A prototype system has been developed based on this research. An industrial case study shows that the methodology is effective

Traceable onboard metrology for machine tools and large-scale systems

Esta tesis doctoral persigue la mejora de las funcionalidades de las máquinas herramienta para la fabricación de componentes de alto valor añadido. En concreto, la tesis se centra en mejorar la precisión de las máquinas herramienta en todo su volumen de trabajo y en desarrollar el conocimiento para realizar la medición por coordenadas trazable con este medio productivo. En realidad, la tecnología para realizar mediciones en máquina herramienta ya está disponible, como son los palpadores de contacto y los softwares de medición, sin embargo, hay varios factores que limitan la trazabilidad de la medición realizada en condiciones de taller, que no permiten emplear estas medidas para controlar el proceso de fabricación o validar la pieza en la propia máquina-herramienta, asegurando un proceso de fabricación de cero-defectos. Aquí, se propone el empleo del documento técnico ISO 15530-3 para piezas de tamaño medio. Para las piezas de gran tamaño se presenta una nueva metodología basada en la guía VDI 2617-11, que no está limitada por el empleo de una pieza patrón para caracterizar el error sistemático de la medición por coordenadas en la máquina-herramienta. De esta forma, se propone una calibración previa de la máquina-herramienta mediante una solución de multilateración integrada en máquina, que se traduce en la automatización del proceso de verificación y permite reducir el tiempo y la incertidumbre de medida. En paralelo, con el conocimiento generado en la integración de esta solución en la máquina-herramienta, se propone un nuevo procedimiento para la caracterización de la precisión de apunte del telescopio LSST en todo su rango de trabajo. Este nuevo procedimiento presenta una solución automática e integrada con tecnología láser tracker para aplicaciones de gran tamaño donde la precisión del sistema es un requerimiento clave para su buen funcionamiento.<br /

Accuracy Enhancement with Processing Error Prediction and Compensation of a CNC Flame Cutting Machine Used in Spatial Surface Operating Conditions

This study deals with the precision performance of the CNC flame-cutting machine used in spatial surface operating conditions and presents an accuracy enhancement method based on processing error modeling prediction and real-time compensation. Machining coordinate systems and transformation matrix models were established for the CNC flame processing system considering both geometric errors and thermal deformation effects. Meanwhile, prediction and compensation models were constructed related to the actual cutting situation. Focusing on the thermal deformation elements, finite element analysis was used to measure the testing data of thermal errors, the grey system theory was applied to optimize the key thermal points, and related thermal dynamics models were carried out to achieve high-precision prediction values. Comparison experiments between the proposed method and the teaching method were conducted on the processing system after performing calibration. The results showed that the proposed method is valid and the cutting quality could be improved by more than 30% relative to the teaching method. Furthermore, the proposed method can be used under any working condition by making a few adjustments to the prediction and compensation models