Evaluation of servo, geometric and dynamic error sources on five axis high-speed machine tool

Many sources of errors exist in the manufacturing process of complex shapes. Some approximations occur at each step from the design geometry to the machined part. The aim of the paper is to present a method to evaluate the effect of high speed and high dynamic load on volumetric errors at the tool center point. The interpolator output signals and the machine encoder signals are recorded and compared to evaluate the contouring errors resulting from each axis follow-up error. The machine encoder signals are also compared to the actual tool center point position as recorded with a non-contact measuring instrument called CapBall to evaluate the total geometric errors. The novelty of the work lies in the method that is proposed to decompose the geometric errors in two categories: the quasi-static geometric errors independent from the speed of the trajectory and the dynamic geometric errors, dependent on the programmed feed rate and resulting from the machine structure deflection during the acceleration of its axes. The evolution of the respective contributions for contouring errors, quasi-static geometric errors and dynamic geomet- ric errors is experimentally evaluated and a relation between programmed feed rate and dynamic errors is highlighted.Comment: 13 pages; International Journal of Machine Tools and Manufacture (2011) pp XX-X

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

On-machine identification of rotary axis location errors under thermal influence by spindle rotation

Position and orientation errors of rotary axis average lines are often among dominant error contributors in the five-axis kinematics. Although many error calibration schemes are available to identify them on -machine, they cannot be performed when a machine spindle is rotating. Rotary axis location errors are often influenced by the machine’s thermal deformation. This paper presents the application of a non-contact laser light barrier system, widely used in the industry for tool geometry measurement, to the identification of rotary axis location errors, when the spindle rotates in the same speed as in actual machining applications. The effectiveness of the proposed scheme is verified by experimental comparison with the R-Test and a machining test. The uncertainty analysis is also presented.This work was supported by JSPS KAKENHI Grant NumberJP15K05721

The use of a Laser Tracker and a Self-centring Probe for Rotary Axis Verification

This paper presents a small collection of tests related with the analysis of a rotary axis according to ISO 230-7 but introducing two alternative equipments briefly explaining each method. The disadvantages of the methods in which the movement of a rotary axis engages the translational axes of a Machine Tool are expressed, which leads to the proposed study. The errors of a rotary axis are described as established in standards and the measurement procedures carried out in the tests for verification of a rotary indexing table, based on the use of a self-centring probe and a laser tracker, are explained. Also, the necessary elements setup for measurement are described. Then, the followed calculation process of the measured errors is explained in detail. Finally, the results of the most significant errors obtained from the test measurements are presented

Static stiffness modeling and sensitivity analysis for geared system used for rotary feeding

The positioning accuracy of rotary feed system under load greatly depends on the static stiffness of mechanical transmission system. This paper proposes a unified static stiffness model of rotary feed system with geared transmission system. Taking the torsional stiffness of transmission shaft and mesh stiffness of gear pairs into account, the motion equations of the whole transmission system are presented. Based on the static equilibrium, a unified expression for the relationship between torsional angles of two adjacent elements is derived. Then a unified static stiffness model is presented. Furthermore, analytical expressions for sensitivity analysis of the static stiffness on the individual element’s stiffness and design parameters are derived. The presented model is verified by a traditional model, and a good agreement is obtained. The influence of phase angle of meshing gear pairs on the resultant static stiffness is investigated. An example transmission system is employed to perform the sensitivity analysis and the results are analyzed. The proposed model provides an essential tool for the design of rotary feed system satisfying requirement of static stiffness

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 /

Étalonnage des machines-outils à cinq axes : configuration optimisée des artefacts et de la séquence de mesure de la méthode SAMBA en vue d'une estimation efficace des erreurs géométriques

RÉSUMÉ Les machines-outils à commande numérique (MOCN) sont assujetties à plusieurs sources d’erreurs, entre autres géométriques, thermiques et dynamiques qui peuvent contribuer à la dégradation de leurs performances. Une attention particulière est prêtée à l’usinage multi axes où le mouvement simultané des axes prismatiques et rotatifs engendre une erreur de positionnement et d’orientation de l’outil par rapport au point à usiner sur la pièce. Des moyens d’évaluations de ces erreurs et de leurs causes, à des fins de maintenance et de compensation, sont alors à développer en tenant compte des aspects économiques, techniques et humains. Il s’agit en particulier de minimiser les temps de mesures qui résultent en des arrêts de production et par conséquent des coûts indirects à éviter à l’entreprise. Le but de la présente thèse est d’améliorer la précision d’une machine-outil à cinq axes à travers l’optimisation d’une technique d’étalonnage existante. En vue de prédire au mieux le comportement de la machine, l’élaboration d’une routine d’inspection adéquate est nécessaire. Ceci comprend un positionnement optimal des éléments du dispositif de mesure, sous forme de billes de référence, ainsi qu’une planification judicieuse des poses de palpage dans l’espace de travail. Une approche analytique basée sur un algorithme d’échange pour la conception d’un plan D-optimal est adoptée pour générer des scénarios d’étalonnage en fonction des écarts géométriques à estimer, modélisés sous forme de polynôme, et du nombre d’inconnues définissant le modèle de la machine. L’évaluation de la pertinence des tests est effectuée à partir d’une étude comparative de critères appelés communément en robotique, indices d’observabilité, issus de l’analyse de la matrice jacobienne d’identification. La qualité prédictive des séquences de mesures générées par simulation est validée en deux étapes : la première consiste en des expériences de répétabilité des tests optimisés imbriqués, la deuxième est une analyse de l’incertitude sur les tests et les paramètres d’erreurs identifiés. Une validation par mesure directe d’une cale calibrée, montée sur la table de la machine, permet de confirmer les résultats qualitatifs fournis par l’indice d’observabilité et ceux quantitatifs déduits de l’estimation de l’incertitude. Les résultats montrent que les routines de vérification proposées sont capables de donner une description complète de la géométrie imparfaite de la machine en incluant les écarts de membrures et les écarts cinématiques. Une amélioration de 55.7% de la valeur de l’indice d’observabilité est constatée par rapport à celle de la stratégie de mesure utilisée présentement dans le laboratoire.----------ABSTRACT Numerically controlled machine tools are prone to potential geometric, thermal and dynamic errors that can have a negative impact on their performance. A careful attention is paid to multi-axis machining where the simultaneous movement of prismatic and rotary axes lead to a positioning and orientation deviation of the tool relative to the workpiece. Tools for assessing these errors and their causes, for maintenance and compensation purposes, are to be developed while taking into consideration economic, technical and human aspects. In particular, this involves minimizing the measurement duration which results in production downtimes and consequently indirect costs to be avoided by the company. This thesis aims to improve the accuracy of a five-axis machine tool through the optimization of an existing calibration technique. For a better prediction of the machine tool erroneous behavior, an adequate inspection routine is sought. This includes optimal positioning of the measuring device components, i.e. master balls, as well as a wise planning of the probing poses in the working volume. An analytical approach based on an exchange algorithm for a D-optimal design is carried out to generate calibration scenarios based on the estimated geometric errors, described as ordinary polynomials, and the number of unknowns predefined in the machine model. The evaluation of the optimized tests suitability relies on a comparison of criteria, commonly known in the robotics field as observability indices and are the outcome of the identification Jacobian matrix analysis. Simulation results are validated in two steps: the first one consists of a repeatability testing of nested optimized probing sequences while the second one is an analysis of the estimated uncertainty on the overall tests and the identified error parameters. Validation via a direct measuring of a calibrated gauge block, mounted on the machine workpiece, confirms the qualitative results provided by the observability index and the quantitative ones concluded from the uncertainty estimation. The outcome suggests that the proposed geometric model updating routines enable a comprehensive description of the machine tool behavior by including location errors and error motions. An improvement of 55.7% of the observability index value is depicted with respect to the currently used measurement strategy. The optimal calibration test duration varies between 30 minutes while probing one master ball for axes location errors identification and 2 hours and 18 minutes for the estimation of both axes location errors and error motions while measuring an artefact of three master balls

Machine tool volumetric error features extraction and classification using principal component analysis and K-means

Volumetric errors (VE) are related to the machine tool accuracy state. Extracting features from the complex VE data provides with a means to characterize this data. VE feature classification can reveal the machine tool accuracy states. This paper presents a study on how to use principal component analysis (PCA) to extract the features of VE and how to use the K-means method for machine tool accuracy state classification. The proposed data processing methods have been tested with the VE data acquired from a five-axis machine tool with different states of malfunction. The results indicate that the PCA and K-means are capable of extracting the VE feature information and classifying the fault states including the C axis encoder fault, uncalibrated C axis encoder fault, and pallet location fault from the machine tool normal states. This research provides a new way for VE features extraction and classification