High-performance NC for high-speed machining by means of polynomial trajectories

International audienceThis paper summarises works carried out for defining tool trajectory formats well adapted to High Speed Machining (HSM). Advantages in using native polynomial formats, calculated directly from the CAD model, are highlighted. In particular, polynomial surface formats are presented as a generic format for tool trajectory. Illustrations show that surface formats represent a good compromise between smoothness machining time, and surface quality

Angular approach combined to mechanical model for tool breakage detection by eddy current sensors

International audienceThe paper presents a new complete approach for Tool Condition Monitoring (TCM) in milling. The aim is the early detection of small damages so that catastrophic tool failures are prevented. A versatile in-process monitoring system is introduced for reliability concerns. The tool condition is determined by estimates of the radial eccentricity of the teeth. An adequate criterion is proposed combining mechanical model of milling and angular approach. Then, a new solution is proposed for the estimate of cutting force using eddy current sensors implemented close to spindle nose. Signals are analysed in the angular domain, notably by synchronous averaging technique. Phase shifts induced by changes of machining direction are compensated. Results are compared with cutting forces measured with a dynamometer table. The proposed method is implemented in an industrial case of pocket machining operation. One of the cutting edges has been slightly damaged during the machining, as shown by a direct measurement of the tool. A control chart is established with the estimates of cutter eccentricity obtained during the machining from the eddy current sensors signals. Efficiency and reliability of the method is demonstrated by a successful detection of the damage

A new versatile in-process monitoring system for milling

International audienceTool condition monitoring (TCM) systems can improve productivity and ensure workpiece quality, yet, there is a lack of reliable TCM solutions for small-batch or one-off manufacturing of industrial parts. TCM methods which include the characteristics of the cut seem to be particularly suitable for these demanding applications. In the first section of this paper, three process-based indicators have been retrieved from literature dealing with TCM. They are analysed using a cutting force model and experiments are carried out in industrial conditions. Specific transient cuttings encountered during the machining of the test part reveal the indicators to be unreliable. Consequently, in the second section, a versatile in-process monitoring method is suggested. Based on experiments carried out under a range of different cutting conditions, an adequate indicator is proposed: the relative radial eccentricity of the cutters is estimated at each instant and characterizes the tool state. It is then compared with the previous tool state in order to detect cutter breakage or chipping. Lastly, the new approach is shown to be reliable when implemented during the machining of the test part

A Tailored Ontology Supporting Sensor Implementation for the Maintenance of Industrial Machines

International audienceThe longtime productivity of an industrial machine is improved by condition-based maintenance strategies. To do this, the integration of sensors and other cyber-physical devices is necessary in order to capture and analyze a machine's condition through its lifespan. Thus, choosing the best sensor is a critical step to ensure the efficiency of the maintenance process. Indeed, considering the variety of sensors, and their features and performance, a formal classification of a sensor's domain knowledge is crucial. This classification facilitates the search for and reuse of solutions during the design of a new maintenance service. Following a Knowledge Management methodology, the paper proposes and develops a new sensor ontology that structures the domain knowledge, covering both theoretical and experimental sensor attributes. An industrial case study is conducted to validate the proposed ontology and to demonstrate its utility as a guideline to ease the search of suitable sensors. Based on the ontology, the final solution will be implemented in a shared repository connected to legacy CAD (computer-aided design) systems. The selection of the best sensor is, firstly, obtained by the matching of application requirements and sensor specifications (that are proposed by this sensor repository). Then, it is refined from the experimentation results. The achieved solution is recorded in the sensor repository for future reuse. As a result, the time and cost of the design process of new condition-based maintenance services is reduced

Complete Analytical Expression of the Stiffness Matrix of Angular Contact Ball Bearings

International audienceAngular contact ball bearings are predominantly used for guiding high speed rotors such as machining spindles. For an accurate modelling, dynamic effects have to be considered, most notably in the bearings model. The paper is based on a dynamic model of angular contact ball bearings. Different kinematic hypotheses are discussed. A new method is proposed for the computation of the stiffness matrix: a complete analytical expression including dynamic effects is presented in order to ensure accuracy at high shaft speed. It is demonstrated that the new method leads to the exact solution, contrary to the previous ones. Besides, the computational cost is similar. The new method is then used to investigate the consequence of the kinematic hypotheses on bearing stiffness values. Last, the relevance of this work is illustrated through the computation of the dynamic behavior of a high speed milling spindle. The impact of this new computation method on the accuracy of a finite element spindle model is quantified

Elasto-Dynamic Model of Robotic Milling Process Considering Interaction between Tool and Workpiece

International audienceIn this paper, a reduced elasto-dynamic model of the robotic based milling process is presented. In contrast to previous works, it takes into account the interaction between the milling tool and the workpiece that depends on the end-effector position, process parameters and cutting conditions (spindle rotation, feed rate, geometry of the tool, etc.). To reduce the dimension of the problem, the robot dynamics is described as an equivalent mass-spring-damper system with six dimensions. This approach, based on the Rayleigh-Ritz approximation, aims at decreasing computational cost and at avoiding inaccuracy due to ill-conditioning in the full size model. To achieve a realistic modeling of the milling process, the machining efforts due to the interaction between robot, tool and working material are introduced into the robot model and calculated at each time instant. Using this global model that integrates the robot dynamics and the milling process particularities, it is possible to obtain the movement of the robot end-effector and corresponding quality of the final product (profile, macro geometry, etc.). In addition, this model allows selecting the best process parameters and avoiding the vibratory behavior of this machining system which can dramatically affect the milling quality. The developed model is applied to the behavior analysis of KUKA KR270 robot used for milling applications. This allows finding acceptable range for robot motion profile parameters

Cutting force model for machining of CFRP laminate with diamond abrasive cutter

The article presents a cutting force model for trimming operations of CFRP laminate with diamond abrasive cutters. Those tools are more and more encountered on industrial applications of CFRP trimming, due to their abrasion resistance and their low cost. Contrary to endmills, they consist of a large number of cutting grits, randomly distributed around the tool. To tackle the issue, a continuous model of tool engagement is proposed. Validity of the approach is verified. A mechanical model of cutting forces, adapted to CFRP laminate, is then presented. The evolution of specific cutting coefficient in relation to fibres orientation is investigated through a piecewise constant model. It leads to the proposal of a sine model for the specific cutting coefficients. The simulated forces are in good agreement with the experimental results of cutting tests, carried out in multidirectional CFRP laminate for different fibres orientation and widths of cut. Cutting mechanisms are finally discussed depending on fibres orientation

Analyse de l'exploitation des broches en UGV aéronautique

Le fraisage grande vitesse des pièces aéronautiques de grandes dimensions nécessite à la fois un taux d'enlèvement de copeaux important ainsi qu'une qualité de finition garantissant les tolérances de ces pièces à haute valeur ajoutée. Implantées sur des machines outils UGV, les électrobroches doivent supporter, sur des phases d'usinage de plusieurs heures, des sollicitations physiques importantes. Malgré les avancées technologiques, les broches apparaissent aujourd'hui comme le maillon faible des machines d'usinage à grande vitesse aéronautique. Ce papier propose un concept innovant de surveillance des broches d'UGV qui permet de suivre l'usure de celles-ci, particulièrement au niveau de leurs roulements à billes, cause principale de leurs défaillances. Pour cela des broches FISCHER ont été instrumentées de plusieurs accéléromètres, puis intégrées sur machines FOREST-LINE. Grâce aux signaux vibratoires enregistrés par un système de surveillance conçu spécifiquement et à partir d'un état de l'art sur la surveillance des roulements que nous avons réalisés, un critère vibratoire adapté au suivi de l'état des paliers des broches a été développé. De plus, les signaux et informations enregistrés lors de l'usinage par le même système de surveillance permettent de relier l'endommagement des roulements aux sollicitations subies par la broche lors de son utilisation afin d'assurer aussi une réelle surveillance du procédé en lui-même

Classification contextuelle pour système d'aide à la décision pour machines-outils

International audienceDans le contexte général de l'Industrie 4.0, une entreprise de fabrication moderne dispose de nombreuses données numériques qui pourraient être utilisées pour rendre les machines-outils plus intelligentes et faciliter la prise de décision en matière de gestion opérationnelle. L'une des premières étapes de l'approche d'exploration de données est la sélection précise de données pertinentes. Pour ce faire, les données brutes doivent être classées dans différents groupes de contextes. Cet article présente une étude comparative d'algorithmes d'apprentissage automatique non-supervisé pour la classification contextuelle ; qui est utile pour un système d'aide à la décision pour machines-outils. Les vérifications par fouilles manuelles montrent que la méthode GMM permet d'obtenir de bons résultats de classification contextuelle, contrairement à celle des K-means. Mots-clés-UGV, Industrie 4.0, apprentissage non-supervisé