Automated CNC Tool Path Planning and Machining Simulation on Highly Parallel Computing Architectures

This work has created a completely new geometry representation for the CAD/CAM area that was initially designed for highly parallel scalable environment. A methodology was also created for designing highly parallel and scalable algorithms that can use the developed geometry representation. The approach used in this work is to move parallel algorithm design complexity from an algorithm level to a data representation level. As a result the developed methodology allows an easy algorithm design without worrying too much about the underlying hardware. However, the developed algorithms are still highly parallel because the underlying geometry model is highly parallel. For validation purposes, the developed methodology and geometry representation were used for designing CNC machine simulation and tool path planning algorithms. Then these algorithms were implemented and tested on a multi-GPU system. Performance evaluation of developed algorithms has shown great parallelizability and scalability; and that main algorithm properties are required for modern highly parallel environment. It was also proved that GPUs are capable of performing work an order of magnitude faster than traditional central processors. The last part of the work demonstrates how high performance that comes with highly parallel hardware can be used for development of a next level of automated CNC tool path planning systems. As a proof of concept, a fully automated tool path planning system capable of generating valid G-code programs for 5-axis CNC milling machines was developed. For validation purposes, the developed system was used for generating tool paths for some parts and results were used for machining simulation and experimental machining. Experimental results have proved from one side that the developed system works. And from another side, that highly parallel hardware brings computational resources for algorithms that were not even considered before due to computational requirements, but can provide the next level of automation for modern manufacturing systems

Volumetric Error-Based Condition and Health Monitoring System for Machine-Tools

Résumé Des défaillances ou détériorations imprévues ou non détectées des machines-outils entraînent des pertes de production et de qualité, d'où la nécessité d'une maintenance prescriptive et normative utilisant la surveillance de l'état des machines-outils. Cette recherche présente la méthodologie et les solutions développées pour surveiller l’état de précision des machines-outils à cinq axes en analysant les erreurs volumétriques de la machine-outil. L’erreur volumétrique est définie comme un vecteur d'erreur cartésien représentant l'écart de la position réelle de l'outil par rapport à sa position attendue par rapport au repère de la pièce et projeté dans le repère de base. La méthode SAMBA (Scale and Master Ball Artefact) a été utilisée pour mesurer les erreurs volumétriques de la machine-outil expérimentale à cinq axes. Les erreurs volumétriques acquises contenant les états normaux et défectueux de la machine-outil constituent la base de données pour cette recherche. De plus, des pseudo-fautes et les fautes graduelles et soudaines simulées ont également été utilisées. Les caractéristiques du vecteur d'erreurs volumétriques extraites par des mesures de similarité de vecteur sont utilisées comme entrée pour le graphique de contrôle basé sur les moyennes mobiles pondérées exponentiellement, où le changement anormal du vecteur unique d'erreurs volumétriques peut être détecté. Pour surveiller de manière exhaustive l’état de précision de la machine-outil, une matrice de mesures de similarité vectorielle combinée contenant toutes les caractéristiques d’erreurs volumétriques acquises a été proposée et traitée par le graphique de contrôle de la moyenne mobile pondérée exponentiellement. Pour les mêmes défauts, les deux traitements de données ci-dessus peuvent tous détecter automatiquement le temps exact d’apparition du défaut. Sur la base d'une logique de surveillance complète des erreurs volumétriques, une analyse fractale des coordonnées d'erreur volumétrique a également été explorée. Les résultats des tests révèlent qu’il s’agit d’un outil efficace pour représenter la fonctionnalité des erreurs volumétriques. Pour comprendre le processus de changement de l'état de la machine-outil, les erreurs volumétriques historiques acquises ont été traitées par analyse en composantes principales et par K-moyennes. D'une part, les méthodes proposées séparent les états normaux et défectueux de la machine-outil (près de 100%), d'autre part, les machines-outils désignées fournissent les références pour la reconnaissance de l'état d’autre machines-outils lors du traitement de nouvelles données d'erreurs volumétriques. En résumé, le travail de recherche effectué dans cette thèse a contribué à la mise au point d’une solution efficace de surveillance de l’état de la précision des machines-outils à l’aide des erreurs volumétriques des machines-outils, basées sur des méthodes d’extraction de caractéristiques, de reconnaissance des modifications et de classification des états. Le système développé peut reconnaître les points de changement exacts des défauts réels du codeur d'axe C, des pseudo-défauts EXX et EYX. De plus, il atteint une précision proche de 100% dans la classification de l'état défectueux et normal de la machine-outil. ---------- Abstract Unexpected or undetected machine tool failures or deterioration results in production and quality losses, hence proactive and prescriptive maintenance using machine tool condition monitoring is sought. This research presents the methodology and solutions developed to monitor the accuracy state of five-axis machine tools by analyzing the machine tool volumetric errors which are defined as the Cartesian error vector of the deviation of the actual tool position compared to its expected position relative to the workpiece frame and projected into the foundation frame. The scale and master ball artefact (SAMBA) method has been used for the measurement of volumetric errors of the experimental five-axis machine tool. The acquired volumetric errors containing machine tool normal and faulty states provide the database for this research. In addition, pseudo-faults and the simulated gradual and sudden faults have also been used. Volumetric error vector features extracted by vector similarity measures are used as the input for the exponential weight moving average control chart where the abnormal change of the single volumetric error vector can be detected. To comprehensively monitor the machine tool accuracy state, a combined vector similarity measure array containing all acquired volumetric errors features has been proposed and processed by the exponential weight moving average control chart. Towards the same faults, the above two data processing can all automatically detect the exact fault occurrence time. Based on the logic of comprehensive monitoring of volumetric errors, fractal analysis of volumetric error coordinates has also been explored. The testing results reveal that it is an effective tool for volumetric errors features representing. To understand the change process of the machine tool state, the acquired historical volumetric errors have been processed by principal component analysis and K-means. For one thing, the proposed methods separate the normal and faulty states of the machine tool (Nearly 100%), for another thing, the designated machine tools provide the references for machine tools state recognition when processing new volumetric errors data. In summary, this research contributed to the development of an efficient solution for machine tool accuracy state monitoring using machine tools volumetric errors based on feature extraction, change recognition and state classification methods. The developed system can recognize the exact change points of real C-axis encoder faults, pseudo-faults EXX and EYX. In addition, it achieves close to 100% accuracy in machine tool faulty and normal state classification

Manufacturing Metrology

Metrology is the science of measurement, which can be divided into three overlapping activities: (1) the definition of units of measurement, (2) the realization of units of measurement, and (3) the traceability of measurement units. Manufacturing metrology originally implicates the measurement of components and inputs for a manufacturing process to assure they are within specification requirements. It can also be extended to indicate the performance measurement of manufacturing equipment. This Special Issue covers papers revealing novel measurement methodologies and instrumentations for manufacturing metrology from the conventional industry to the frontier of the advanced hi-tech industry. Twenty-five papers are included in this Special Issue. These published papers can be categorized into four main groups, as follows: Length measurement: covering new designs, from micro/nanogap measurement with laser triangulation sensors and laser interferometers to very-long-distance, newly developed mode-locked femtosecond lasers. Surface profile and form measurements: covering technologies with new confocal sensors and imagine sensors: in situ and on-machine measurements. Angle measurements: these include a new 2D precision level design, a review of angle measurement with mode-locked femtosecond lasers, and multi-axis machine tool squareness measurement. Other laboratory systems: these include a water cooling temperature control system and a computer-aided inspection framework for CMM performance evaluation

Calibration and Control of a Redundant Robotic Workcell for Milling Tasks

This article deals with the tuning of a complex robotic workcell of eight joints devoted to milling tasks. It consists of a KUKA (TM) manipulator mounted on a linear track and synchronised with a rotary table. Prior to any machining, the additional joints require an in situ calibration in an industrial environment. For this purpose, a novel planar calibration method is developed to estimate the external joint configuration parameters by means of a laser displacement sensor and avoiding direct contact with the pattern. Moreover, a redundancy resolution scheme on the joint rate level is integrated within a computer aided manufacturing system for the complete control of the workcell during the path tracking of a milling task. Finally, the whole system is tested in the prototyping of an orographic model.Andres De La Esperanza, FJ.; Gracia Calandin, LI.; Tornero Montserrat, J. (2011). Calibration and Control of a Redundant Robotic Workcell for Milling Tasks. International Journal of Computer Integrated Manufacturing. 24(6):561-573. doi:10.1080/0951192X.2011.566284S56157324

A novel haptic model and environment for maxillofacial surgical operation planning and manipulation

This paper presents a practical method and a new haptic model to support manipulations of bones and their segments during the planning of a surgical operation in a virtual environment using a haptic interface. To perform an effective dental surgery it is important to have all the operation related information of the patient available beforehand in order to plan the operation and avoid any complications. A haptic interface with a virtual and accurate patient model to support the planning of bone cuts is therefore critical, useful and necessary for the surgeons. The system proposed uses DICOM images taken from a digital tomography scanner and creates a mesh model of the filtered skull, from which the jaw bone can be isolated for further use. A novel solution for cutting the bones has been developed and it uses the haptic tool to determine and define the bone-cutting plane in the bone, and this new approach creates three new meshes of the original model. Using this approach the computational power is optimized and a real time feedback can be achieved during all bone manipulations. During the movement of the mesh cutting, a novel friction profile is predefined in the haptical system to simulate the force feedback feel of different densities in the bone

Characterising geometric errors in rotary axes of 5-axis machine tools

It is critical to ensure that a 5-axis machine tool is operating within its geometric tolerance. However, there are various sources of errors influencing its accuracy; testing them with current methods requires expensive equipment and long machine down time. This motivates the development of a simple and fast way to identify and characterise geometric errors of 5-axis machine tools. A method using a Double Ball Bar (DBB) is proposed to characterise rotary axes Position Independent Geometric Errors (PIGEs), which are caused by imperfections during assembly of machine components. An established method is used to test the same PIGEs, and the results are used to validate the developed method. The Homogeneous Transformation Matrices (HTMs) are used to build up a machine tool model and generate DBB error plots due to different PIGEs based on the given testing scheme. The simulated DBB trace patterns can be used to evaluate individual error impacts for known faults and diagnose machine tool conditions. The main contribution is the development of the fast and simple characterisation of the PIGEs of rotary axes. The results show the effectiveness and improved efficiency of the new methods, which can be considered for 5-axis machine tool maintenance and checking

Postprocesamiento CAM-ROBOTICA orientado al prototipado y mecanizado en células robotizadas complejas

The main interest of this thesis consists of the study and implementation of postprocessors to adapt the toolpath generated by a Computer Aided Manufacturing (CAM) system to a complex robotic workcell of eight joints, devoted to the rapid prototyping of 3D CAD-defined products. It consists of a 6R industrial manipulator mounted on a linear track and synchronized with a rotary table. To accomplish this main objective, previous work is required. Each task carried out entails a methodology, objective and partial results that complement each other, namely: - It is described the architecture of the workcell in depth, at both displacement and joint-rate levels, for both direct and inverse resolutions. The conditioning of the Jacobian matrix is described as kinetostatic performance index to evaluate the vicinity to singular postures. These ones are analysed from a geometric point of view. - Prior to any machining, the additional external joints require a calibration done in situ, usually in an industrial environment. A novel Non-contact Planar Constraint Calibration method is developed to estimate the external joints configuration parameters by means of a laser displacement sensor. - A first control is originally done by means of a fuzzy inference engine at the displacement level, which is integrated within the postprocessor of the CAM software. - Several Redundancy Resolution Schemes (RRS) at the joint-rate level are compared for the configuration of the postprocessor, dealing not only with the additional joints (intrinsic redundancy) but also with the redundancy due to the symmetry on the milling tool (functional redundancy). - The use of these schemes is optimized by adjusting two performance criterion vectors related to both singularity avoidance and maintenance of a preferred reference posture, as secondary tasks to be done during the path tracking. Two innovative fuzzy inference engines actively adjust the weight of each joint in these tasks.Andrés De La Esperanza, FJ. (2011). Postprocesamiento CAM-ROBOTICA orientado al prototipado y mecanizado en células robotizadas complejas [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/10627Palanci

Discrete modeling of sculptured surface machining for robust automatic feedrate selection

Traditional feedrate selection techniques currently used in three and five-axis CNC machining reduces milling efficiency. Manually estimated feedrates tend to be conservative and constant, greatly increasing mill time. The goal of this research is to develop robust techniques and software tools for automatically generating optimized feedrates for use on three and five-axis CNC mills, to both simplify the feed selection process and to increase the safety and efficiency of the milling operation through milling process simulation. The simulation software estimates milling force vectors for each tool move, and identifies a feedrate that maintains a desired peak force. The desired cutting force value may be selected to prevent cutter breakage, maintain part tolerance, or meet some other criteria. Other conditions are also considered, such as maximum allowable chip thickness and machine constraints. This allows for the generation of variable feedrates that are optimized for each tool move. The software consists of three distinct portions: a discrete mechanistic model, a discrete geometric model, and a CNC machine model. The mechanistic model estimates cutting forces as a function of cut geometry, cutter/stock relative velocity, and material constants. The geometric model keeps track of the changing in-process stock geometry and provides the cut geometry parameters required by the mechanistic model. The CNC machine model calculates the cutter/stock relative velocity based on feed inputs, machine kinematics, and controller behavior. A feed value is calculated in an iterative manner for each tool move based on the force estimates. The results of this research have produced accurate force estimates during sculptured surface machining, and have also demonstrated that this approach at automatic feedrate selection is feasible. Testing of feedrate selection has included the five-axis milling of production turbomachinery in an industrial environment. An average improvement in efficiency of 20% has resulted from the use of the optimized feeds