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

Real-time control of a KEOPS-DELTA parallel kinematics machine using LinuxCNC and ETHERCAT

This paper presents a laboratory stand for investigating trajectory optimization algorithms for non-cartesian numerically controlled machines. The stand consists of a Delta machine in KEOPS configuration with linear motors controlled by high performance servo-drives. The machine is controlled by real-time control system with LinuxCNC software. The control is performed via real-time communication bus EtherCAT. The paper also describes the extension of the LinuxCNC control system with NURBS interpolaion and s-curve feedrate profiling. Also research to be performed on the machine is discussed concerning development of trajectory optimization algorithms for parallel kinematics machines.U ovom radu je predstavljena laboratorijska postavka za razvoj algoritama optimizacije trajektorije numerički upravljanih mašina alatki sa spegnutim osama. Laboratorijsku postavku čine DELTA mehanizam u KEOPS konfiguraciji sa linearnim osnaženim osama pogonjenih servo pogonima visokih performansi. Upravljanje mašinom je bazirano na LinuxCNC softverskom sistemu. Komunikacija pri upravljanju se vrši u realnom vremenu preko EtherCAT-a. U radu je takođe opisano proširenje LinuxCNC upravljačkog sistema sa NURBS interpolacijom i profilisanjem brzine pomoćnog kretanja pomoću s-krive. Dalja istraživanja će se odnositi na razvoj algoritama optimizacije trajektorije za mašine alatke sa paralelnom kinematikom

Real-time control of a KEOPS-DELTA parallel kinematics machine using LinuxCNC and ETHERCAT

This paper presents a laboratory stand for investigating trajectory optimization algorithms for non-cartesian numerically controlled machines. The stand consists of a Delta machine in KEOPS configuration with linear motors controlled by high performance servo-drives. The machine is controlled by real-time control system with LinuxCNC software. The control is performed via real-time communication bus EtherCAT. The paper also describes the extension of the LinuxCNC control system with NURBS interpolaion and s-curve feedrate profiling. Also research to be performed on the machine is discussed concerning development of trajectory optimization algorithms for parallel kinematics machines.U ovom radu je predstavljena laboratorijska postavka za razvoj algoritama optimizacije trajektorije numerički upravljanih mašina alatki sa spegnutim osama. Laboratorijsku postavku čine DELTA mehanizam u KEOPS konfiguraciji sa linearnim osnaženim osama pogonjenih servo pogonima visokih performansi. Upravljanje mašinom je bazirano na LinuxCNC softverskom sistemu. Komunikacija pri upravljanju se vrši u realnom vremenu preko EtherCAT-a. U radu je takođe opisano proširenje LinuxCNC upravljačkog sistema sa NURBS interpolacijom i profilisanjem brzine pomoćnog kretanja pomoću s-krive. Dalja istraživanja će se odnositi na razvoj algoritama optimizacije trajektorije za mašine alatke sa paralelnom kinematikom

Time-Optimal Trajectory Generation for 5-Axis On-the-Fly Laser Drilling

On-the-fly laser drilling provides a highly productive method for producing hole clusters (pre-defined groups of holes to be laser drilled) on freeform surfaced parts, such as gas turbine combustion chambers. Although the process is capable of achieving high throughputs, current machine tool controllers are not equipped with appropriate trajectory functions that can take full advantage of the achievable laser drilling speeds. While the problem of contour following has received previous attention in time-optimal trajectory generation literature, on-the-fly laser drilling presents different technological requirements, needing a different kind of trajectory optimization solution, which has not been studied prior to this thesis. The duration between consecutive hole locations, which corresponds to the laser pulsing period, has to be kept constant, ideally throughout the part program. However, the toolpath between the holes is not fixed and can be optimized to enable the shortest possible segment duration. To preserve the dynamic beam positioning accuracy and avoid inducing excessive vibrations on the laser optics, the axis velocity, acceleration, and jerk profiles need to be limited. Furthermore, to ensure that hole elongation does not violate the given part tolerances, the orthogonal component of part velocity relative to the laser beam needs to be capped. All of these requirements have been fulfilled in the trajectory optimization algorithm developed in this thesis. The hole locations are provided as pre-programmed sequences by the Computer Aided Design/Manufacturing software (CAD/CAM). A time-optimized trajectory for each sequence is planned through a series of time-scaling and unconstrained optimization operations, which guarantees a feasible solution. The initial guess for this algorithm is obtained by minimizing the integral square of the fourth time derivative (i.e. ‘snap’). The optimized trajectories for each cluster are then joined together or looped onto themselves (for repeated laser shots) using a time-optimized looping/stitching (optimized/smooth toolpath to repeat/loop a cluster or connect/stitch between consecutive clusters) algorithm. This algorithm also minimizes the integral square of jerk in the faster axes. The effectiveness of the overall solution has been demonstrated in simulations and preliminary experimental results for on-the-fly laser drilling of a hole pattern for a gas turbine combustion chamber panel. It is shown that the developed algorithm improves the cycle time for a single pass by at least 6% (from kinematic analysis of the motion duration), and more importantly reduces the integral square of jerk by 56%, which would enable the process speed to be pushed up further

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

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

Time-Optimal Feedrate Planning for Freeform Toolpaths for Manufacturing Applications

Optimality and computational efficiency are two desired yet competing attributes of time-optimal feedrate planning. A well-designed algorithm can vastly increase machining productivity, by reducing tool positioning time subject to limits of the machine tool and process kinematics. In the optimization, it is crucial to not overload the machining operation, saturate the actuators’ limits, or cause unwanted vibrations and contour errors. This presents a nonlinear optimization problem for achieving highest possible feedrates along a toolpath, while keeping the actuator level velocity, acceleration and jerk profiles limited. Methods proposed in literature either use highly elaborate nonlinear optimization solvers like Sequential Quadratic Programming (SQP), employ iterative heuristics which extends the computational time, or make conservative assumptions that reduces calculation time but lead to slower tool motion. This thesis proposes a new feedrate optimization algorithm, which combines recasting of the original problem into a Linear Programming (LP) form, and the development of a new windowing scheme to handle very long toolpaths. All constraint equations are linearized by applying B-spline discretization on the kinematic profiles, and approximating the nonlinear jerk equation with a linearized upper bound (so-called ‘pseudo-jerk’). The developed windowing algorithm first solves adjacent portions of the feed profile with zero boundary conditions at overlap points. Afterwards, using the Principle of Optimality, connection boundary conditions are identified that guarantee a feasible initial guess for blending the pre-solved adjacent feed profiles into one another, through a consecutive pass of LP. Experiments conducted at the sponsoring company of this research, Pratt & Whitney Canada (P&WC), show that the proposed algorithm is able to reliably reduce cycle time by up to 56% and 38% in two different contouring operations, without sacrificing dynamic positioning accuracy. Benchmarks carried out with respect to two earlier proposed feedrate optimization algorithms, validate both the time optimality and also drastic (nearly 60 times) reduction in the computational load, achieved with the new method. Part quality, robustness and feed drive positioning accuracy have also been validated in 3-axis surface machining of a part with 1030 waypoints and 10,000 constraint checkpoints

5-axis double-flank CNC machining of spiral bevel gears via custom-shaped milling tools -- Part I: modeling and simulation

A new category of 5-axis flank computer numerically controlled (CNC) machining, called \emph{double-flank}, is presented. Instead of using a predefined set of milling tools, we use the shape of the milling tool as a free parameter in our optimization-based approach and, for a given input free-form (NURBS) surface, compute a custom-shaped tool that admits highly-accurate machining. Aimed at curved narrow regions where the tool may have double tangential contact with the reference surface, like spiral bevel gears, the initial trajectory of the milling tool is estimated by fitting a ruled surface to the self-bisector of the reference surface. The shape of the tool and its motion then both undergo global optimization that seeks high approximation quality between the input free-form surface and its envelope approximation, fairness of the motion and the tool, and prevents overcutting. That is, our double-flank machining is meant for the semi-finishing stage and therefore the envelope of the motion is, by construction, penetration-free with the references surface. Our algorithm is validated by a commercial path-finding software and the prototype of the tool for a specific gear model is 3D printed.RYC-2017-22649 BERC 2014-201

Design and implementation issues for Stewart Platform configuration machine tools

Thesis (M.S.)--Massachusetts Institute of Technology, Dept. of Mechanical Engineering, 1997.Includes bibliographical references (leaves 56-57).by Philip J. Houdek, II.M.S

Smooth and Time-Optimal Trajectory Planning for Multi-Axis Machine Tools

This thesis presents novel methods for feedrate optimization and toolpath smoothing in CNC machining. Descriptions of the algorithms, simulation test cases, and experimental results are presented. Both feedrate optimization and toolpath smoothing are essential for increasing manufacturing efficiency while retaining part quality in CNC machining. The application of high-speed machining also necessitates the use of high feedrates, and smooth toolpaths which can be safely traversed at high feeds. However, problems occur when the feedrate is increased without check. High tracking error in machining may cause part tolerance errors. Transient vibrations due to jerky movement can lead to poor part surface quality. High speed trajectories may also demand greater torque than what the feed drives are capable of producing, which affects the motion controller’s ability to follow the trajectory correctly. The condition of the machine is also a concern, with the potential for damage or excessive wear on the machine’s components, if excessive axis velocity or jerk (i.e., rate of change of acceleration) is commanded. The feedrate scheduling algorithm developed in this thesis combines linear and nonlinear programming in a dual-windowed implementation. Linear programming (which is computationally fast) is used to quickly provide a near-optimal guess, based on axis velocity, acceleration, and jerk constraints. The solution is then refined through the use of nonlinear optimization. In the latter step, requiring more computations, the commanded motor torque and expected servo error are constrained directly, leading to shorter movement time. A windowing alignment procedure is presented which allows for these two optimization methods, each with different problem constraints and solutions horizons, to work in tandem with one another without risking infeasible boundary conditions between the windows. The algorithm is validated in simulation and experiment studies. Case studies analyzing the parameters of the optimization algorithm are also presented, and the configuration which is most computationally efficient is determined. A toolpath generation method is presented in which Euler-spiral pairs are used to smooth sharp corners, with an algorithm that integrates directly with the developed feedrate optimization The result is an exactly arc-length parametrized, G2-continuous toolpath whose axis derivatives can be computed very efficiently, which helps reduce the overall computation time. A repositioning toolpath method is also developed to reduce the cycle time of multi-layer contouring operations. This method replaces circular arc based repositioning segments between contouring passes (commonly used in industry) with a smooth Euler spiral based curve. This avoids tangent and curvature discontinuities, allowing for smoother motion with lower velocity and acceleration demands, while also reducing the overall motion. The repositioning toolpath has also been integrated with feedrate optimization and validated in simulation results