Novel control approaches for the next generation computer numerical control (CNC) system for hybrid micro-machines

It is well-recognised that micro-machining is a key enabling technology for manufacturing high value-added 3D micro-products, such as optics, moulds/dies and biomedical implants etc. These products are usually made of a wide range of engineering materials and possess complex freeform surfaces with tight tolerance on form accuracy and surface finish.In recent years, hybrid micro-machining technology has been developed to integrate several machining processes on one platform to tackle the manufacturing challenges for the aforementioned micro-products. However, the complexity of system integration and ever increasing demand for further enhanced productivity impose great challenges on current CNC systems. This thesis develops, implements and evaluates three novel control approaches to overcome the identified three major challenges, i.e. system integration, parametric interpolation and toolpath smoothing. These new control approaches provide solid foundation for the development of next generation CNC system for hybrid micro-machines.There is a growing trend for hybrid micro-machines to integrate more functional modules. Machine developers tend to choose modules from different vendors to satisfy the performance and cost requirements. However, those modules often possess proprietary hardware and software interfaces and the lack of plug-and-play solutions lead to tremendous difficulty in system integration. This thesis proposes a novel three-layer control architecture with component-based approach for system integration. The interaction of hardware is encapsulated into software components, while the data flow among different components is standardised. This approach therefore can significantly enhance the system flexibility. It has been successfully verified through the integration of a six-axis hybrid micro-machine. Parametric curves have been proven to be the optimal toolpath representation method for machining 3D micro-products with freeform surfaces, as they can eliminate the high-frequency fluctuation of feedrate and acceleration caused by the discontinuity in the first derivatives along linear or circular segmented toolpath. The interpolation for parametric curves is essentially an optimization problem, which is extremely difficult to get the time-optimal solution. This thesis develops a novel real-time interpolator for parametric curves (RTIPC), which provides a near time-optimal solution. It limits the machine dynamics (axial velocities, axial accelerations and jerk) and contour error through feedrate lookahead and acceleration lookahead operations. Experiments show that the RTIPC can simplify the coding significantly, and achieve up to ten times productivity than the industry standard linear interpolator. Furthermore, it is as efficient as the state-of-the-art Position-Velocity-Time (PVT) interpolator, while achieving much smoother motion profiles.Despite the fact that parametric curves have huge advantage in toolpath continuity, linear segmented toolpath is still dominantly used on the factory floor due to its straightforward coding and excellent compatibility with various CNC systems. This thesis presents a new real-time global toolpath smoothing algorithm, which bridges the gap in toolpath representation for CNC systems. This approach uses a cubic B-spline to approximate a sequence of linear segments. The approximation deviation is controlled by inserting and moving new control points on the control polygon. Experiments show that the proposed approach can increase the productivity by more than three times than the standard toolpath traversing algorithm, and 40% than the state-of-the-art corner blending algorithm, while achieving excellent surface finish.Finally, some further improvements for CNC systems, such as adaptive cutting force control and on-line machining parameters adjustment with metrology, are discussed in the future work section.It is well-recognised that micro-machining is a key enabling technology for manufacturing high value-added 3D micro-products, such as optics, moulds/dies and biomedical implants etc. These products are usually made of a wide range of engineering materials and possess complex freeform surfaces with tight tolerance on form accuracy and surface finish.In recent years, hybrid micro-machining technology has been developed to integrate several machining processes on one platform to tackle the manufacturing challenges for the aforementioned micro-products. However, the complexity of system integration and ever increasing demand for further enhanced productivity impose great challenges on current CNC systems. This thesis develops, implements and evaluates three novel control approaches to overcome the identified three major challenges, i.e. system integration, parametric interpolation and toolpath smoothing. These new control approaches provide solid foundation for the development of next generation CNC system for hybrid micro-machines.There is a growing trend for hybrid micro-machines to integrate more functional modules. Machine developers tend to choose modules from different vendors to satisfy the performance and cost requirements. However, those modules often possess proprietary hardware and software interfaces and the lack of plug-and-play solutions lead to tremendous difficulty in system integration. This thesis proposes a novel three-layer control architecture with component-based approach for system integration. The interaction of hardware is encapsulated into software components, while the data flow among different components is standardised. This approach therefore can significantly enhance the system flexibility. It has been successfully verified through the integration of a six-axis hybrid micro-machine. Parametric curves have been proven to be the optimal toolpath representation method for machining 3D micro-products with freeform surfaces, as they can eliminate the high-frequency fluctuation of feedrate and acceleration caused by the discontinuity in the first derivatives along linear or circular segmented toolpath. The interpolation for parametric curves is essentially an optimization problem, which is extremely difficult to get the time-optimal solution. This thesis develops a novel real-time interpolator for parametric curves (RTIPC), which provides a near time-optimal solution. It limits the machine dynamics (axial velocities, axial accelerations and jerk) and contour error through feedrate lookahead and acceleration lookahead operations. Experiments show that the RTIPC can simplify the coding significantly, and achieve up to ten times productivity than the industry standard linear interpolator. Furthermore, it is as efficient as the state-of-the-art Position-Velocity-Time (PVT) interpolator, while achieving much smoother motion profiles.Despite the fact that parametric curves have huge advantage in toolpath continuity, linear segmented toolpath is still dominantly used on the factory floor due to its straightforward coding and excellent compatibility with various CNC systems. This thesis presents a new real-time global toolpath smoothing algorithm, which bridges the gap in toolpath representation for CNC systems. This approach uses a cubic B-spline to approximate a sequence of linear segments. The approximation deviation is controlled by inserting and moving new control points on the control polygon. Experiments show that the proposed approach can increase the productivity by more than three times than the standard toolpath traversing algorithm, and 40% than the state-of-the-art corner blending algorithm, while achieving excellent surface finish.Finally, some further improvements for CNC systems, such as adaptive cutting force control and on-line machining parameters adjustment with metrology, are discussed in the future work section

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

Process dependent path planning for machining with industrial robots

The use of industrial robots in machining operations, such as milling, is an area of growing interest due to potential workflow and efficiency benefits. However, the inherent mechanical design of robot manipulators results in low stiffness and easy-to-excite dynamics when compared to the traditionally used \gls{cnc} machines. While research exists to compensate for deficiencies in robot manipulators, such as trajectory planning, online and offline error compensation, no integrated solution combining process-force compensation, robotic trajectory planning, and online error compensation exists, as would be required for industrial settings. This thesis introduces a deflection-limited trajectory planning algorithm for curvilinear slotting and linear peripheral milling cuts. The research purpose is to develop a solution involving a variable feed rate trajectory that limits the deflection-induced part errors when milling with an industrial robot. Thus, given a set of points to be approximated into a path, the methodology in this thesis generates a process-aware trajectory in which feed-rate has been adjusted to meet a user-specified deflection limit. The trajectory is formatted to be compatible with a closed-loop feedback and communication system with the industrial robot. Experiments are conducted using a large (range of 2855 mm), industrial robot milling system controlled by a closed-loop, laser tracker feedback system. Experimental data supports that the deflection-limited variable feed rate trajectory provides better part accuracy and surface roughness than the constant feed rate case. Furthermore, the variable feed rate trajectory executed by the closed-loop system maintains better positional accuracy than the open-loop, native robot controller using native motion types. Thus, the merit of a process dependent trajectory planner is argued, and future work for improvements and use-case generalization is suggested.M.S

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

Machining Speed Gains in a 3-Axis CNC Lathe Mill

The intent of this work is to improve the machining speed of an existing 3 axis CNC wood working lathe. This lathe is unique in that it is a modi ed manual lathe that is capable of machining complex sculptured surfaces. The current machining is too slow for the lathe to be considered useful in an industrial setting. To improve the machining speed of the lathe, several modi cations are made to the mechanical, electrical and software aspects of the system. It was found that the x-axis of the system, the axis that controls the depth of cut of the tool, is the limiting axis. A servo motor is used to replace the existing stepper motor, providing the x-axis with more torque and faster response times, which should improve the performance of the system. To control the servo motor, a 1st-order linear transfer function model is selected and identi ed. Then, an adaptive sliding mode controller is applied to make the x-axis a robust and accurate positioning system. A new trajectory generator is implemented to create a smooth motion for all three axes of the lathe. This trajectory uses a 5th-order polynomial to describe the position curve of the feed pro le, giving the system continuous jerk motion. This type of pro le is much easier for motors to follow, as discontinuous motion will always result in errors. These modi cations to the lathe system are then evaluated experimentally using a test case. Three test pieces are designed to represent three of the common shapes that are typically machined on the wood turning lathe. These test cases indicated a minimum reduction in machining time of 52:91% over the previous lathe system. An algorithm is also developed that attempts to sacri ce work piece model geometry to achieve speed gains. The algorithm is used when a certain feedrate is desired for a model, but machining at that speed will cause toolpath following errors, leaving surface defects in the work piece. The algorithm will attempt to solve this problem by sacri cing model geometry. A simulation tool is used to detect where surface defects will occur during machining and a then the work piece model is modi ed in the corresponding area. This will create a smoother part, which allows each axis of the system to follow the new toolpath more easily, as the dynamic requirements are reduced. The potential of this algorithm is demonstrated in an experimental test case. A test piece is created that has features of varying di culty to machine. When the algorithm is run, Matlab/Simulink is used simulate the output of the lathe and locate the areas in the part geometry that will cause defects. Once located, the geometry features are smoothed in SolidWorks using the fi llet feature. The algorithm produces a work piece with smoothed geometry that can be machined at a feedrate approximately 42:8% faster than before. Although it is only the first implementation of the algorithm, the experimental results con rm the potential of the method. Machining speed gains are successfully achieved through the sacrifice of model geometry

Smooth Trajectory Generation for Machine Tools and Industrial Robots

This thesis presents accurate and time-optimal smooth reference trajectory generation techniques for manufacturing equipment such as high-speed machine tools (MT) and industrial robots (IR). Typical machining tool-paths for MTs and IRs are defined as a series of discrete linear moves. Although Point-to-Point (P2P) feed motion can be generated by interpolating each linear segment with high-order velocity profiles, the continuous and accurate transition between consecutive segments is necessary to realize a non-stop contouring motion for efficient manufacturing. To generate continuous feed motion along sharp cornered tool-paths, most numerical control (NC) systems blend (smooth) corners locally using various curves and splines. The feed (speed) is reduced around the blend sections so that the motion system’s kinematic limits are respected. This thesis proposes 2 novel techniques to enable modern MT and IR to generate non-stop rapid motion along discrete tool-paths. Firstly, a Kinematic Corner Smoothing (KCS) technique has been proposed to generate time-optimal (minimum time) motion trajectories in a real-time within axis kinematic limits. A novel real-time interpolation technique based on Finite Impulse Response (FIR) filtering has also been proposed to suppress residual vibrations for high positioning accuracy of machine tools and motion systems as well. These two techniques are tailored for Cartesian structured motion systems such as 2-3 axis machine tools. Finally, a decoupled FIR filtering technique has been developed to synchronously interpolate tool position and orientation for accurate motion generation for 5-axis MTs and IRs. These techniques are computationally lightweight and suitable for real-time implementation on modern NC systems. Simulation and experimental validation on Cartesian and 5-axis machine tools are presented to validate the effectiveness of the developed algorithms to interpolate along with discrete commands for high-speed and high-accuracy motion

Smooth path planning with Pythagorean-hodoghraph spline curves geometric design and motion control

This thesis addresses two significative problems regarding autonomous systems, namely path and trajectory planning. Path planning deals with finding a suitable path from a start to a goal position by exploiting a given representation of the environment. Trajectory planning schemes govern the motion along the path by generating appropriate reference (path) points. We propose a two-step approach for the construction of planar smooth collision-free navigation paths. Obstacle avoidance techniques that rely on classical data structures are initially considered for the identification of piecewise linear paths that do not intersect with the obstacles of a given scenario. In the second step of the scheme we rely on spline interpolation algorithms with tension parameters to provide a smooth planar control strategy. In particular, we consider Pythagorean\u2013hodograph (PH) curves, since they provide an exact computation of fundamental geometric quantities. The vertices of the previously produced piecewise linear paths are interpolated by using a G1 or G2 interpolation scheme with tension based on PH splines. In both cases, a strategy based on the asymptotic analysis of the interpolation scheme is developed in order to get an automatic selection of the tension parameters. To completely describe the motion along the path we present a configurable trajectory planning strategy for the offline definition of time-dependent C2 piece-wise quintic feedrates. When PH spline curves are considered, the corresponding accurate and efficient CNC interpolator algorithms can be exploited

Smooth path planning with Pythagorean-hodoghraph spline curves geometric design and motion control

This thesis addresses two significative problems regarding autonomous systems, namely path and trajectory planning. Path planning deals with finding a suitable path from a start to a goal position by exploiting a given representation of the environment. Trajectory planning schemes govern the motion along the path by generating appropriate reference (path) points. We propose a two-step approach for the construction of planar smooth collision-free navigation paths. Obstacle avoidance techniques that rely on classical data structures are initially considered for the identification of piecewise linear paths that do not intersect with the obstacles of a given scenario. In the second step of the scheme we rely on spline interpolation algorithms with tension parameters to provide a smooth planar control strategy. In particular, we consider Pythagorean–hodograph (PH) curves, since they provide an exact computation of fundamental geometric quantities. The vertices of the previously produced piecewise linear paths are interpolated by using a G1 or G2 interpolation scheme with tension based on PH splines. In both cases, a strategy based on the asymptotic analysis of the interpolation scheme is developed in order to get an automatic selection of the tension parameters. To completely describe the motion along the path we present a configurable trajectory planning strategy for the offline definition of time-dependent C2 piece-wise quintic feedrates. When PH spline curves are considered, the corresponding accurate and efficient CNC interpolator algorithms can be exploited

Aspheric geodesic lenses for an integrated optical spectrum analyser

Abstract available p. xiii-xi

Precision Machining

The work included in this book focuses on precision machining and grinding processes, including milling, laser machining and polishing on various materials for high-end applications. These processes are in the forefront of contemporary technology, with significant industrial applications. Their importance is also made clear by the important works that are included in the research that is presented in the book. Some important aspects of these processes are investigated, and process parameters are optimized. This is performed in the presented works with significant experimental and modelling work, incorporating modern tools of analysis and measurements