Feed rate modeling in circular–circular interpolation discontinuity for high-speed milling

In this paper, a modeling approach is presented in order to evaluate feed rate during a circular interpolation in high-speed milling. The developed model depends on the type of discontinuity and the kinematic performance of the machine tool. To begin with, a feed rate modeling for circular interpolation with continuity in tangency is developed. After, the discontinuity in tangency between two circular interpolations is replaced by discontinuity in curvature by adding a fillet which is in relation to the functional tolerance ε imposed in the part design. An experimental study has been carried out to validate the models

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

Modelling and optimization of multi-axis machining process considering CNC motion limitations

The importance of multi-axis machining processes is increased over the years, especially for industries such as automotive, aerospace, dies and molds, biomedical where the parts have complex surfaces. As the demand for products is increased from these industries, it became crucial to minimize the cycle time to overcome the demand and also reduce the production costs while maintaining or enhancing the part quality. In order to achieve this the dimensional tolerances and a desired surface quality should be inside the acceptance limit while increasing productivity. The properties of the machine tool such as its own structure, axis drives, drivetrain, axis control limits and axis motor maximum capabilities can be regarded as boundary conditions of the process. The limits for the drives cannot be used at full capacity constantly as the machining process is a highly variable and flexible operation. For instance, sharp maneuvers on the tool path may not be realized at high feedrate values. In some cases, the required motion exceeds the motion capability of the axis drives, i.e. jerk, acceleration and velocity limitations. In those cases, the CNC unit slows down the motion to synchronize machine axes to keep up within geometrical limits of the required tool path. On the other hand, sometimes the commanded feed rate may not be achieved at some instances of a cycle involving short distances due to limited jerk and acceleration of the axes. These problems reduce the productivity of the operation as well as the quality of the final product. This thesis presents a new feed-rate optimization algorithm which re-adjusts the rotary axis motions to stay in the acceleration and jerk limits as well as to obtain a better surface quality for the final product in multi-axis machining. All measured velocity, acceleration and jerk limits are given to the algorithm to re-calculate the tool axis vector, such as lead and tilt angles, for minimizing the cycle time and enhancing part surface quality. As the current studies do not rely on the drive limits for choosing the tool orientation in multi-axis machining, for the first time, the algorithm represented in this thesis optimizes the tool’s lead and tilt angles at each Cutter Location (CL) point. The technique used in the study optimizes the tool orientation vector for minimizing the cycle time by observing the acceleration and jerk limits of the axis drives of the machine tool. The unnecessary motions between CL points generated by commercial software can be eliminated by the algorithm and this increases the productivity of the process. The feasibility of the algorithm and the models in this thesis is presented on an industrial part geometry where the productivity and machined surface quality improvements are demonstrated

Piecewise Arc-Length Parameterized NURBS Tool Paths Generation for 3-Axis CNC Machining of Accurate, Smooth Sculptured Surfaces

In current industrial applications many engineering parts having complex shapes are designed using sculptured surfaces in CAD system. Due to the lack of smooth motions and accurate machining of these surfaces using standard linear and circular motions in conventional CNC machines, new commercial CNC systems are equipped with parametric curve interpolation function. However, in some applications these surfaces can be very complex that are susceptible to gouging and due to the approximation of; CL-path in CAM system and path parameter in real –time, high machining accuracy, smooth kinematic and feed-rate profiles, are difficult to achieve. This dissertation focuses on developing algorithms that generate tool paths in NURBS form for smooth, high speed and accurate sculptured surface machining. The first part of the research identifies and eliminates gouge cutter location (CL) point from the tool path. The proposed algorithm uses global optimization technique (Particle Swarm Optimization) to check all the CC-points along a tool-path with high accuracy, and only gouging free CC-points are used to generate the set of valid CL-points. Mathematical models have been developed and implemented to cover most of the cutter shapes, used in the industry. In the second phase of the research, all valid CL-points along the tool-path are used to generate CL-path in B-spline form. The main contribution of this part is to formulate an error function of the offset approximation and to represent it in NURBS form to globally bound the approximation errors. Based on this error function, an algorithm is proposed to generate tool-paths in B-spline from with; globally controlled accuracy, fewer control points and low function degree, compared to its contemporaries. The proposed approach thus presents an error-bounded method for B-spline curve approximation to the ideal CL-path within the accuracy. This part of research has two components, one is for 2½- axis (pocket) and the other one is for 3-axis (surface) CNC machining. The third part deals with the problem of CL-path parameter estimation during machining in real time. Once the gouging free CL-path in NURBS form with globally controlled accuracy is produced, it is re-parameterized with approximate arc-length in the off-line stage. The main features of this work are; (1) sampling points and calculating their approximate arc-lengths within error bound by decomposing the input path into Bezier curve segments, (2) fitting the NURBS curve with approximate arc-length parameter to the sample points until the path and parameterization errors are within the tolerance, and (3) segment the curve into pieces with different feed rates if during machining the cutter trajectory errors are beyond the tolerance at highly curved regions in the NURBS tool path

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

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

Automated Process Planning for Five-Axis Point Milling of Sculptured Surfaces

Ph.DDOCTOR OF PHILOSOPH

A virus-evolutionary, multi-objective intelligent tool path optimisation methodology for sculptured surface CNC machining

Today’s production environment faces multiple challenges involving fast adaptation to modern technologies, flexibility in accommodating them to current industrial practices and cost reduction through automating repetitive tasks. At the same time the requirements for manufacturing functional, aesthetic and versatile products, turn these challenges to clear and present industrial problems that need to be solved by delivering at least semi-optimal results. Even though sculptured surfaces can meet such requirements when it comes to product design, a critical problem exists in terms of their machining operations owing to their arbitrary nature and complex geometrical features as opposed to prismatic surfaces. Current approaches for generating tool paths in computer-aided manufacturing (CAM) systems are still based on human intervention as well as trial-and-error experiments. These approaches neither can provide optimal tool paths nor can they establish a generic approach for an advantageous and profitable sculptured surface machining (SSM). Major goal of this PhD thesis is the development of an intelligent, automated and generic methodology for generating optimal 5-axis CNC tool paths to machine complex sculptured surfaces. The methodology considers the tool path parameters “cutting tool”, “stepover”, “lead angle”, “tilt angle” and “maximum discretisation step” as the independent variables for optimisation whilst the mean machining error, its mean distribution on the sculptured surface and the minimum number of tool positions are the crucial optimisation criteria formulating the generalized multi-objective sculptured surface CNC machining optimisation problem. The methodology is a two-fold programming framework comprising a virus-evolutionary genetic algorithm as the methodology’s intelligent part for performing the multi-objective optimisation and an automation function for driving the algorithm through its argument-passing elements directly related to CAM software, i.e., tool path computation utilities, objects for programmatically retrieving tool path parameters’ inputs, etc. These two modules (the intelligent algorithm and the automation function) interact and exchange information as needed towards the achievement of creating globally optimal tool paths for any sculptured surface. The methodology has been validated through simulation experiments and actual machining operations conducted to benchmark sculptured surfaces and corresponding results have been compared to those available from already existing tool path generation/optimisation approaches in the literature. The results have proven the methodology’s practical merits as well as its effectiveness for maintaining quality and productivity in sculptured surface 5-axis CNC machining

Modeling and Contour Control of Multi-Axis Linear Driven Machine Tools

In modern manufacturing industries, many applications require precision motion control of multi-agent systems, like multi-joint robot arms and multi-axis machine tools. Cutter (end effector) should stay as close as possible to the reference trajectory to ensure the quality of the final products. In conventional computer numerical control (CNC), the control unit of each axis is independently designed to achieve the best individual tracking performance. However, this becomes less effective when dealing with multi-axis contour following tasks because of the lack of coordination among axes. This dissertation studies the control of multi-axis machine tools with focus on reducing the contour error. The proposed research explicitly addresses the minimization of contour error and treats the multi-axis machine tool as a multi-input-multi-output (MIMO) system instead of several decoupled single-input-single-output (SISO) systems. New control schemes are developed to achieve superior contour following performance even in the presence of disturbances. This study also extends the applications of the proposed control system from plane contours to regular contours in R3. The effectiveness of the developed control systems is experimentally verified on a micro milling machine