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

Contouring Accuracy Improvement Using an Adaptive Feedrate Planning Method for CNC Machine Tools

AbstractThe reduction of contour error plays an important role in achieving high accuracy machining. To reduce contour error, most of previous studies have focused on developing advanced control strategies. As an alternative strategy, contouring accuracy improvement using an adaptive feedrate planning method is proposed in this paper. First, a typical PID controller is adopted to build the contour error model, from which the feedrate can be scheduled in the contour error violated zones. Then, the relations between each constraint and the cutter tip feedrate are derived. After that, a linear programming model is applied to obtain the optimal feedrate profile on the sampling positions of the given tool path. Finally, illustrated examples are given to validate the feasibility and applicability of the proposed feedrate planning method. The comparison results show that the proposed method has a significant effect on improving contouring accuracy

Arc-Length Parameterized NURBS Tool Path Generation and Velocity Profile Planning for Accurate 3-Axis Curve Milling

In modern industrial CNC (Computer Numerical Control) machining processes, the pursuing of higher accuracy and efficiency has always been one of the most important tasks to be discussed and studied. A lot of proposed algorithms are developed in order to optimize the machining performance in either of the above focused domains. Nevertheless, there is forever a trade-off between gaining less machining error and providing higher feed rate. As for machining a free-shaped curve (e.g., Bezier curves, B-splines and NURBS) in a three-dimensional space, a better manner to balance out the aforementioned trade-offs turns out to be even more critical and essential. The conventional iterative function used for tool path generation could cause feed rate fluctuation during the actual machining, and it thus might lead to failure on constraining the error within the machining accuracy requirement. Another potential problem occurs when the machining process comes across into a relatively high curvature segment with the prescribed high feed rate, due to the machine axial acceleration limit, the machine may not be able to maintain the tool tip trajectory within the error tolerance. Therefore, a new approach to NURBS tool path generation for high feed rate machining is proposed. In this work, several criterions are set for checking the viability of the prescribed feed rate and adjusting it according to the actual shape of the objective curve and the capability of the machine. After the offline feed rate viability check and readjustment, a new iterative algorithm based on the arc-length re-parameterized NURBS function would be implemented to calculate the tool path in real-time. By using this proposed method, the feed rate fluctuation is diminished and the overall efficiency of the machining process would have been optimized under the condition of accuracy guaranteed

Motion Profile Control Algorithm and Corner Smoothing Technique for Trajectory Optimization of High-Precision Processing

Processing accuracy in instrumental technology has always been of great importance. Producers of Computer Numeric Control (CNC) systems are constantly looking for novel solutions to achieve higher velocities and precision. However, most of the produced software algorithms are inaccessible to the general public. Hence the task to develop sufficient open source software arises. This paper aims to create a trajectory optimization algorithm, including feed rate control and a corner smoothing technique, which will allow effective high-speed and high-precision processing. It is intended to standardize the algo- rithm for application with both stepper and servo motor driven machines. The developed motion planning method is based on a cosine function to attain a smooth change of velocity that allows for vibration reduction. To achieve smooth corner processing, spline curves are applied to adjust the size and shape of a fillet and thus satisfy the required tolerance and maintain high velocities. The resulting algorithm is programmed and simulation tests are carried out. The final algorithm shows a smooth transition of velocities, which leads to vibration reduction and consequently to minimization of machining error. In corner smoothing the use of parametric curves demonstrates the ability to vary tolerance. As a result, a sufficient motion control algorithm is developed and can be used in CNC software

Multi-angle valve seat machining: experimental analysis and numerical modelling

Modern automotive manufacturers operate in highly competitive markets, heavily influenced by Government regulation and ever more environmentally conscious consumers. Modern high-temperature, high-pressure engines that use high hardness multi-angle valve seats are an attractive environmental option, but one that manufacturers find requires more advanced materials and tighter geometric tolerances to maintain engine performance.Tool manufacturers meet these increasingly tougher demands by using, higher hardness cutting materials such as polycrystalline cubic boron nitride (pcBN), that on paper, promise to wear at a lower rate, require less coolant and deliver tighter tolerances than their carbide counterparts.The low brittle fracture toughness of pcBN makes tools that use it vulnerable to minute chipping. A review of literature for this work pointed to no clear answer to this problem, although suggestions range from manufacturing defects, dynamic and flexibility problems with the production line machinery and fixtures, and radial imbalances in the cutting loads.This work set about experimentally investigating those potential explanations, coming to the conclusion that the high radial imbalance of the cutting loads is responsible for pcBN cutting insert failure during multi-angle valve seat machining, and that by simply relocating the cutting inserts around the multi angle cutting tool, the imbalance can be reduced, thus extending the life of the cutting inserts.It is not always easy to predict the imbalance due to the multiple flexibilities in the system, and simulating such a system in 3D with all its associated cutting phenomena such as friction, thermal expansion, chip flow and shearing, would call upon extraordinary computational power and extremely precise experimental inputs to reduce cumulative error.This thesis proves that such a 3D simulation can be made, that runs in exceptionally short durations compared to traditional methods, by making a number of simplifications.MSC Marc was used to host the simulation, with a parametric script written in Python responsible for generating the model geometry and cutter layout. A Fortran program was developed that is called upon by Marc to calculate the required cutting load outputs and generate new workpiece meshes as material is removed.</div

Multi-Agent Modeling for Integrated Process Planning and Scheduling

Multi-agent systems have been used for modelling various problems in the social, biological and technical domain. When comes to technical systems, especially manufacturing systems, agents are most often applied in optimization and scheduling problems. Traditionally, scheduling is done after creation of process plans. In this paper, agent methodology is used for integration of these two functions. The proposed multi-agent architecture provides simultaneous performance of process planning and scheduling and it consists of four intelligent agents: part and job agents, machine agent, and optimization agent. Verification and feasibility of a proposed approach is conducted using agent based simulation in AnyLogic software

Rapid manufacturing of vacuum forming components utilising reconfigurable screw pin tooling

Current market trends are moving from large quantity production towards small batch production and mass customization. This has led to the high demand for the flexibility and adaptability of manufacturing technology and systems. Several reconfigurable pin type tooling systems have been proposed and developed to satisfy such demands. However, these reconfigurable tooling systems still suffer from several drawbacks, including difficulties associated with positioning and locking the pins and problems of uneven “staircase” surface effects from relying on discrete finite size pins. The main focus of this research is on building a hybrid vacuum-forming machine system (HAVES) based on reconfigurable screw-pin tooling (SPT)as a test bed for understanding the processes involved in developing this technology and to examine the feasibility of implementing such technology in an industrial system. The SPT used is composed of identical screw pins,which are engaged with each other in an array pattern. By adjusting vertical displacement of the screw pins, a wide variety of component geometry can be formed. The adjustment methodology of the SPT is formulated mathematically in order to help construction of the SPT be parametrical thus enabling automatic CNC G-code generation. The HAVES test bed development involves full machine design and hardware and software integration. The hardware integration task included a CNC controller, drive motors, encoders, milling and screw adjustment heads, SPT, vacuum forming system. The software integration task involved the processing of three-dimensional CAD geometry to automatically generate post processed G codes in order to adjust the screw-pin to the required component geometry and subsequent surface machining for driving the final die geometry and minimize operator intervention. The completed HAVES test bed has been tested for accuracy, repeatability and functionalities with quality good results. An economic analysis has been also conducted to verify the economic feasibility of the HAVES test bed by comparing the cost of making vacuum forming components using a dedicated mould versus using the HAVES test bed

Multi-Agent Modeling for Integrated Process Planning and Scheduling

Multi-agent systems have been used for modelling various problems in the social, biological and technical domain. When comes to technical systems, especially manufacturing systems, agents are most often applied in optimization and scheduling problems. Traditionally, scheduling is done after creation of process plans. In this paper, agent methodology is used for integration of these two functions. The proposed multi-agent architecture provides simultaneous performance of process planning and scheduling and it consists of four intelligent agents: part and job agents, machine agent, and optimization agent. Verification and feasibility of a proposed approach is conducted using agent based simulation in AnyLogic software

Fast Adjoint-assisted Multilevel Multi delity Method for Uncertainty Quanti cation of the Aleatoric Kind

PhDIn this thesis an adjoint-based multilevel multi delity Monte Carlo (MLMF) method is proposed, analysed, and demonstrated using test problems. Firstly, a multifi delity framework using the approximate function evaluation [1] based on the adjoint error correction of Giles et al. [2] is employed as a low fidelity model. This multifi delity framework is analysed using the method proposed by Ng and Wilcox [3]. The computational cost reduction and accuracy is demonstrated using the viscous Burgers' equation subject to uncertain boundary condition. The multi fidelity framework is extended to include multilevel meshes using the MLMF of Geraci [4] called the FastUQ. Some insights on parameters affecting computational cost are shown. The implementation of FastUQ in Dakota toolkit is outlined. As a demonstration, FastUQ is used to quantify uncertainties in aerodynamic parameters due to surface variations caused by manufacturing process. A synthetic model for surface variations due to manufacturing process is proposed based on Gaussian process. The LS89 turbine cascade subject to this synthetic disturbance model at two o -design conditions is used as a test problem. Extraction of independent random modes and truncation using a goal-based principal component analysis is shown. The analysis includes truncation for problems involving multiple QoIs and test conditions. The results from FastUQ are compared to the state-of-art SMLMC method and the approximate function evaluation using adjoint error correction called the inexpensive Monte Carlo method (IMC). About 70% reduction in computational cost compared to SMLMC is achieved without any loss of accuracy. The approximate model based on the IMC has high deviations for non-linear and sensitive QoI, namely the total-pressure loss. FastUQ control variate effectively balances the low fi delity model errors and additional high fidelity evaluations to yield accurate results comparable to the high fidelity model.This work has received funding from the European Union's Horizon 2020 research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 642959