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 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

Optimisation of Mobile Communication Networks - OMCO NET

The mini conference “Optimisation of Mobile Communication Networks” focuses on advanced methods for search and optimisation applied to wireless communication networks. It is sponsored by Research & Enterprise Fund Southampton Solent University. The conference strives to widen knowledge on advanced search methods capable of optimisation of wireless communications networks. The aim is to provide a forum for exchange of recent knowledge, new ideas and trends in this progressive and challenging area. The conference will popularise new successful approaches on resolving hard tasks such as minimisation of transmit power, cooperative and optimal routing

Prediction of cutting forces in five-axis micro-ball end milling

Five axis micro-ball end milling has been shown as a viable option for machining complex free form surfaces with high aspect ratios and provide micron-scale tolerances. Unfortunately, due to the high fragility of the cutting tool, premature tool failure has been a major challenge in micro-scale machining. Tool strength of a micro-ball end mill can be easily exceeded by the strain induced by cutting force, thus cutting force is desired to be accurately predicted. Traditionally, researchers have used the mechanistic relationship between experimental force and chipload to develop empirical cutting force models for end mill operation. However, these models suffer the drawbacks including the need for extensive experimental calibration, and the limitation to in-plane tool movements. Therefore a comprehensive cutting force model that is suitable for micro-ball end milling operation is desired. The work in this thesis presents a five-axis ball end milling force model that is specifically tailored to micro-scale machining. A composite cutting force is generated by combining two force contributions from a shearing/ploughing slip-line field model and a quasi-static indentation model. To fully capture the features of micro-scale five-axis machining, a unique chip thickness algorithm based on the velocity kinematics of a ball end mill is proposed. This formulation captures intricate tool trajectories as well as readily allows the integration of runout and elastic recovery effects. A workpiece updating algorithm has also been developed to identify tool-workpiece engagement. As a dual purpose, historical elastic recovery is stored locally on the meshed workpiece surface in vector form so that the directionality of elastic recovery is preserved for future time increments. The model has been calibrated and validated through a comparison with experiment data gain by five axis micro-ball end mill testing. Simulation results show reasonably accurate prediction of end milling cutting forces with minimal experimental data fitting. A potential model application for machining process planning is also presented

Scaling Multidimensional Inference for Big Structured Data

In information technology, big data is a collection of data sets so large and complex that it becomes difficult to process using traditional data processing applications [151]. In a world of increasing sensor modalities, cheaper storage, and more data oriented questions, we are quickly passing the limits of tractable computations using traditional statistical analysis methods. Methods which often show great results on simple data have difficulties processing complicated multidimensional data. Accuracy alone can no longer justify unwarranted memory use and computational complexity. Improving the scaling properties of these methods for multidimensional data is the only way to make these methods relevant. In this work we explore methods for improving the scaling properties of parametric and nonparametric models. Namely, we focus on the structure of the data to lower the complexity of a specific family of problems. The two types of structures considered in this work are distributive optimization with separable constraints (Chapters 2-3), and scaling Gaussian processes for multidimensional lattice input (Chapters 4-5). By improving the scaling of these methods, we can expand their use to a wide range of applications which were previously intractable open the door to new research questions

Shape characterisation of tool path motion

For a given application, the autonomous regulation of tool path motion by a machine’s controller can produce undesirable and unknown machining conditions. Machining parameters may therefore require a posteriori optimisation. Indeed, the methods employed are often iterative and informed by empirical evidence from machining trials. A shape characterisation of tool path motion is postulated by enforcing constraints on the kinematic equations describing velocity, acceleration and jerk. The resulting description of motion depends only upon the kinematic limits of a machine and the intrinsic shape properties of a tool path. The resulting shape schematics provide complete illustrations of the distinctive features of each of the kinematic vectors. Kinematic profiles, derived from a series of test tool path motions are compared with these shape schematics in order to provide supportive empirical evidence. The main contribution of this thesis is to demonstrate a priori shape characterisation of tool path motion. This characterisation is achieved without knowledge of the motion control algorithms implemented by a given machine’s controller. The characterisation may be employed to inform the selection of machining parameters and thereby reduce the time and the number of machining trials

Design and implementation of a modular controller for robotic machines

This research focused on the design and implementation of an Intelligent Modular Controller (IMC) architecture designed to be reconfigurable over a robust network. The design incorporates novel communication, hardware, and software architectures. This was motivated by current industrial needs for distributed control systems due to growing demand for less complexity, more processing power, flexibility, and greater fault tolerance. To this end, three main contributions were made. Most distributed control architectures depend on multi-tier heterogeneous communication networks requiring linking devices and/or complex middleware. In this study, first, a communication architecture was proposed and implemented with a homogenous network employing the ubiquitous Ethernet for both real-time and non real-time communication. This was achieved by a producer-consumer coordination model for real-time data communication over a segmented network, and a client-server model for point-to-point transactions. The protocols deployed use a Time-Triggered (TT) approach to schedule real-time tasks on the network. Unlike other TT approaches, the scheduling mechanism does not need to be configured explicitly when controller nodes are added or removed. An implicit clock synchronization technique was also developed to complement the architecture. Second, a reconfigurable mechanism based on an auto-configuration protocol was developed. Modules on the network use this protocol to automatically detect themselves, establish communication, and negotiate for a desired configuration. Third, the research demonstrated hardware/software co-design as a contribution to the growing discipline of mechatronics. The IMC consists of a motion controller board designed and prototyped in-house, and a Java microcontroller. An IMC is mapped to each machine/robot axis, and an additional IMC can be configured to serve as a real-time coordinator. The entire architecture was implemented in Java, thus reinforcing uniformity, simplicity, modularity, and openness. Evaluation results showed the potential of the flexible controller to meet medium to high performance machining requirements

An Analysis Review: Optimal Trajectory for 6-DOF-based Intelligent Controller in Biomedical Application

With technological advancements and the development of robots have begun to be utilized in numerous sectors, including industrial, agricultural, and medical. Optimizing the path planning of robot manipulators is a fundamental aspect of robot research with promising future prospects. The precise robot manipulator tracks can enhance the efficacy of a variety of robot duties, such as workshop operations, crop harvesting, and medical procedures, among others. Trajectory planning for robot manipulators is one of the fundamental robot technologies, and manipulator trajectory accuracy can be enhanced by the design of their controllers. However, the majority of controllers devised up to this point were incapable of effectively resolving the nonlinearity and uncertainty issues of high-degree freedom manipulators in order to overcome these issues and enhance the track performance of high-degree freedom manipulators. Developing practical path-planning algorithms to efficiently complete robot functions in autonomous robotics is critical. In addition, designing a collision-free path in conjunction with the physical limitations of the robot is a very challenging challenge due to the complex environment surrounding the dynamics and kinetics of robots with different degrees of freedom (DoF) and/or multiple arms. The advantages and disadvantages of current robot motion planning methods, incompleteness, scalability, safety, stability, smoothness, accuracy, optimization, and efficiency are examined in this paper

21st century manufacturing machines: Design, fabrication and controls

Advances in nanotechnology, microfabrication and new manufacturing processes, the revolution of open electronics, and the emerging internet of things will influence the design, manufacture, and control of manufacturing machines in the future. For instance, miniaturization will change manufacturing processes; additive and rapid prototyping will change the production of machine components; and open electronics offer a platform for new control architectures for manufacturing systems that are open, modular, and easy to reconfigure. Combined with the latest trends in cyber-physical systems and the internet of things, open architecture controllers for CNC systems can become platforms, oriented for numerical control as a service (NCaaS) and manufacturing as a service, tailored to the creation of cyber-manufacturing networks of shared resources and web applications. With this potential in mind, this research presents new design-for-fabrication methodologies and control strategies to facilitate the creation of next generation machine tools. It provides a discussion and examples of the opportunities that the present moment offers. The first portion of this dissertation focuses on the design of complex 3D MEMS machines realized from conventional 2.5D microfabrication processes. It presents an analysis of an example XYZ-MEMS parallel kinematics stage as well as of designs of the individual components of the manipulator, integrated into a design approach for PK-XYZ-MEMS stages. It seems likely that this design-for-fabrication methodology will enable higher functionality in MEMS micromachines and result in new devices that interact, in three full dimensions, with their surroundings. Novel and innovative research exemplifies the opportunities new and economical manufacturing technologies offer for the design and fabrication of modern machine tools. The second portion of this dissertation describes the demonstration of a new flexural joint designed with both traditional and additive manufacturing processes. It extrapolates principles based on the design of this joint that alleviate the effects of low accuracy and poor surface finishing, anisotropy, reductions in material properties of components, and small holding forces. Based on these results, the next section presents case examples of the construction of mesoscale devices and machine components using multilayered composites and hybrid flexures for precision engineering, medical training, and machine tools for reduced life applications and tests design-for-fabrication strategies. The results suggest the strategies effectively address existing problems, providing a repertory of creative solutions applicable to the design of devices with hybrid flexures. The implications for medical industry, micro robotics, soft robotics, flexible electronics, and metrology systems are positive. Chapter number five examines to positive impact of open architectures of control for CNC systems, given the current availability of micro-processing power and open-source electronics. It presents a new modular architecture controller based on open-source electronics. This component-based approach offers the possibility of adding micro-processing units and an axis of motion without modification of the control programs. This kind of software and hardware modularity is important for the reconfiguration of new manufacturing units. The flexibility of this architecture makes it a convenient testbed for the implementation of new control algorithms on different electromechanical systems. This research provides general purpose, open architecture for the design of a CNC system based on open electronics and detailed information to experiment with these platforms. This dissertation’s final chapter describes how applying the latest trends to the classical concepts of modular and open architecture controllers for CNC systems results in a control platform, oriented for numerical control as a service (NCaaS) and manufacturing as a service (MaaS), tailored to the creation of cyber-manufacturing networks of shared resources and web applications. Based on this technology, this chapter introduces new manufacturing network for numerical control (NC) infrastructure, provisioned and managed over the internet. The proposed network architecture has a hardware, a virtualization, an operating system, and a network layer. With a new operating system necessary to service and virtualize manufacturing resources, and a micro service architecture of manufacturing nodes and assets, this network is a new paradigm in cloud manufacturing