Novel control of a high performance rotary wood planing machine

Rotary planing, and moulding, machining operations have been employed within the woodworking industry for a number of years. Due to the rotational nature of the machining process, cuttermarks, in the form of waves, are created on the machined timber surface. It is the nature of these cuttermarks that determine the surface quality of the machined timber. It has been established that cutting tool inaccuracies and vibrations are a prime factor in the form of the cuttermarks on the timber surface. A principal aim of this thesis is to create a control architecture that is suitable for the adaptive operation of a wood planing machine in order to improve the surface quality of the machined timber. In order to improve the surface quality, a thorough understanding of the principals of wood planing is required. These principals are stated within this thesis and the ability to manipulate the rotary wood planing process, in order to achieve a higher surface quality, is shown. An existing test rig facility is utilised within this thesis, however upgrades to facilitate higher cutting and feed speeds, as well as possible future implementations such as extended cutting regimes, the test rig has been modified and enlarged. This test rig allows for the dynamic positioning of the centre of rotation of the cutterhead during a cutting operation through the use of piezo electric actuators, with a displacement range of ±15μm. A new controller for the system has been generated. Within this controller are a number of tuneable parameters. It was found that these parameters were dependant on a high number external factors, such as operating speeds and run‐out of the cutting knives. A novel approach to the generation of these parameters has been developed and implemented within the overall system. Both cutterhead inaccuracies and vibrations can be overcome, to some degree, by the vertical displacement of the cutterhead. However a crucial information element is not known, the particular displacement profile. Therefore a novel approach, consisting of a subtle change to the displacement profile and then a pattern matching approach, has been implemented onto the test rig. Within the pattern matching approach the surface profiles are simplified to a basic form. This basic form allows for a much simplified approach to the pattern matching whilst producing a result suitable for the subtle change approach. In order to compress the data levels a Principal Component Analysis was performed on the measured surface data. Patterns were found to be present in the resultant data matrix and so investigations into defect classification techniques have been carried out using both K‐Nearest Neighbour techniques and Neural Networks. The application of these novel approaches has yielded a higher system performance, for no additional cost to the mechanical components of the wood planing machine, both in terms of wood throughput and machined timber surface quality

Motion control and synchronisation of multi-axis drive systems

Motion control and synchronisation of multi-axis drive system

Proceedings of the 4th Baltic Mechatronics Symposium - Tallinn April 25, 2019

The Baltic Mechatronics Symposium is annual symposium with the objective to provide a forum for young scientists from Baltic countries to exchange knowledge, experience, results and information in large variety of fields in mechatronics. The symposium was organized in co-operation with Taltech and Aalto University. The venue of the symposium was Nordic Hotel Forum Tallinn.The symposium was organized parallel to the 12th International DAAAM Baltic Conference and 27th International Baltic Conference BALTMATTRIB 2019. The selected papers are published in Proceedings of Estonian Academy of Sciences indexed in ISI Web of Science. The content of the proceedings: 1. Continuous wet spinning of cellulose nanofibrils 2. Development of motor efficiency test setup for direct driven hydraulic actuator 3. Development of pressure former for continuous nanopaper manufacturing 4. Device for tree volume measurements 5. Effect of external load on rotor vibration 6. Granular jamming based gripper for heavy objects 7. Integrated car camera system for monitoring inner cabin and outer traffic 8. Inverted pendulum controlled with CNC control system 9. Multi-material mixer and extruder for 3D printing 10. Object detection and trajectory planning using a LIDAR for an automated overhead cran

A computer graphics approach to logistics strategy modelling

This thesis describes the development and application of a decision support system for logistics strategy modelling. The decision support system that is developed enables the modelling of logistics systems at a strategic level for any country or area in the world. The model runs on IBM PC or compatible computers under DOS (disk operating system). The decision support system uses colour graphics to represent the different physical functions of a logistics system. The graphics of the system is machine independent. The model displays on the screen the map of the area or country which is being considered for logistic planning. The decision support system is hybrid in term of algorithm. It employs optimisation for allocation. The customers are allocated by building a network path from customer to the source points taking into consideration all the production and throughput constraints on factories, distribution depots and transshipment points. The system uses computer graphic visually interactive heuristics to find the best possible location for distribution depots and transshipment points. In a one depot system it gives the optimum solution but where more than one depot is involved, the optimum solution is not guaranteed. The developed model is a cost-driven model. It represents all the logistics system costs in their proper form. Its solution very much depends on the relationship between all the costs. The locations of depots and transshipment points depend on the relationship between inbound and outbound transportation costs. The model has been validated on real world problems, some of which are described here. The advantages of such a decision support system for the formulation of a problem are discussed. Also discussed is the contribution of such an approach at the validation and solution presentation stages

A platform cascading method for scale based product family design.

In this dissertation, a product family design method for scale based products leveraged from multiple platforms is presented. A product family is a set of related products derived from a product platform. Product family design involves designing the platform and also leveraging the different product variants from the platform. A common approach to the product family design is to treat it as a design optimization problem, so that tradeoff analysis can be performed between commonality and individual product performance.In the evaluation stage, evaluation functions are used to evaluate the family of products leveraged from the platform. After Evaluation of the products leveraged, PCM uses a cascading formulation to generate subsequent platforms from the initial platform. Cascading generates new platform by converting the platform parameters from the previous platform to a scale parameter to leverage the set of products that have poor performance. The method is illustrated using two examples: (1) axial pump product family design and (2) universal electric motor product family design. The method can be easily implemented in gradient based optimization tools and can be used design scale based product families in a time efficient manner.A product family based on a single platform may lead to poor performance of the product family. A better approach is to leverage the products from multiple platforms. This approach offers more challenges to the designer. The designer must now determine: the optimum number of product platforms that are required, the values of platform parameters for each platform, the products that are leveraged from each platform and the value of scale parameters.In this dissertation, a Platform Cascading Method (PCM) is presented which is capable of designing the family of products based on multiple platforms. PCM is comprised of three stages: (1) Single platform stage; (2) Evaluation stage; and (3) Cascading stage. In PCM, the family is first leveraged using a single platform. The non platform scale based design problem has the structure of a Mixed Integer Non Linear Problem (MINLP) due to the combinatorial nature of the platform commonality parameters and continuous product parameters. Solving MINLPs are not straightforward and require high amount of expertise and time in solving the problem and hence transform to high product lead time. In PCM, the non platform specified product family design formulation is converted from a MINLP to a NLP by relaxing the platform commonality parameters to continuous parameters and then mathematically constraining to produce discrete results in the end

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

Semi-Analytical Approach Towards Design and Optimization of Induction Machines for Electric Vehicles

Electric machine design is a comprehensive task depending on the several factors, such as material resource limitations and economic factors. Therefore, an induction machine is a promising candidate because of the absence of magnetic material in the rotor. However, the conventional design approach can neither reflect the advances of the induction machine(IM) design nor exploit the trade-offs between design factors and the multi-physics nature of the electrical machine. Therefore, proposing fast and accurate novel methods to design, develop and analyze IMs using electromagnetic field oriented approaches is competitive to the old-fashion numerical methods. To achieve improved IM design from a baseline design to an optimal design, this dissertation: (1) Investigates the challenges of the high speed IM design specified for the electric vehicle application at the rated operating condition considering electromagnetic boundaries for the reasonable saturation level within a compact volume; (2) Proposes a new design approach of IM using modified equivalent circuit parameters to reduce spatial harmonics because of slotting effect and skewing effect; and also presents the importance of the 3-D analysis over 2-D analysis while developing the IM; (3) Proposes a novel electromagnetic field oriented mathematical model considering the slotting effect and axial flux variation because of skewing rotor bars to evaluate the IM performance with a lower and precise computational effort; (4) developed baseline IM is optimized with genetic algorithm incorporated in proposed subdomain model to improve the torque-speed profile. In order to further simplify the optimization procedure, a parametric and sensitivity based design approach is implemented to reduce the design variables. To evaluate the proposed optimal IM with extended constant power region and high torque density within a compact volume using novel 3-D subdomain model, the machine has been prototyped and tested from low to high speed under no-load and loaded condition. Electrical circuit parameter variation is demonstrated and compared to the one simulated in the FEA environment. This innovation can be applied to a family of electric machines with various topologies

ESSE 2017. Proceedings of the International Conference on Environmental Science and Sustainable Energy

Environmental science is an interdisciplinary academic field that integrates physical-, biological-, and information sciences to study and solve environmental problems. ESSE - The International Conference on Environmental Science and Sustainable Energy provides a platform for experts, professionals, and researchers to share updated information and stimulate the communication with each other. In 2017 it was held in Suzhou, China June 23-25, 2017

NASA Tech Briefs, January 1989

Topics include: Electronic Components & and Circuits. Electronic Systems, A Physical Sciences, Materials, Computer Programs, Mechanics, Machinery, Fabrication Technology, Mathematics and Information Sciences, and Life Sciences

Handbook of Computational Intelligence in Manufacturing and Production Management

Artificial intelligence (AI) is simply a way of providing a computer or a machine to think intelligently like human beings. Since human intelligence is a complex abstraction, scientists have only recently began to understand and make certain assumptions on how people think and to apply these assumptions in order to design AI programs. It is a vast knowledge base discipline that covers reasoning, machine learning, planning, intelligent search, and perception building. Traditional AI had the limitations to meet the increasing demand of search, optimization, and machine learning in the areas of large, biological, and commercial database information systems and management of factory automation for different industries such as power, automobile, aerospace, and chemical plants. The drawbacks of classical AI became more pronounced due to successive failures of the decade long Japanese project on fifth generation computing machines. The limitation of traditional AI gave rise to development of new computational methods in various applications of engineering and management problems. As a result, these computational techniques emerged as a new discipline called computational intelligence (CI)