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

Conical scan impact study. Volume 2: Small local user data processing facility

The impact of a conical scan versus a linear scan multispectral scanner (MSS) instrument on a small local-user data processing facility was studied. User data requirements were examined to determine the unique system rquirements for a low cost ground system (LCGS) compatible with the Earth Observatory Satellite (EOS) system. Candidate concepts were defined for the LCGS and preliminary designs were developed for selected concepts. The impact of a conical scan MSS versus a linear scan MSS was evaluated for the selected concepts. It was concluded that there are valid user requirements for the LCGS and, as a result of these requirements, the impact of the conical scanner is minimal, although some new hardware development for the LCGS is necessary to handle conical scan data

Integrating tolerances in G and M codes using neural networks

Continuous integrated solutions from CAD down to the preparation of NC programs were developed in the recent years. However, if tolerances should be considered, the interaction of human experts is still necessary. A way to fill this gap in the production process is shown in this thesis. The study builds a relationship between the given design tolerances and including these tolerances in machining by generating respective G and M codes. The study focuses on physical phenomena and their inter-relationship while manufacturing. For example how the speed of machining, torque, power, depth of cut, etc. influences machining under specified tolerances. Artificial neural networks (ANN) have been used to generate required outputs because of their capability to learn from a given set of data points. Four different kinds of neural networks, as a module, have been used. with different kinds of learning rules (algorithms) depending on the type of inputs and outputs. The whole model incorporates retrieval of tolerances from a CAD software and running the algorithms for (i) Dimensional tolerance analysis, (ii) Control of feed rate, spindle speed, depth of cut and cutting forces, (iii) Propagation of errors in multistage machining, and (iv) Vectorization of geometrical tolerances. Machining processes would include (i) Milling, (ii) Turning, and (iii) Drilling. Then the corresponding outputs are interpreted and analyzed to generate G and M codes. This study has shown how ANN can revolutionize NC machine manufacturing. A case study illustrates the effectiveness of the proposed method

EXPERIMENTAL AND NUMERICAL INVESTIGATION OF PLASMA-JET FORMING

Sheet metal forming has found increasing applications in modern industries. To eliminate use of expensive tools during product development, thermal forming, a rapid prototyping process that is flexible enough to decrease costs has been developed. Thermal forming processes use a heat source to perform the required deformation mainly by creating a thermal difference along the thickness of the sheet. Gas flames, lasers and plasma heat sources have been used for sheet metal bending by thermal forming. An alternative to laser and gas flames, plasma-jet forming has been developed that uses a non-transferred plasma arc as a heat source. The plasma-jet forming system uses a highly controllable non-transferred plasma torch as a heat source to create the necessary thermal gradient in the sheet metal that causes the required plastic deformation. Various experiments to produce simple linear bends and other complex shapes have been conducted by using different scanning options and coupling techniques. A computer simulated model using finite element method is being developed to study key parameters affecting this process and also to measure the thermal transient temperature distribution during the process. A predictive model to relate the deformation to the temperature gradient for various materials is being developed. Simulation results that are in accordance to experimental observations will further improve this material forming process to be highly controllable and more accurat

Feature based workshop oriented NC planning for asymmetric rotational parts

This thesis describes research which is aimed at devising a framework for a feature based workshop oriented NC planning. The principal objective of this thesis is to utilize a feature based method which can rationalize and enhance part description and in particular part planning and programming on the shop-floor. This work has been done taking into account new developments in the area of shop floor programming. The importance of the techniques and conventions which are addressed in this thesis stems from the recognition that the most effective way to improve and enhance part description is to capture the intent of the engineering drawing by devising a medium in which the recurring patterns of turned components can be modelled for machining. Experimental application software which allows the user to describe the workpiece and subsequently generate the manufacturing code has been realized

Fully automated urban traffic system

The replacement of the driver with an automatic system which could perform the functions of guiding and routing a vehicle with a human's capability of responding to changing traffic demands was discussed. The problem was divided into four technological areas; guidance, routing, computing, and communications. It was determined that the latter three areas being developed independent of any need for fully automated urban traffic. A guidance system that would meet system requirements was not being developed but was technically feasible

Advanced deep space communication systems study Final report

Deep space communication system requirements for period 1970 to 198

Mechanical design automation: a case study on plastic extrusion die tooling

The Skills Gap in Mechanical Engineering (ME) Design has been widening with the increasing number of baby boomers retiring (Silver Tsunami) and the lack of a new generation to acquire, practice and perfect their knowledge base. This growing problem has been addressed with several initiatives focused on attracting and retaining young talent; however, these types of initiatives may not be timely for this new group to be trained by an established Subject Matter Expert (SME) group. Automated Engineering Design provides a potential pathway to address not only the Skills Gap but also the transfer of information from SMEs to a new generation of engineers. Automation has been at the heart of the Advanced Manufacturing Industry, and has been successful at accomplishing repetitive tasks with processes, software and equipment. The next stage in Advanced Manufacturing is further integrating Machine Learning techniques (Artificial Intelligence (AI)) in order to mimic human decision making. These initiatives are clear for the type of mechanized systems and repetitive processes present in the manufacturing world, but the question remains if they can be effectively applied to the decision heavy area of ME Design. A collaboration with an industry partner New Jersey Precision Technologies (NJPT) was established in order to address this question. This thesis presents an ME Design Automation process involving a multi-stage approach: Design Definition, Task Differentiation, Workflow Generation and Expert System Development. This process was executed on plastic extrusion tooling design. A Computer Aided Design (CAD) based Expert System was developed for the Automation of design, and the generation of a database towards future Machine Learning work. This system was run on 6 extrusion product examples previously designed by NJPT through traditional methods. The time needed to generate the design was reduced by 95-98%. This thesis demonstrates the capability of automating ME design, the potential impact in industry and next steps towards the application of AI

Empirical Fragility Functions and Numerical Parametric Study for Buckling of Steel Grain Bins under High Wind Loads

While rural infrastructure is critical to the agricultural industry, it has been historically more susceptible to damage and slower to recover following natural disasters than its urban and suburban counterparts. This has been made evident most recently by the events of the August 10, 2020, derecho in which rural regions in Iowa were among the hardest hit areas with sustained windspeeds exceeding 120 mph. Among the most frequently damaged structures in this event were corrugated steel grain bins, which farmers and co-ops use to dry and store certain commodities. Unlike most other critical structures, steel grain bins are not designed and constructed to consistent design standards for wind loads resulting in a wide range of performance and impact to individual farmers and the economy. Therefore, the overarching goal of this thesis is to enhance knowledge of steel grain bin performance under wind loads, which is accomplished by field reconnaissance, empirical fragility analysis, and finite element modeling. A survey of over 600 standard construction corrugated steel grain bins was carried out over a large area of eastern and central Iowa in the immediate aftermath of the August 2020 storm. Physical characteristics, configuration, construction, and damage severity were observed and recorded. Windspeed data from the National Weather Service and point estimates from observed damage indicators were used to build a more detailed estimate of peak windspeeds across the region. Empirical fragility curves were developed to relate the probability of various steel grain bin damage states to windspeed. This fragility analysis considered the effects of the physical characteristics, configuration, and construction of the grain bins. The results of this analysis showed that grain bin diameter and exposure of the terrain they are located on are the most significant factors when it comes to their susceptibility to damage. Finite element modelling was used to carry out a parametric analysis of the effects of a wide range of physical characteristics of empty steel grain bins on their buckling strength under wind loads. The finite element software LS-DYNA was utilized to construct three-dimensional numerical models using shell elements. Critical wind load was determined by a nonlinear buckling analysis by the arc-length method. The parametric analysis was carried out by looking at the effects of diameter, height, number of vertical stiffeners, number of wind rings, presence of wind on the roof of the structure, analysis as vented or unvented, wavelength of the corrugation profile, depth of the corrugation profile, thickness of the cylinder wall, and thickness of vertical stiffeners. The results of this analysis were compared to empirical results from the data collected during the August 2020 derecho in order to confirm the trends observed during the parametric analysis. The conclusions drawn from this were that grain bin height, diameter, and openness of terrain have the greatest influence on susceptibility to damage from high winds regardless of other characteristics. Parameters such as presence of stiffeners, wind rings, and roof vents had more influence on the theoretical buckling wind load than they had on observed performance in the field. Advisor: Christine E. Wittic