Automated CNC Tool Path Planning and Machining Simulation on Highly Parallel Computing Architectures

This work has created a completely new geometry representation for the CAD/CAM area that was initially designed for highly parallel scalable environment. A methodology was also created for designing highly parallel and scalable algorithms that can use the developed geometry representation. The approach used in this work is to move parallel algorithm design complexity from an algorithm level to a data representation level. As a result the developed methodology allows an easy algorithm design without worrying too much about the underlying hardware. However, the developed algorithms are still highly parallel because the underlying geometry model is highly parallel. For validation purposes, the developed methodology and geometry representation were used for designing CNC machine simulation and tool path planning algorithms. Then these algorithms were implemented and tested on a multi-GPU system. Performance evaluation of developed algorithms has shown great parallelizability and scalability; and that main algorithm properties are required for modern highly parallel environment. It was also proved that GPUs are capable of performing work an order of magnitude faster than traditional central processors. The last part of the work demonstrates how high performance that comes with highly parallel hardware can be used for development of a next level of automated CNC tool path planning systems. As a proof of concept, a fully automated tool path planning system capable of generating valid G-code programs for 5-axis CNC milling machines was developed. For validation purposes, the developed system was used for generating tool paths for some parts and results were used for machining simulation and experimental machining. Experimental results have proved from one side that the developed system works. And from another side, that highly parallel hardware brings computational resources for algorithms that were not even considered before due to computational requirements, but can provide the next level of automation for modern manufacturing systems

Geometric process planning in rough machining

This thesis examines geometric process planning in four-axis rough machining. A review of existing literature provides a foundation for process planning in machining; efficiency (tool path length) is identified as a primary concern. Emergent structures (thin webs and strings) are proposed as a new metric of process robustness. Previous research efforts are contrasted to establish motivation for improvements in these areas in four-axis rough machining. The original research is presented as a journal article. This research develops a new methodology for quickly estimating the remaining stock during a plurality of 2 y D cuts defined by their depth and orientation relative to a rotary fourth axis. Unlike existing tool path simulators, this method can be performed independently of (and thus prior to) tool path generation. The algorithms presented use polyhedral mesh surface input to create and analyze polygonal slices, which are again reconstructed into polyhedral surfaces. At the slice level, nearly all operations are Boolean in nature, allowing simple implementation. A novel heuristic for polyhedral reconstruction for this application is presented. Results are shown for sample components, showing a significant reduction in overall rough machining tool path length. The discussion of future work provides a brief discussion of how this new methodology can be applied to detecting thin webs and strings prior to tool path planning or machining. The methodology presented in this work provides a novel method of calculating remaining stock such that it can be performed during process planning, prior to committing to tool path generation

Software Simulation of Numerically Controlled Machining

The field of numerically controlled (NC) machining has long been interested with predicting and measuring the errors in machining. Creating a simulation of NC machining is one way of achieving this. This thesis presents one such implementation of an NC simulation. It also runs a number of numerical and physical tests to verify the simulation?s correctness. The numerical tests show that the simulator work correctly as well as providing guide lines for appropriate simulation parameters. The physical tests show that the results of the simulation match the results of real NC machines. It is hoped that this thesis can provide a guide for the creation of machining simulators and their verification

Voxel octree intersection based 3D scanning

Recent developments in the field of three dimensional (3D) printing have resulted in widely available low-cost 3D printers. These printers require 3D models, which are traditionally created in 3D modeling software or are created from 3D scans of existing objects. To be printable, these models must exhibit the property of being watertight. In this thesis, a technique is developed, which, in combination with a custom built low-cost 3D scanner, produces watertight 3D models. Models produced by this technique - the voxel octree intersection technique - do not require any additional processing prior to 3D printing. Results from using this technique with the custom built scanner are examined, and along with the effects of changing various parameters to the technique

Overview of database projects

The use of entity and object oriented data modeling techniques for managing Computer Aided Design (CAD) is explored

Dimensional verification and correction of five-axis numerically controlled milling tool paths

A system of algorithms is presented for material removal simulation, automatic dimensional verification and integrated error correction of numerically controlled (NC) milling tool paths. Several different approaches to these problems have been proposed including direct solid modeling, discrete vector intersection, and spatial partitioning. However, each of these methods suffer inherent restrictions that limit their practical application. This dissertation presents a discrete dexel NC verification algorithm based on a spatial partitioning technique (dexel representation) which incorporates the advantages of the discrete vector intersection approach. Hence, real-time animated five-axis milling simulation is supported by efficient regularized Boolean set operations, and dimensional milling errors are verified simultaneously with the simulation process. Based on intermediate dimensional verification results, a reduction of intersection volume algorithm is developed to eliminate detected gouges on the part surface. In addition, a technique for detection and elimination of unexpected collisions between the tool assembly and the workpiece is developed. These combined algorithms automatically correct tool paths to avoid gouges and collisions resulting in tool paths that are ready for immediate industrial application. A major disadvantage of dexel-based spatial partitioning, as originally proposed, is view dependency, i.e., dexels are constructed along a specific viewing vector so reconstruction of dexels is required for each new viewing direction. To overcome this problem, a contour display method is developed to transform dexel-based objects into a set of parallel planar contours thus enabling dynamic viewing transformations. In summary, this dissertation describes a unique hybrid approach to NC milling verification which provides for efficient, accurate and automatic assessment and correction of five-axis milling tool paths

The characterisation and simulation of 3D vision sensors for measurement optimisation

The use of 3D Vision is becoming increasingly common in a range of industrial applications including part identification, reverse engineering, quality control and inspection. To facilitate this increased usage, especially in autonomous applications such as free-form assembly and robotic metrology, the capability to deploy a sensor to the optimum pose for a measurement task is essential to reduce cycle times and increase measurement quality. Doing so requires knowledge of the 3D sensor capabilities on a material specific basis, as the optical properties of a surface, object shape, pose and even the measurement itself have severe implications for the data quality. This need is not reflected in the current state of sensor haracterisation standards which commonly utilise optically compliant artefacts and therefore can not inform the user of a 3D sensor the realistic expected performance on non-ideal objects.This thesis presents a method of scoring candidate viewpoints for their ability to perform geometric measurements on an object of arbitrary surface finish. This is achieved by first defining a technology independent, empirical sensor characterisation method which implements a novel variant of the commonly used point density point cloud quality metric, which is normalised to isolate the effect of surface finish on sensor performance, as well as the more conventional assessment of point standard deviation. The characterisation method generates a set of performance maps for a sensor per material which are a function of distance and surface orientation. A sensor simulation incorporates these performance maps to estimate the statistical properties of a point cloud on objects with arbitrary shape and surface finish, providing the sensor has been characterised on the material in question.A framework for scoring measurement specific candidate viewpoints is presented in the context of the geometric inspection of four artefacts with different surface finish but identical geometry. Views are scored on their ability to perform each measurement based on a novel view score metric, which incorporates the expected point density, noise and occlusion of measurement dependent model features. The simulation is able to score the views reliably on all four surface finishes tested, which range from ideal matt white to highly polished aluminium. In 93% of measurements, a set of optimal or nearly optimal views is correctly selected.</div

Optimisation of surface coverage paths used by a non-contact robot painting system

This thesis proposes an efficient path planning technique for a non-contact optical “painting” system that produces surface images by moving a robot mounted laser across objects covered in photographic emulsion. In comparison to traditional 3D planning approaches (e.g. laminar slicing) the proposed algorithm dramatically reduces the overall path length by optimizing (i.e. minimizing) the amounts of movement between robot configurations required to position and orientate the laser. To do this the pixels of the image (i.e. points on the surface of the object) are sequenced using configuration space rather than Cartesian space. This technique extracts data from a CAD model and then calculates the configuration that the five degrees of freedom system needs to assume to expose individual pixels on the surface. The system then uses a closest point analysis on all the major joints to sequence the points and create an efficient path plan for the component. The implementation and testing of the algorithm demonstrates that sequencing points using a configuration based method tends to produce significantly shorter paths than other approaches to the sequencing problem. The path planner was tested with components ranging from simple to complex and the paths generated demonstrated both the versatility and feasibility of the approach

Enabling Premixed Hydrogen-Air Combustion for Aeroengines via Laboratory Experiment Modeling

All combustion systems from large scale power plants to the engines of cars to gas turbines in aircraft are looking for new fuel sources. Recently, clean energy for aviation has come into the foreground as an important issue due to the environment impacts of current combustion methods and fuels used. The aircraft industry is looking towards hydrogen as a new, powerful, and clean fuel of the future. However there are several engineering and scientific challenges to overcome before hydrogen can be deployed into the industry. These issuesrange from storing the hydrogen in a viable cryogenic form for an aircraft to stably burning the hydrogen in different phases during flight. Since a fundamental aspect, the fuel source (usually kerosene), is being switched to hydrogen, extensive modeling and ground testing of a future engine is required before a gas turbine engine can be retrofitted to work with hydrogen or built from the ground up. Modeling and simulating turbofan engine components can complement the engineering design process by allowing designs to be tested before beingimplemented into an actual turbofan engine. This allows an engineer to build confidence around a given design. Actual testing of gas turbine engines and their turbomachinery components is expensive and modeling these devices can help mitigate some of the cost and reduce potentially fatal errors in the design of the engine. In this thesis, several models are developed that allow for the study of hydrogen in a laboratory environment, and are compared to past works, industry software and data. This includes a 0D turbofan engine model and computational fluid dynamics simulations of a laboratory scale burner. The results formed in this work establish that the initial design of the burner and codes developedhere can serve as a foundation for future experiments and aid in the pursuit of achieving agas turbine engine operating with hydrogen-air mixtures