Investigation and development of an advanced virtual coordinate measuring machine

This thesis was submitted for the degree of Doctor of Philosophy and was awarded by Brunel UniversityDimensional measurement plays a critical role in product development and quality control. With the continuously increasing demand for tighter tolerances and more complex workpiece shapes in the industry, dimensional metrology often becomes the bottleneck of taking the quality and performance of manufacturing to the next level. As one kind of the most useful and powerful measuring instruments, coordinate measuring machines (CMMs) are widely employed in manufacturing industries. Since the accuracy and efficiency of a CMM have a vital impact on the product quality, productivity and manufacturing cost, the evaluation and improvement of CMM performance have always been important research topics since the invention of CMM. A novel Advanced Virtual Coordinate Measuring Machine (AVCMM) is proposed against such a background. The proposed AVCMM is a software package that provides an integrated virtual environment, in which user can plan inspection strategy for a given task, carry out virtual measurement, and evaluate the uncertainty associated with the measurement result, all without the need of using a physical machine. The obtained estimate of uncertainty can serve as a rapid feedback for user to optimize the inspection plan in the AVCMM before actual measurement, or as an evaluation of the result of a performed measurement. Without involving a physical CMM in the inspection planning or evaluation of uncertainty, the AVCMM can greatly reduce the time and cost needed for such processes. Furthermore, as the package offers vivid 3D visual representation of the virtual environment and supports operations similar to a physical CMM, it does not only allow the user to easily plan and optimise the inspection strategy, but also provide a cost-effective, risk-free solution for training CMM operators. A modular, multitier architecture has been adopted to develop the AVCMM system, which incorporates a number of functional components covering CMM and workpiece modelling, error simulation, inspection simulation, feature calculation, uncertainty evaluation and 3D representation. A new engine for detecting collision/contact has been developed and utilized, which is suitable for the virtual environment of simulated CMM inspections. A novel approach has been established to calculate errors required for the error simulation, where the data are obtained from FEA simulations in addition to conventional experimental method. Monte Carlo method has been adopted for uncertainty evaluation and has been implemented with multiple options available to meet different requirements. A prototype of the proposed AVCMM system has been developed in this research. Its validity, usability and performance have been verified and evaluated through a set of experiments. The principles for utilising the AVCMM in practical use have also been established and demonstrated. The results have indicated that the proposed AVCMM system has great potentials to improve the functionalities and overall performance of CMMs.ORSAS and the School of Engineering and Design of Brunel University

The evaluation of a novel haptic machining VR-based process planning system using an original process planning usability method

This thesis provides an original piece of work and contribution to knowledge by creating a new process planning system; Haptic Aided Process Planning (HAPP). This system is based on the combination of haptics and virtual reality (VR). HAPP creates a simulative machining environment where Process plans are automatically generated from the real time logging of a user’s interaction. Further, through the application of a novel usability test methodology, a deeper study of how this approach compares to conventional process planning was undertaken. An abductive research approach was selected and an iterative and incremental development methodology chosen. Three development cycles were undertaken with evaluation studies carried out at the end of each. Each study, the pre-pilot, pilot and industrial, identified progressive refinements to both the usability of HAPP and the usability evaluation method itself. HAPP provided process planners with an environment similar to which they are already familiar. Visual images were used to represent tools and material whilst a haptic interface enabled their movement and positioning by an operator in a manner comparable to their native setting. In this way an intuitive interface was developed that allowed users to plan the machining of parts consisting of features that can be machined on a pillar drill, 21/2D axis milling machine or centre lathe. The planning activities included single or multiple set ups, fixturing and sequencing of cutting operations. The logged information was parsed and output to a process plan including route sheets, operation sheets, tool lists and costing information, in a human readable format. The system evaluation revealed that HAPP, from an expert planners perspective is perceived to be 70% more satisfying to use, 66% more efficient in completing process plans, primarily due to the reduced cognitive load, is more effective producing a higher quality output of information and is 20% more learnable than a traditional process planning approach

Coordinate Measuring Machine (CMM) inspection planning and knowledge capture – formalising a black art

In manufacturing, the automated elicitation of engineering knowledge is a major challenge due to the increasing knowledge-intensive processes and systems used in industry. Capturing and formalizing engineering knowledge is a highly costly and time-consuming task. The existing literature covers little in this field, leaving unanswered the technical difficulties of capturing and representing knowledge in Coordinate Measuring Machine (CMM) inspection planning applications. This work presents the Inspection Planning and Capturing Knowledge (IPaCK) system, a novel paradigm for the automated capturing and formalising of human centred expertise in the field of CMM planning. The proposed solution is an innovative physical setup using a simple tracked hand-held probe that facilitates intuitive planning of a CMM measurement strategy as a user interacts with a real component. As the sequence is generated, in real time a motion tracking-based digital tool logs user activity throughout the task. A post processor then converts log file data into multiple formalised outputs representing the knowledge created and utilised during the CMM inspection planning task. Experienced CMM inspection planners validated IPaCK’s potential to produce knowledge representations of CMM planning strategies that were useful, relevant and accurate. A comparison of planning strategies resulted in the detection of measurement patterns; embedding both inspection planning knowledge and experience, constituting the first known implementation of automatically capturing best practice and defining benchmarks to evaluate future planning strategies. A task completion time (TCT) comparison against a conventional CMM showed that IPaCK facilitates faster measurement planning and part programming. On using the system, novice planners rated IPaCK and its knowledge representations to provide significant metacognition support to CMM planning and training. Experienced planners confirmed IPaCK’s knowledge capture capability and that the formats were industry acceptable, relevant and beneficial in inspection planning tasks. IPaCK could be at the heart of the next generation of CMM inspection planning systems; one that automatically captures and formalises inspection planning knowledge and experience in multiple outputs. This thesis presents the underpinning science and technology to realise the implementation

Error compensation and uncertainty evaluation of CMMs based on kinematic error models and gaussian processes

This thesis was submitted for the degree of Masters of Philosophy and awarded by Brunel University London.Given the increasing demand for precision engineering applications, the evaluation of measurement error and uncertainty has been the focus of intensive research to meet the requirements of precision manufacturing processes. Systematic errors of mechanical components affect the accuracy of the production parts. It is therefore best to analyse the geometric accuracy of machine tools before production processes begin. This proposed method is based on simulation in the MATLAB programme, which investigates the influence of the geometric errors of the Coordinate Measuring Machine (CMM) on the calibration. The advantages of this measurement procedure are reduced physical measuring times, reduced measurement uncertainties as well as volumetric measurement, and compensation for CMM geometric errors. In this research, theoretical modelling of the local, kinematic error model and the Gaussian Process (GP) model are presented and explored in depth. These proposed methods are simulations providing an integrated virtual environment in which user can generate the inspection path planning for specific tasks and evaluate the errors and uncertainty associated with the measurement results, all without the need to perform a number of physical CMM measurements. The estimated errors and uncertainty can serve as rapid feedback for users before performing actual measurements or as a prior evaluation of the results of the CMM calibrations. The estimation of CMM geometric errors are usually described using 21 kinematic errors which consist of three positional and three rotational error functions for each of the three axes, along with three squareness errors. This assumes that the method to estimate of these kinematic errors can be generated by performing an artefact measurement such as for a hole or a ball plate in the numbers of the positions of the CMM working region and then matching the kinematic errors to the measured changes in artefact geometry. The process validation of a local, kinematic error model and a GP model has been determined with the design and analysis of CMM measurement using a ball plate as an artefact, calculating the percentage error to compare their effective results. This research project has led to the following contribution to knowledge: Mathematical model development for making effective choices regarding the local, kinematic error model and GP model is performed and formulated; this is verified by particular kinematic errors of the CMM measurements, presenting high accuracy and reliability of the error and uncertainty evaluation performance. The improvement achieved by the proposed method over the traditional approaches between the simulated datasets and actual CMM data measurements has been demonstrated. The numerical simulations with a well-designed strategy providing accurate estimates of the CMM kinematic errors using only a nominal CMM calibration with a ball plate have been validated and evaluated in both approaches. The influences of kinematic errors affected through the measurement process of the CMM on the calibration have been investigated.Royal Thai Government, Ministry of Sciences and Technology and National Institute of Metrology Thailand (NIMT)

Investigation of 3DP technology for fabrication of surgical simulation phantoms

The demand for affordable and realistic phantoms for training, in particular for functional endoscopic sinus surgery (FESS), has continuously increased in recent years. Conventional training methods, such as current physical models, virtual simulators and cadavers may have restrictions, including fidelity, accessibility, cost and ethics. In this investigation, the potential of three-dimensional printing for the manufacture of biologically representative simulation materials for surgery training phantoms has been investigated. A characterisation of sinus anatomical elements was performed through CT and micro-CT scanning of a cadaveric sinus portion. In particular, the relevant constituent tissues of each sinus region have been determined. Secondly, feedback force values experienced during surgical cutting have been quantified with an actual surgical instrument, specifically modified for this purpose. Force values from multiple post-mortem subjects and different areas of the paranasal sinuses have been gathered and used as a benchmark for the optimisation of 3D-printing materials. The research has explored the wide range of properties achievable in 3DP through post-processing methods and variation of printing parameters. For this latter element, a machine-vision system has been developed to monitor the 3DP in real time. The combination of different infiltrants allowed the reproduction of force values comparable to those registered from cadaveric human tissue. The internal characteristics of 3D printed samples were shown to influence their fracture behaviour under resection. Realistic appearance under endoscopic conditions has also been confirmed. The utilisation of some of the research has also been demonstrated in another medical (non-surgical) training application. This investigation highlights a number of capabilities, and also limitations, of 3DP for the manufacturing of representative materials for application in surgical training phantoms

Optimising additive manufacturing for fine art sculpture and digital restoration of archaeological artefacts

Additive manufacturing (AM) has shown itself to be beneficial in many application areas, including product design and manufacture, medical models and prosthetics, architectural modelling and artistic endeavours. For some of these applications, coupling AM with reverse engineering (RE) enables the utilisation of data from existing 3D shapes. This thesis describes the application of AM and RE within sculpture manufacture, in order to optimise the process chains for sculpture reproduction and relic conservation and restoration. This area poses particular problems since the original artefacts can often be fragile and inaccessible, and the finishing required on the AM replicas is both complex and varied. Several case studies within both literature and practical projects are presented, which cover essential knowledge of producing large scale sculptures from an original models as well as a wide range of artefact shapes and downstream finishing techniques. The combination of digital technologies and traditional art requires interdisciplinary knowledge across engineering and fine art. Also, definitions and requirements (e.g. ‘accuracy’), can be applied as both engineering and artistic terms when specifications and trade-offs are being considered. The thesis discusses the feasibility for using these technologies across domains, and explores the potential for developing new market opportunities for AM. It presents and analyses a number of case study projects undertaken by the author with a view to developing cost and time models for various processes used. These models have then been used to develop a series of "process maps", which enable users of AM in this area to decide upon the optimum process route to follow, under various circumstances. The maps were validated and user feedback obtained through the execution of two further sculpture manufacturing projects. The thesis finishes with conclusions about the feasibility of the approach, its constraints, the pros and cons of adopting AM in this area and recommendations for future research

Autonomous Navigation of Automated Guided Vehicle Using Monocular Camera

This paper presents a hybrid control algorithm for Automated Guided Vehicle (AGV) consisting of two independent control loops: Position Based Control (PBC) for global navigation within manufacturing environment and Image Based Visual Servoing (IBVS) for fine motions needed for accurate steering towards loading/unloading point. The proposed hybrid control separates the initial transportation task into global navigation towards the goal point, and fine motion from the goal point to the loading/unloading point. In this manner, the need for artificial landmarks or accurate map of the environment is bypassed. Initial experimental results show the usefulness of the proposed approach.COBISS.SR-ID 27383808

Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations

Optimization of Operation Sequencing in CAPP Using Hybrid Genetic Algorithm and Simulated Annealing Approach

In any CAPP system, one of the most important process planning functions is selection of the operations and corresponding machines in order to generate the optimal operation sequence. In this paper, the hybrid GA-SA algorithm is used to solve this combinatorial optimization NP (Non-deterministic Polynomial) problem. The network representation is adopted to describe operation and sequencing flexibility in process planning and the mathematical model for process planning is described with the objective of minimizing the production time. Experimental results show effectiveness of the hybrid algorithm that, in comparison with the GA and SA standalone algorithms, gives optimal operation sequence with lesser computational time and lesser number of iterations