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Methods of evaluation of the positioning capability of Cartesian and non-Cartesian machines

Longstaff, Andrew P. (2002) Methods of evaluation of the positioning capability of Cartesian and non-Cartesian machines. Doctoral thesis, University of Huddersfield.

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    Manufacture and assembly of ever more precise components has been the driving force for
    many research projects. Error avoidance and error correction are used to improve the
    accuracy of the final output, but it is only by error evaluation that a manufacturer can
    quantify his production capability.

    The ability of a machine to perform the task designated to it is of critical importance.
    In particular it is essential to be able to determine the capability of a production machine to
    produce a part accurately, a measuring machine to dimension a part reliably or a handling
    machine to place a part in the appropriate position. In order to achieve this it is necessary to
    establish the positioning accuracy of the device throughout its working volume.

    In addition to the need for the assessment of machining performance, there is a
    strong desire within the machine-building community to allow for the post-assembly
    correction of errors inherent in the manufacture of machines. Such techniques are often a
    cost-effective complement to error avoidance.

    During this project, a new geometric model and supporting measurement methods
    are produced for the evaluation of errors in Cartesian-based machines. This work is an
    extension of that performed by Ford, et. al. Ell as discussed in chapter 3. The new work
    addresses the previously unresolved problem of determining the errors throughout the
    working volume of a machine with volumetric compensation and a tool or probe offset. This
    simulation method is in contrast to other techniques that quantify machine performance
    based upon a small subset of the machine volume.

    It is proposed that a figure for volumetric accuracy derived from these methods
    cannot stand on its own as a description of the manufacturing capability of a machine. The
    effects of measurement uncertainty on the synthesis technique have been examined and
    modelled. This has produced a method of quantifying machining capability based upon
    machine configuration, tool or head configuration, and supported by uncertainty based upon
    the test data input to the model.

    An alternative method of evaluating errors through the working volume is to
    measure directly using, for example, a tracking laser. One such system (LaserTrace) is
    based upon absolute position being resolved by trilateration from two tracking lasers. This
    system has been investigated for its applicability to the measurement process. Two methods
    have been produced to improve the accuracy of the system and reduce the time required for
    its calibration. One is based upon photogrammetry techniques, the other on a novel use of a
    checking gauge (MCG). The artefact is used for acquisition of data to perform
    parameter identification on a model of the system that has been found from first principles.

    This MCG-based calibration technique was successful, within the constraints of the
    resolution and repeatability of the control loop. Attempts were then made to apply this
    methodology to a second machine of the non-Cartesian type and configuration (UMD).
    Simulation shows this technique to be applicable, but the instability of the prototype
    precluded comprehensive on-machine testing.

    In the course of this research a thennal model of the UMD has also been produced to
    overcome the sensitivity of the prototype device to temperature changes. Such a model
    could be used to provide software correction of LTMD position values.

    Item Type: Thesis (Doctoral)
    Additional Information: EThOS Persistent ID
    Uncontrolled Keywords: Machine performance, Machinery Tools, Machinery
    Subjects: T Technology > TJ Mechanical engineering and machinery
    Schools: School of Computing and Engineering
    School of Computing and Engineering > Centre for Precision Technologies
    School of Computing and Engineering > Centre for Precision Technologies > Engineering Control and Machine Performance Research Group
    Related URLs:
    Depositing User: Graham Stone
    Date Deposited: 22 Oct 2009 15:50
    Last Modified: 25 Nov 2010 10:07


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