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Automatic planning for machine tool calibration: A case study

Parkinson, Simon, Longstaff, Andrew P., Fletcher, Simon, Crampton, Andrew and Gregory, Peter (2012) Automatic planning for machine tool calibration: A case study. Expert Systems with Applications, 39 (13). pp. 11367-11377. ISSN 09574174

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    Abstract

    Machine tool owners require knowledge of their machine’s capabilities, and the emphasis increases with
    areas of high accuracy manufacturing. An aspect of a machine’s capability is its geometric accuracy. International
    Standards and best-practice guides are available to aid understanding of the required measurements
    and to advise on how to perform them. However, there is an absence of any intelligent method
    capable of optimising the duration of a calibration plan, minimising machine down-time. In this work,
    artificial intelligence in the form of automated planning is applied to the problem of machine tool
    pseudo-static geometric error calibration. No prior knowledge of Artificial Intelligence (AI) planning is
    required throughout this paper. The authors have written this paper for calibration engineers to see
    the benefits that automated planning can provide. Two models are proposed; the first produces a sequential
    calibration plan capable of finding the optimal calibration plan. The second model has the additional
    possibility of planning for concurrent measurements, adding the possibility of further reducing machine
    down-time. Both models take input regarding a machine’s configuration and available instrumentation.
    The efficacy of both models is evaluated by performing a case study of a five-axis gantry machine,
    whereby calibration plans are produced and compared against both an academic and industrial expert.
    From this, the effectiveness of this novel method for producing optimal calibration plan is evaluated,
    stimulating potential for future work.

    Item Type: Article
    Additional Information: NOTICE: this is the author’s version of a work that was accepted for publication in Expert Systems with Applications. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Expert Systems with Applications Volume 39, Issue 13, 1 October 2012, Pages 11367–11377 doi:10.1016/j.eswa.2012.03.054
    Subjects: Q Science > QA Mathematics > QA76 Computer software
    T Technology > TA Engineering (General). Civil engineering (General)
    Schools: School of Computing and Engineering
    School of Computing and Engineering > Centre for Precision Technologies > EPSRC Centre for Innovative Manufacturing in Advanced Metrology
    School of Computing and Engineering > Centre for Precision Technologies > Engineering Control and Machine Performance Research Group
    Related URLs:
    Depositing User: Simon Parkinson
    Date Deposited: 24 May 2012 10:57
    Last Modified: 04 Jun 2013 14:52
    URI: http://eprints.hud.ac.uk/id/eprint/13501

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