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Abstract

This paper presents optimisation of a measuring probe path in inspecting the prismatic parts on a CMM. The optimisation model is based on: (i) the mathematical model that establishes an initial collision-free path presented by a set of points, and (ii) the solution of Travelling Salesman Problem (TSP) obtained with Ant Colony Optimisation (ACO). In order to solve TSP, an ACO algorithm that aims to find the shortest path of ant colony movement (i.e. the optimised path) is applied. Then, the optimised path is compared with the measuring path obtained with online programming on CMM ZEISS UMM500 and with the measuring path obtained in the CMM inspection module of Pro/ENGINEERĀ® software. The results of comparing the optimised path with the other two generated paths show that the optimised path is at least 20% shorter than the path obtained by on-line programming on CMM ZEISS UMM500, and at least 10% shorter than the path obtained by using the CMM module in Pro/ENGINEERĀ®.

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Authors and Affiliations

Slavenko M. Stojadinovic
Vidosav D. Majstorovic
Numan M. Durakbasa
Tatjana V. Sibalija
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Abstract

This paper presents a multivariate regression predictive model of drift on the Coordinate Measuring Machine (CMM) behaviour. Evaluation tests on a CMM with a multi-step gauge were carried out following an extended version of an ISO evaluation procedure with a periodicity of at least once a week and during more than five months. This test procedure consists in measuring the gauge for several range volumes, spatial locations, distances and repetitions. The procedure, environment conditions and even the gauge have been kept invariables, so a massive measurement dataset was collected over time under high repeatability conditions. A multivariate regression analysis has revealed the main parameters that could affect the CMM behaviour, and then detected a trend on the CMM performance drift. A performance model that considers both the size of the measured dimension and the elapsed time since the last CMM calibration has been developed. This model can predict the CMM performance and measurement reliability over time and also can estimate an optimized period between calibrations for a specific measurement length or accuracy level.
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Authors and Affiliations

Eduardo Cuesta
Braulio Alvarez
Fernando Sanchez-Lasheras
Daniel Gonzalez-Madruga

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