Abstract
Articulated Arms Coordinate Measuring Machines (AACMMs) have spread out in the manufacturing industry thanks to their flexibility and reduced cost. Nevertheless, their performance has been barely studied unlike traditional coordinate measuring machines. Therefore, a lack of traceability and reliability have been found AACMM field. AACMM performance is affected by many factors which are partially studied and compensated. Among them, human factor is one of the main factors with a significant impact on AACMM performance, however it is not considered in current evaluation or calibration methodologies. In this work, a new methodology is presented in order to calculate operator contribution to AACMM errors. Furthermore, operator behavior changes according to the measured feature and type of tolerance. For this reason, a features-based gauge capable of materialize a wide range of tolerances types has been designed and built for using with this methodology. Test results provide with a reasonable basis for performing both operator and AACMM qualification.
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