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Machine tool performance testing, as defined by ISO 230 and ANSI B5.54, has been successfully used to maintain and improve the accuracy and repeatability of production-level machine tools. In this study, a controlled series of experiments have been used to test the efficacy of these performance tests in the prediction of part form errors. Results are shown for flatness, squareness, position, and profile tolerances. The experimental results suggest that standard machine tool performance tests can also be used to predict the “best-case” tolerances that can be achieved for particular part features.

The increasing use of robots in a variety of production applications has led to a rapid growth in the development of languages for off-line robot programming. In this paper we present a survey of the languages currently available for the off-line programming of robots, discuss performance measures that could be used to categorize these languages, point out current technological barriers to off-line robot programming, and make some predictions regarding future trends in this important area.

It is shown that the volumetric errors of a three-axis machine tool or measuring machine can be determined by measuring the displacement error along 22 lines in the machine work zone. Pitch and yaw are derived from measuring the displacement error on two parallel lines for each axis. The squareness and straightness errors are determined by measuring two diagonals and one additional line. Roll errors are derived from the straightness errors on two parallel planes. Formulae for calculating these components of error and also the three-dimensional positioning error at any particular point are given. Experiments show that this method simplifies machine calibration, reduces the equipment needed, and can improve accuracy.