Using automatic machine vision-based systems, the calibration of measuring instruments can be extended. With machine vision it is possible to check hundreds of points on the scale of a dial indicator, giving new insight into its sources of error. This paper describes a machine vision-based system for the calibration of dial indicators developed at the Centre for Metrology and Accreditation in Finland, with emphasis on the calculation of measurement uncertainty.

The calibration of simple handheld instruments is often more expensive than the price of a new device. Therefore, the amount of manual labour is kept at a minimum in order to keep the price of calibration at a tolerable level. This also means that only a few points of e.g. a length scale can be checked. By using automatic machine vision based systems, the calibration of measurement instruments can be done faster and more thoroughly. In order to study the possibilities of machine vision automation for volume calibration tasks a set-up for micrometer calibration was constructed at Centre for Metrology and Accreditation (MIKES). With the developed automated machine vision system it is possible to check hundreds of points on the scale of a micrometer, giving new insight into error sources of the micrometer screw. The attained uncertainty is at the same level as calibration with gauge blocks according to ISO 3611.

Small angle generators are simple devices for providing small angles traceable to the definition of the SI-unit radian. The most accurate ones use a laser interferometer for measurement of angular displacement. Small angle generators used for autocollimator calibration usually create angles around a single axis. A two-directional angle generator would be preferable, as it could more efficiently reveal artefacts related to angular displacement across both axes, such as orthogonality of the autocollimator's measuring axes. Characterizing errors depending on one axis only would also be easier, as the setup needs to be aligned only once for studying both axes of the autocollimator. We describe a novel interferometric two-directional small angle generator which we have built and tested for autocollimator calibration. The range is ±1000″ for both axes. The estimated standard uncertainty for full range is 0.0036″ for the horizontal and 0.0053″ for the vertical direction.

The use of an optical coordinate measuring machine (CMM) for the diameter measurement of optical apertures is described. The traceability and mechanical stability of the aperture areas are of importance for accurate photometric and radiometric measurements. Detailed evaluation of the measurement uncertainty for the aperture diameter is presented. High-accuracy mechanical CMM was used to confirm the validity of the optical CMM results. The difference between the contact and non-contact measurement was 0.1 mm for the mean diameter result. If the required standard uncertainty for the mean diameter is of the order of 1 mm, the optical CMM provides an efficient method for aperture area measurements. Ã Optical radiometry is the field of science which studies the measurement of electromagnetic radiation, including visible light. Light is also measured using the techniques of photometry that deal with brightness as perceived by the human eye.

In craniomaxillofacial surgical procedures, an emerging practice adopts the preoperative virtual planning that uses medical imaging (computed tomography), 3D thresholding (segmentation), 3D modeling (digital design), and additive manufacturing (3D printing) for the procurement of an end-use implant. The objective of this case study was to evaluate the cumulative spatial inaccuracies arising from each step of the process chain when various computed tomography protocols and thresholding values were independently changed. A custom-made quality assurance instrument (Phantom) was used to evaluate the medical imaging error. A sus domesticus (domestic pig) head was analyzed to determine the 3D thresholding error. The 3D modeling error was estimated from the computer-aided design software. Finally, the end-use implant was used to evaluate the additive manufacturing error. The results were verified using accurate measurement instruments and techniques. A worst-case cumulative error of 1.7 mm (3.0%) was estimated for one boundary condition and 2.3 mm (4.1%) for two boundary conditions considering the maximum length (56.9 mm) of the end-use implant. Uncertainty from the clinical imaging to the end-use implant was 0.8 mm (1.4%). This study helps practitioners establish and corroborate surgical practices that are within the bounds of an appropriate accuracy for clinical treatment and restoration.

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