The mathematical model of CMM measurements is very complex to reconstruct. ISO 15530-4 presents a method to estimate CMM measurement uncertainty without the need of the mathematical model of CMM measurements.

Coordinate measuring machine (CMM) has been used in many manufacturing industries, ranging from aerospace, automotive to consumer product, that mass-produces various types of parts.

ISO/DTS 15530-2 provide a way to estimate coordinate measuring machine (CMM) measurement uncertainties without using any complex calibrated artefacts. Instead, only a performance verified CMM and a standard calibrated gauge block are needed.

CMM measurement uncertainty estimation: Relevant uncertainty contributors

Calibration, performance verification and measurement uncertainty estimation are important activities for coordinate measuring machine (CMM) machine and measurement.

A coordinate measuring machine (CMM) is a complex measuring instrument. Hence, there are many error sources that cause the degradation of a CMM measurement accuracy and the increase of the uncertainty of the CMM measurement results.

In any CMM measurements, especially with a tactile-CMM, sampling strategy is very important. This Sampling strategy in CMM measurement affects not only measurement performance, but also measurement accuracy!

Part-alignment is a compulsory process that needs to be performed for CMM measurements. This process is performed right after the qualification process of CMM probing system. Only after part-alignment is performed, dimensional and geometrical measurements by a CMM can be carried out.

In this post, the vector diagram and the mathematics behind the qualification process of a probing system are presented.

In this post, important aspects regarding the probing system of tactile-CMM is discussed. By knowing these aspects, we can improve the efficiency and efficacy of dimensional and geometrical measurements with tactile-CMM.

Probing system in a tactile coordinate measuring machine (tactile-CMM) is a fundamental component that acts as sensor to detect whether a stylus tip has touched the surface of a measured part.

There is a general procedure to operate a tactile coordinate measuring machine (tactile-CMM). In this post, we will discuss this general procedure that can be implemented to all types of tactile-CMM from various manufacturers.

Coordinate measuring machine (CMM), especially tactile CMM, is the industry standard for dimensional and geometrical measurement. The use and application of CMM in manufacturing industry, from automotive, aerospace until space industry, have been matured and well-accepted.

Coordinate measuring machines (CMMs) have been well accepted as universal instruments to perform various types of dimensional and geometrical measurements. The measurements are performed by capturing or probing 3D spatial coordinate points (XYZ–coordinates) on the surface of a measured part.

Measuring dimension and geometry at micro-scale and Nano-scale is challenging. Because, at micro- and Nano-scale, there are additional effects that are not relevant at higher-scale measurements (than micro-scale measurement), but are very relevant at the micro- and Nano-scale.

This post will give a practical explanation about gauge repeatability and reproducibility (Gauge R&R or GR&R) test. Gauge R&R is one of measurement system analysis methods.

The invention of coordinate measuring machine (CMM) is a direct consequence of the need to verify dimensional tolerances (GD&T). In this post, the history behind the invention of CMM as well as a brief introduction about CMM is presented.

This post will discuss Spreadsheets method to estimate measurement uncertainties. This method is the most well-known and used method to estimate measurement uncertainties.

In quality inspection, measurement uncertainty has a fundamental role in deciding the conformance and non-conformance of a part.

In this post, three important aspects in measurement are concisely discussed. The three aspects are measurement model, systematic error and random error.

In this post, a method to estimate measurement uncertainties based on Monte-Carlo simulation is presented with examples.