Uncertainty Modeling and Evaluation of CMM Task Oriented Measurement Based on SVCMM

Abstract

Due to the variety of measurement tasks and the complexity of the errors of coordinate measuring machine (CMM), it is very difficult to reasonably evaluate the uncertainty of the measurement results of CMM. It has limited the application of CMM. Task oriented uncertainty evaluation has become a difficult problem to be solved. Taking dimension measurement as an example, this paper puts forward a practical method of uncertainty modeling and evaluation of CMM task oriented measurement (called SVCMM method). This method makes full use of the CMM acceptance or reinspection report and the Monte Carlo computer simulation method (MCM). The evaluation example is presented, and the results are evaluated by the traditional method given in GUM and the proposed method, respectively. The SVCMM method is verified to be feasible and practical. It can help CMM users to conveniently complete the measurement uncertainty evaluation through a single measurement cycle.

Misjudgement probability estimation of product inspection based on uncertainty

“…The present paper carries out product testing experiment by using the CMM with five products as examples to demonstrate the updated process of the value characteristic index when each product is measured in the full inspection. It also evaluates the uncertainty of the measurement information of the products and calculates the misjudgement rate based on the theoretical analysis [9, 10].…”

Metrology and Measurement Systems

“…The problem of estimation of task specific uncertainty, especially in industrial conditions, is still up-to-date and investigated by many research centres [14][15][16][17].…”

A Random Factorial Design of Experiments Study on the Influence of Key Factors and Their Interactions on the Measurement Uncertainty: A Case Study Using the ZEISS CenterMax

“…The clear majority of the methods and approaches for the measurement of uncertainty in CMM can be classified as mathematical, comparative, and performance test ones. The first group of these, also referred to as mathematical modeling methods, encompasses the same calibration of the CMM geometric errors, which is the base for the posterior creation of a theoretical model that allows predicting the uncertainty for all measurements executed according to the model's assumptions [5]. On the other hand, comparison methods usually involve the measurement of an "identical" calibrated part, often referred to as artifact.…”