scholarly journals 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

2019 ◽  
Vol 10 (1) ◽  
pp. 37 ◽  
Author(s):  
Michaela Kritikos ◽  
Lissette Concepción Maure ◽  
Alfredo Alejandro Leyva Céspedes ◽  
Daynier Rolando Delgado Sobrino ◽  
Róbert Hrušecký

This paper addresses the uncertainty analysis in the case of a coordinate measuring machine. The main goal was analyzing, quantifying, and drawing conclusions on the influence of key factors and their interactions on the measurements’ uncertainty of the variable’s parallelism, angularity, roundness, diameter, and distance. In order to achieve this goal, a Random Factorial Design of Experiments was designed and implemented. It focused on the factors Stylus diameter, Step width, and Speed using three random levels each. For the solution of the experiment, an analysis of variance was used. The study was carried out on the coordinate measuring machine (CMM) ZEISS CenterMax. It was concluded that the interaction effects among Stylus diameter, Step width, and Speed were active at a confidence level of 95%. Besides, it was possible to estimate random factors‘ variance and their contribution to the total variation. Among the main effects, the Stylus diameter showed to be the one with the biggest influence. The paper also quantifies the influence in the measurement uncertainty, where the highest value of standard uncertainty belonged to the Stylus diameter in the evaluation of the variable’s angularity and diameter. Besides, the Speed factor was proved to have the biggest influence on the roundness’ measurement and evaluation.

2006 ◽  
Vol 66 (3-4) ◽  
pp. 198-207 ◽  
Author(s):  
Raúl Molina ◽  
Fernando Martínez ◽  
Juan Antonio Melero ◽  
David H. Bremner ◽  
Anand G. Chakinala

2014 ◽  
Vol 2 (20) ◽  
pp. 7509-7516 ◽  
Author(s):  
D. Eric Shen ◽  
Leandro A. Estrada ◽  
Anna M. Österholm ◽  
Danielle H. Salazar ◽  
Aubrey L. Dyer ◽  
...  

A fractional factorial design of experiments allowed us to optimize the areal capacitance of electropolymerized films over 7 variables using a dramatically reduced set of experiments.


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