Consideration of the Measurement Uncertainty in the Assembling of Components Characterized by High Dimensional Variation

2013 Joint IMEKO (International Measurement Confederation) TC1-TC7-TC13 Symposium: Measurement Across Physical and Behavioural Sciences

Hernández, C.^1 ; Tutsch, R.^1

Institut für Produktionsmesstechnik, Technische Universität Braunschweig, Schleinitzstrasse 20, D-38106 Braunschweig, Germany^1

关键词: Assembling techniques;    Capability indices;    Dimensional specifications;    Dimensional variations;    In-line measurements;    Measurement uncertainty;    Process capabilities;    Statistical dynamics;   

Others  :  https://iopscience.iop.org/article/10.1088/1742-6596/459/1/012037/pdf
DOI  :  10.1088/1742-6596/459/1/012037

来源: IOP

【 摘 要 】

The Statistical Dynamic Specifications Method (SDSM) relies on in-line measurements to manage dimensional specifications, target and tolerance. SDSM is the cornerstone of an innovative assembling technique based on the Statistical Feed-Forward Control Model (SFFCM) for processes in which the stacked dimensional variation of the assembled components reaches the order of the total allowed tolerance. Since the magnitude of such variation might jeopardize the process capability, it is a matter of interest to study the inclusion of the measurement uncertainty when applying SDSM on a target subprocess. By means of simulating the production of assemblies made of parts having high dimensional variation, a set of experiments were designed to compare the impact of different levels of measurement uncertainty on the capability of a target subprocess. Simulation results showed that depending on the magnitude of the uncertainty the capability index cpof the target subprocess increases between 2.5% and 34.5% from 1.27 to 1.82 as a direct consequence of adjusting the respective tolerance. Thus, the inclusion of the measurement uncertainty in the proposed SDSM has a significant impact in its practical realization since a decrement in cpimplies an increment of the scrap percentage of the target subprocess.