journal article·2021-02-24Open access

A Unique Model to Estimate Geometric Deviations in Drilling and Milling Due to Two Uncertainty Sources

Wilma Polini, Andrea Corrado

Applied Sciences· Volume 11· Issue 5

Abstract

Industry 4.0 involves the use of information and communication technologies to transform industry by intelligent networking machines and processes. The availability of big data sets from manufacturing and inspection allow for developing new and more accurate simulation models. This involves the development of new machining simulation models to consider the geometrical deviations of the workpiece due to the machine tool, the part datum surfaces and the fixturing equipment. This work presents a model that kinematically correlates the locator uncertainty, the form deviation on the part datum surface in contact with the locators and the volumetric uncertainty of the machine tool, with the geometric deviations of a surface due to a drilling or milling process. An analytical model was developed in a Matlab® file to simulate the surface geometrical deviations from nominal during drilling or milling. It is new as regards the state of the art because it takes into account two sources of uncertainty. This numerical approach allows for avoiding experimental tests, with a resultant saving of time, energy and material. It was applied to drilling, face milling and contouring processes. It was proved that machine tool volumetric uncertainty influences the form deviation of the machined surface, while the locator configuration and the datum form deviation affect the orientation of the machined surface, as should be in reality. The proposed model allows us to take into account geometrical deviations of the part datum surfaces of 0.001 mm, location deviations in the locators of ± 0.03 mm and machine tool positional and rotational uncertainties of 0.01 mm and σd=0.01∗π180 mm, respectively.
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Research context

OpenAlex topics: Advanced Measurement and Metrology Techniques · Advanced machining processes and optimization · Manufacturing Process and Optimization

SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.

Affiliations

Department of Civil and Mechanical Engineering, Università degli Studi di Cassino e del Lazio Meridionale, via G. di Biasio 43, 03043 Cassino, Italy

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