Characterization of Geometric Surface Features Using Statistically Based Analytical Tools
General Material Designation
[Thesis]
First Statement of Responsibility
Azimi, Farzad
Subsequent Statement of Responsibility
Mullany, Brigid
.PUBLICATION, DISTRIBUTION, ETC
Name of Publisher, Distributor, etc.
The University of North Carolina at Charlotte
Date of Publication, Distribution, etc.
2019
GENERAL NOTES
Text of Note
256 p.
DISSERTATION (THESIS) NOTE
Dissertation or thesis details and type of degree
Ph.D.
Body granting the degree
The University of North Carolina at Charlotte
Text preceding or following the note
2019
SUMMARY OR ABSTRACT
Text of Note
The nature and quality of a surface's topography can play an important role in a part's performance and expected longevity. The complexity of a surface topography means that while commonly used ISO 25178-2 height based statistical metrics are capable of quantifying periodicity and directionality, they are unable to completely describe geometric isolated surface features, i.e. unwanted processing defects. The same standard does outline other metrics capable to describing geometric features, but these require more processing and user input. This dissertation presents a novel approach for quantifying both surface characteristics and features by calculating simple statistical height data metrics as a surface is rotated about its center and then graphing them in a polar plot format. Key polar plots metrics such as minimum and maximum radius, number of lobes and difference between their angular locations, etc. can be used to quantify surface isotropy, surface directionality, and surface periodicity. Uniquely, analysis of the polar plots can also provide estimates of the number and geometric sizes of isolated circular and linear geometric surface features. The capabilities and limitations of the approach are outlined, and discussed with respect to actual surfaces topographies. The simplicity, and potential speed of the method addresses the ever-present industrial need for fast, robust methods of surface characterization.