Statistical Analysis of Surface Texture Performance With Provisions With Uncertainty in Texture Dimensions
Author(s) -
Fan Mo,
Cong Shen,
Jia Zhou,
Michael M. Khonsari
Publication year - 2017
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2017.2694608
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
The performance of surface textures with dimensional uncertainty due to the manufacturing process is investigated with statistical models. The uncertainty parameters are geometrical dimensions (i.e., dimple diameter, area ratio, and dimple depth) and the performance parameters include the friction force, the load-carrying capacity, and the coefficient of friction. The results show that logarithmic models provide an excellent fit to the data and can explain more than 99.98% of the variance in data. The most critical geometric parameter for the coefficient of friction and the load-carrying capacity is found to be the dimple diameter, whereas the most critical geometric parameter for the friction force is the area ratio. Manufacturing errors that follow normal distribution with three-sigma quality are found to be insignificant. Under the conditions simulated, it is determined that a dimple diameter of 1883 μm and a dimple depth of 5.5~6.5 μm yield optimal performance when operating in the hydrodynamic lubrication regime. The area ratio is the key parameter and must be determined based on the requirements of the load-carrying capacity and the coefficient of friction.
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