An Approach Based on the Exploratory Data Analysis to Relate the Wear Behavior with the Microstructure of Ductile Cast Irons

Abstract

The aim of this work is to propose a new methodology to relate Ductile Cast Irons (DCIs) wear behavior with the separation distances and sizes of the graphite nodules through an Exploratory Data Analysis (EDA). This methodology consists of morphological image processing tools (compacity and size distribution curves), an EDA performed by the use of box plots and an EDA-based section classifying algorithm. This algorithm classifies the microstructure of DCIs into classes and levels grouping different behaviors of the separation distances and sizes of graphite nodules. Finally, it was found, through a number of tribological tests, that the obtained classes and levels have a different wear behavior. The results achieved by this methodology were compared with those of traditional techniques used to characterize the microstructure of the material.

Analysis on Behavior Characteristics of Enterprise Financing Investment Risk Data

“…For the new enterprise financing investment risk subset, we need to optimize and perfect the traditional subset [ 6 ]. The selection of risk factors for financing investment of enterprises should be more dynamic and complicated, and should also be integrated into the characteristics of enterprises themselves [ 7 ]. If the selected indicators are not appropriate, the investment loss of enterprises will be caused, so each factor must be carefully screened.…”

Multivariate analysis: An essential for studying complex glasses

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INVESTIGASI MORFOLOGI TWDI (Thin Wall Ductile Iron)AKIBAT PROSES MULTI STAGE SPHEROIDISING

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