Defects in polyethylene film are often caused by contaminant particles in the polymer melt. In this research, particle properties obtainable from in-line melt monitoring, combined with processing information, are used to predict film defect properties.
“Model” particles (solid and hollow glass microspheres, aluminum powder, ceramic microspheres, glass fibers, wood particles, and cross-linked polyethylene) were injected into low-density polyethylene extruder feed. Defects resulted when the polyethylene containing particles was extruded through a film die and stretched by a take-up roller as it cooled to form films 57 to 241mm in thickness.
Two off-line analysis methods were further developed and applied to the defects: polarized light imaging and interferometric imaging. Polarized light showed residual stresses in the film caused by the particle as well as properties of the embedded particle. Interferometry enabled measures of the film distortion, notably defect volume. From the images, only three attributes were required for mathematical modeling: particle area, defect area, and defect volume. These attributes yielded two ”primary defect properties”: average defect height and magnification (of particle area). For all spherical particles, empirical correlations of these properties were obtained for each of the two major types of defects that emerged: high average height and low average height defects. Analysis of data for non-spherical particles was limited to showing how, in some cases, their data differed from the spherical particle correlations.
To help explain empirical correlations of the primary defect properties with film thickness, a simple model was proposed and found to be supported by the high average height defect data: the “constant defect volume per unit particle area” model. It assumes that the product of average defect height and magnification is a constant for all film thicknesses.
A numerical example illustrates how the methodology developed in this work can be used as a starting point for predicting film defect properties in industrial systems. A limitation is that each prediction yields two pairs of primary defect property values, one pair for each defect type. If it is necessary to identify the dominant type, then measurement of a length dimension of sufficient defects in the film is required.
Identifer | oai:union.ndltd.org:TORONTO/oai:tspace.library.utoronto.ca:1807/29967 |
Date | 15 September 2011 |
Creators | Farahani Alavi, Forouzandeh |
Contributors | Balke, Stephen Thomas, Sayad, Saed |
Source Sets | University of Toronto |
Language | en_ca |
Detected Language | English |
Type | Thesis |
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