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dc.contributor.advisorRizvi, Ghaus
dc.contributor.authorAl-Sadi, Jamal
dc.date.accessioned2015-11-03T20:51:55Z
dc.date.accessioned2022-03-29T17:52:54Z
dc.date.available2015-11-03T20:51:55Z
dc.date.available2022-03-29T17:52:54Z
dc.date.issued2015-01-01
dc.identifier.urihttps://hdl.handle.net/10155/579
dc.description.abstractDemand for plastic products is continuously growing with population increase and higher living standards. Imparting colours to plastics is a combination of art and science and plays a key role in production of attractive products for a variety of consumer demands. It requires a good understanding of the processing parameters and formulation of compositions including colour pigments and their dispersion. This thesis presents experimental observations and statistical analysis to investigate scientific reasons for colour mismatches in compounded plastics. Material processing issues were investigated. Six methods were used to study and improve the understanding of colour matching, colour stability, and consistency of compounded plastic materials in order to minimize wastage. The first was Data Mining, in which historical data was analyzed to select formulations, particularly for pigments and polycarbonate blends of compounded plastics that were known to suffer from colour mismatch. The second method involved the use of historical data and an artificial neural network (ANN) to predict the resultants colours based upon pigment formulations. In the third method, a parametric study was utilized to investigate issues in the dispersion of pigments due to the effects of processing conditions. Temperature and feed rate were found to have major effects on colour deviations. The fourth method involved studying the compounding process for blends of two polycarbonate resins (PC) of different melt flow index (MFI). It was also found that the PC composition of 30-70 wt.% was superior in terms of colour matching. The fifth method studied effects of rheology. The viscosity data collected allows predictions of viscosity changes with varying temperatures, which had a direct impact on polymer colour changes during processing of blends. The sixth method looked at the effects of processing parameters on dispersion, pigment size distribution (PSD), and the morphology of pigments in polycarbonate compounds. In general, the total colour difference decreased when processing parameters were increased. De-agglomeration occurred in zones of high shear and was found to significantly increase the number of particles and lower colour differences. The results yield an optimum set of processing parameters for certain grades of plastic. The optimized measurements of processing conditions are typically in agreement with the minimum colour difference. Furthermore, many conclusions found here can be used to optimize compounding materials and generate an efficient dispersion process, and hence reduce colour mismatch so that wastage is minimized.en
dc.description.sponsorshipUniversity of Ontario Institute of Technologyen
dc.language.isoenen
dc.subjectData Miningen
dc.subjectNeural network modelingen
dc.subjectProcessing parameters (DOE)en
dc.subjectPolycarbonate blends and rheologyen
dc.subjectColour matching and morphological dispersionen
dc.titleColour mismatch in compounding of plastics: processing issues and rheological effectsen
dc.typeDissertationen
dc.degree.levelDoctor of Philosophy (PhD)en
dc.degree.disciplineMechanical Engineeringen


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