Designing and analyzing a mixture experiment to optimize the mixing proportions of polyvinyl chloride composites

Altarazi, Safwan; Allaf, Rula M.

doi:10.1080/02664763.2016.1214243

Cited by 9 publications

(4 citation statements)

References 19 publications

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“…Detailed information about the applied process has been published previously (Altarazi et al, 2019). The statistical method of mixture design was used to design the experiments for the production of the HDPE film (Altarazi & Allaf, 2017). The parameters of the blend ingredients and processing variables were included.…”

Section: Methodsmentioning

confidence: 99%

Vision-based Online Defect Detection of Polymeric Film via Structural Quality Metrics

Rawashedeh,

Hazaveh,

Altarazi

2023

Management and Production Engineering Review

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Nondestructive and contactless online approaches for detecting defects in polymer films are of significant interest in manufacturing. This paper develops vision-based quality metrics for detecting the defects of width consistency, film edge straightness, and specks in a polymeric film production process. The three metrics are calculated from an online low-cost grayscale camera positioned over the moving film before the final collection roller and can be implemented in real-time to monitor the film manufacturing for process and quality control. The objective metrics are calibrated to correlate with an expert ranking of test samples, and results show that they can be used to detect defects and measure the quality of polymer films with satisfactory accuracy.

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Section: Methodsmentioning

confidence: 99%

Vision-based Online Defect Detection of Polymeric Film via Structural Quality Metrics

Rawashedeh,

Hazaveh,

Altarazi

2023

Management and Production Engineering Review

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“…The extruder was equipped with a conventional film-blowing die with a diameter of 60 mm and a film-blowing tower with a calendering nip and takeoff rolls. The blow molding formulation and processing parameters (filler size, temperatures of the extruder’s four heaters, the extruder’s mixing speed, and the bubble drawing up speed) were manipulated according to a Minitab-prepared mixture design with extreme vertices and processing variables set as shown in Table 1, which resulted in a total of 86 experimental runs [32]. Table S1, in the supplementary materials, provide the full experimental data set for the extrusion-blow molding.…”

Section: Experimental Dataset Developmentmentioning

confidence: 99%

Machine Learning Models for Predicting and Classifying the Tensile Strength of Polymeric Films Fabricated via Different Production Processes

2019

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In this study, machine learning algorithms (MLA) were employed to predict and classify the tensile strength of polymeric films of different compositions as a function of processing conditions. Two film production techniques were investigated, namely compression molding and extrusion-blow molding. Multi-factor experiments were designed with corresponding parameters. A tensile test was conducted on samples and the tensile strength was recorded. Predictive and classification models from nine MLA were developed. Performance analysis demonstrated the superior predictive ability of the support vector machine (SVM) algorithm, in which a coefficient of determination and mean absolute percentage error of 96% and 4%, respectively were obtained for the extrusion-blow molded films. The classification performance of the MLA was also evaluated, with several algorithms exhibiting excellent performance.

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“…This condition results in severe polymer degradation and discoloration due to the production of hydrogen chloride. Stabilizers are added to prevent the elimination of hydrogen chloride from PVC and subsequent decomposition [20]. Several types of special polymers will furnish the necessary marginal compatibility with PVC to provide the shock-absorbing mechanism required to enhance the impact strength of the PVC product and also to function as impact modifiers.…”

Section: Introductionmentioning

confidence: 99%

Impact of PVC mixtures of the Electrical Conduit on the Physical Properties

Esmail¹

2020

Journal of Natural Sciences, Life and Applied Sciences

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The use of PVC mixtures in the manufacturing of electrical conduit has been employed for a long time along with other materials. In this study, the impact of changing the ratio of the components of the PVC mixtures on the physical properties of the electrical conduit was investigated. The emphasis was placed on three properties: Density, Tensile Strength and Soft Point. The application of the electrical conduit controls the types of materials and their percentages. Physical properties of the PVC products are the most important factors that help to choose compared with other materials. These properties change with the change of the chemical components of the PVC mixture. The study discussed how to enhance and improve these properties by controlling the proportions of some substances in the PVC mixtures. This article aims to demonstrate the strong relationship between PVC polymer, calcium and stabilizers and the physical properties of the electrical conduit. The focus concentrated on three components in the mixture and three physical properties. Random samples were taken to calculate the average percentages of the components in the mixtures. Various tools and several statistical methods were used such as correlation coefficients and scatter charts to prove the relationship between the ratios of the materials and the respective properties. The correlation coefficients between the PVC polymer, stabilizers, calcium, and the density, tensile strength, vicat soft points were (0.92, 0.83, 0.82) respectively. Decreasing the PVC polymer by (17.1%) has caused an increase in the density of the conduit by (2%). Finally, the physical properties of PVC mixtures could be improved by changing component ratios to reach the optimized mixture for the specific application, taking into account other competitive issues such as the final price of the product, environmental impact, and other issues.

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Designing and analyzing a mixture experiment to optimize the mixing proportions of polyvinyl chloride composites

Cited by 9 publications

References 19 publications

Vision-based Online Defect Detection of Polymeric Film via Structural Quality Metrics

Vision-based Online Defect Detection of Polymeric Film via Structural Quality Metrics

Machine Learning Models for Predicting and Classifying the Tensile Strength of Polymeric Films Fabricated via Different Production Processes

Impact of PVC mixtures of the Electrical Conduit on the Physical Properties

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