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Allan, Gordon; Yang, Ruodan; Fotheringham, Alexander; Mather, Robert Rhodes

doi:10.1023/a:1017913731041

Cited by 14 publications

(6 citation statements)

References 5 publications

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“…Moreover, the statistical approach provides a basis for optimization of the spinning process in the direction of either increased or decreased crystallographic order and/or overall orientation of as‐spun PP fibers. This, in turn, also provides a basis for quantitative modeling, such as neural network modeling 11…”

Section: Discussionmentioning

confidence: 99%

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The influence of fiber processing parameters on the structural properties of as‐spun polypropylene fibers: A factorial design approach

Yang

Mather

Fotheringham

2004

J of Applied Polymer Sci

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ABSTRACT:The structures of polypropylene fibers, spun according to a factorial experimental design, have been studied with the aid of wide angle X-ray diffraction and birefringence measurements. From statistical analysis of the results, the fibers have been characterized in terms of their crystallographic order and the overall orientation of their constituent polymer chains. These properties have been quantitatively assessed as responses to seven specially selected process control parameters in the extrusion equipment used to process the fibers. For both crystallographic order and overall orientation, the metering pump speed (MPS) at which the fibers are extruded and the speed (WS) at which the extruded fibers are wound exert significant effects. Moreover, the interaction, WS ϫ MPS, between these two control parameters also significantly influences orientation. For crystallographic order, two further significant parameters are the melt flow index (MFI) of the grade of polypropylene used and the temperature (ST) at which the polymer melt passes through the spinneret. The roles of these two factors in the development of crystallites within the fibers are discussed. No interaction effects, however, appear to be significant for crystallographic order. Models that specify the direction of change of the significant parameters for increasing or reducing both responses are given.

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Section: Discussionmentioning

confidence: 99%

“…To obtain this information reliably and with economy in the number of experimental trials, a statistical approach that integrates factorial experimental design and comprehensive statistical analysis is required 8, 9. The utility of this approach has already been illustrated,10 as has the application of neural networks to our research 11…”

Section: Introductionmentioning

confidence: 90%

The influence of fiber processing parameters on the structural properties of as‐spun polypropylene fibers: A factorial design approach

Yang

Mather

Fotheringham

2004

J of Applied Polymer Sci

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“…A better control and understanding of synthetic fiber processing are essential requirements for obtaining a desired range of mechanical and physical properties. In this regard, the statistical approach is well suited for the development of the synthetic fiber process technology; it efficiently leads to more reliable and accurate results in a small number of experiments …”

Section: Introductionmentioning

confidence: 99%

Use of D‐optimal design to model and the analysis of the effect of the draw ratio on some physical properties of hot multistage drawn nylon 6 fibers

Rahbar

Haji

2013

J of Applied Polymer Sci

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In this article, we present an experimental design methodology for studying the effect of the draw ratio on the physical properties of nylon 6 fibers on hot multistage drawing. A response surface methodology involving D-optimal design was used for the modeling and optimization. According to the analysis of variance results, the proposed models could be used to navigate the design space. We found that the responses of the tenacity and initial modulus were very sensitive to the factor of the second-stage draw ratio, and the shrinkage response was governed by the factor of the third-stage draw ratio. The results show a good agreement between the experimental and model predictions with high correlation coefficients. The operation conditions for obtaining the drawn yarn with the highest tenacity and initial modulus and low shrinkage are proposed.

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“…Other papers reporting the use of neural network modeling are concerned with the prediction of electronic properties of polymers, , as well as the prediction of heat capacities, tensile strength, tensile modulus, compressive strength, and elongation . Furthermore, neural networks have been employed in the optimization of polymer processing and in the inferential estimation of polymer quality during polymerization …”

Section: Data Miningmentioning

confidence: 99%

From Data to Knowledge: Chemical Data Management, Data Mining, and Modeling in Polymer Science

Adams

Schubert

2003

J. Comb. Chem.

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Untitled

Cited by 14 publications

References 5 publications

The influence of fiber processing parameters on the structural properties of as‐spun polypropylene fibers: A factorial design approach

The influence of fiber processing parameters on the structural properties of as‐spun polypropylene fibers: A factorial design approach

Use of D‐optimal design to model and the analysis of the effect of the draw ratio on some physical properties of hot multistage drawn nylon 6 fibers

From Data to Knowledge: Chemical Data Management, Data Mining, and Modeling in Polymer Science

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