Paper to the Polymer Processing Society Annual Meeting, Yokohama, Japan, 8th-12th June 1998, paper 10-04.

S F Bush with C G A Clayton and S Baillie Strong

Introduction

Earlier papers (1991, (1995a, (1995b) have described factory control systems based on relating the appearance of woven or knitted assemblies of textured, dyed or pigmented polyester or nylon fibres to variables in the spinning and texturising processes. As part of this programme quantitative relationships between changes in the appearance of woven or knitted dyed fabric and changes in process variables such as windup speeds, fibre cooling rates, and polymer intrinsic viscosity have been inferred from large quantities of factory data. The appearance of carpet or fabric made up of prepigmented filaments is generally less sensitive to process variation than is fabric made from dyed fibre. However, the quality of both classes of product are very dependent on minimising variations in polymer morphology, the effects of which are often only apparent in the hands of customers.

Because dyestuffs tend to accumulate in the less ordered regions of the polyester fibre, and the rate of diffusion differs markedly in the crystalline and amorphous regions, dye uptake within a given time may be taken as a sensitive indication of morphological development. Moreover different dye molecules respond differently to different morphologies and therefore provide an additional and sensitive way of validating the models. The present paper outlines the basis of a model which has been used to predict morphological development at spinning, drawing and texturing, and combinations of these processes.

References

[1] S F Bush and C G A Clayton: “Analysis and Control of Variability in the Fibre-Making Process”, 7th Ann Mtg Poly Proc Soc, Hamilton, Canada, April 11-14 (1991)

[2] S F Bush and C G A Clayton: “Intelligent Manufacture of Polyester Fibres on the Full Scale”, 11th Ann Mtg Poly Proc Soc, Seoul, Korea, 27-30 March (1995)

[3] S F Bush: “Characterization of Pigment Distribution in Extrusion of Synthetic Fibres”, Poly Proc Soc Euro Mtg, Stuttgart, Germany, 26-28 Sept (1995) KN1-01

See also the section on Systems Design & Control.

Paper to the 11th Annual Meeting of the Polymer Processing Society, Seoul, Korea, paper 6-02, 27th-30th March 1995.

S F Bush with C G A Clayton

Abstract

Synthetic fibre production is characterized by the fact that while control is actually exerted in the factories, in many cases we can only know if the quality required by the market has been achieved some weeks later or even longer, after several additional operations such as knitting and dyeing have been performed by customers. In some cases, the operation of polymerization, spin-drawing, draw-texturing and weaving or knitting, and dyeing are all performed by separate manufacturers.

While defects may show up at any of these stages, the most difficult defects to counter are those which show up after dyeing, since the appearance of fabrics depends on quite subtle variations in the yarn polymer morphology and on the bulking geometry. Any of the preceding stages can contribute to observed variations in appearance. The problem of multiple stages is compounded by the requirement at fabric assembly to be able to use bobbins made at different times and from a sequence of different positions at each of the preceding stages.

In an earlier paper (Ref 1) the authors described the principles of a Process Analysis-Monitoring System (PAMS) which uses the principles of variance analysis extended on a huge scale to rank and locate the sources of non-uniformity in the factories and on the machines. The present paper builds on this by developing mechanistic relationships between the primary determinants of appearance (bulking, dye uptake and/or pigment dispersion) and the principal process variables such as plate temperatures, windup speeds, bulking speeds, through the relationships of both classes of variables to the fibre morphology.

Broadly speaking the PAMS variance analysis will indicate where in the various manufacturing stages, the sources of variability are likely to be. Combining the models of fibre behaviour with the PAMS allows this fuzzy diagnosis to be made more precise and in some cases determines the precise variable and its position causing a given type of variability. By this means an intelligent process system has been built up which is capable of steady refinement in the light of plant results.

References

[1] S F Bush and C G A Clayton, Analysis and Control of Variability in the Fibre-making Process, 7th Ann Mtg Poly Proc Soc, Hamilton, Ontario, Canada, 11-14 April (1991)