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)