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Measuring Nylon Carpet Yarn Heat History by Remote NIR Spectroscopy

Part I: Development of Laboratory Remote Fiber-Optic Measurements

Solutia, Inc., Gonzalez, Florida 32560, U.S.A.

Subhas Ghosh

Institute of Textile Technology, Charlottesville, Virginia 22902, U.S.A.

Heat setting of nylon carpet yarns is one of the most critical processes in carpet manufacturing. The temperature at which the yarn is heat set—the heat-set temperature (HST)—is one of the most important operational variables in the process. Previous investigations with laboratory, bench-top, near infrared (NIR) reflectance instrumentation had shown NIR to be a simple, rapid, and accurate laboratory technique for measuring the HST of nylon carpet yams. The potential of NIR for measuring the HST/heat history of nylon carpet yarns directly on the carpet yarn bobbin and in the manufacturing area is evaluated in a two-phase program. In this paper, Phase One—the evaluation of remote fiber optic sampling systems and the development of a laboratory measurement of HST/heat history directly on the bobbin—is presented and discussed. Nylon 66 yams are heat set by both the Suessen and Superba methods over wide HST ranges. NIR calibrations for HST are developed and validated with two remote fiber optic sampling systems—an interactance probe ("Probe") and a remote reflectance head ("Head"). Excellent agreement is obtained between the stated Suessen and Superba HSTs and the NIR results for both fiber optic sampling systems, with high R² values (normally >0.9) and low residuals (standard deviation of differences, SDD) of normally <3° for both systems on both heat-set methods. The Probe sampling system is the best overall system for at-line measurements, with low sampling system weight, simpler operation, faster analysis time, and increased flexibility. The Head sampling system is the best overall system for on-line measurements, where its superior accuracy can be optimized.

Textile Research Journal, Vol. 70, No. 6, 519-524 (2000)
DOI: 10.1177/004051750007000608


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