The annual demand for fibres continues to rise worldwide. Consequently, more and more fibres must be produced to meet this demand, most of which are melt-spun polymeric man-made fibres. Smooth filaments made of polymers are mainly used for technical applications in industry. For use in clothing or home textiles, for example, a texturing process is used to give the filaments a crimp and thus a feel like that of natural fibres. In this state, they can be processed together with natural fibres and used in textiles. Partially oriented yarns (POY) are of great importance in texturing. The yarns are mainly crimped with the help of the so-called false-twist texturing process (FTTP). Since POY accounts for about 60% of the melt-spun filament yarn produced worldwide, the FTTP is the most important texturing process in the textile industry. In this paper, the main components of false-twist texturing (FTT) machines are explained, along with the state of the art and research for each component and its influence on the process. Relevant patents are discussed, as well as process optimisation techniques, innovative polymers, and yarn types recently used in FTT, followed by a conclusion and an outlook for the process.

The annual demand for fibres continues to rise worldwide. Consequently, more and more fibres must be produced to meet this demand, most of which are melt-spun polymeric man-made fibres. [1] Smooth filaments made of polymers are mainly used for technical applications in industry. For use in clothing or home textiles, for example, a texturing process is used to give the filaments a crimp and thus a feel like that of natural fibres. In this state, they can be processed together with natural fibres and used in textiles. Partially oriented yarns (POY) are of great importance in tex-turing. The yarns are mainly crimped with the help of the so-called false-twist texturing process (FTTP). [2] Since POY accounts for about 60 % of the melt-spun filament yarn produced world-wide, the FTTP is the most important texturing process in the textile industry [3]. In this paper, the main components of false-twist texturing (FTT) machines are explained along with the state of the art and research for each component and its influence on the process. Relevant patents are dis-cussed as well as process optimisation techniques, innovative polymers and yarn types recently used in FTT, followed by a conclusion and an outlook for the process.

Melt-spun man-made fibres are crucial for the ever-rising demand for fibres. To use them in clothing or home textiles, they need the feel and properties of natural fibres, often imparted through texturing processes. The most dominant process, with 30 Mio. t production capacity per year, uses false-twist texturing to transform smooth melt-spun partially oriented yarns (POY) into crimped, fluffy draw-textured yarns (DTY). However, the heaters used in the process are long and inefficient, thereby compromising production efficiency. Short, efficient microwave heaters are proposed to overcome these drawbacks, reducing energy consumption by 40 % and increasing productivity by 20 %, leading to significant cost savings and equivalent CO2 reductions during DTY production. However, conventional microwaves do not reach peak electric field strengths needed to heat the yarns in such a short residence time. Therefore, an optimisation algorithm is developed that couples a Genetic Algorithm and a high-frequency simulation to identify unconventional microwave resonator geometries with high electric field strengths along the yarn path of polymeric multifilament yarns. First results show that peak values of up to 0.63 MV/m can be achieved along the yarn path with an excitation power of only 100 W. This lies below estimated necessary values of 1 MV/m. However, the fitness value used in this work is very local and the algorithm will be optimised to achieve higher values and account for heating along the complete yarn path. Future work will quantify energy efficiency and validate on a pilot scale along with a novel yarn temperature sensor.