Since the success of production processes in the textile industry depends on good planning and having a clear programme from the raw materials until the final product, the focus of this research is in the modelling of the production process of biodegradable aliphatic-aromatic co-polyester (AAC) fibres. The statistical modelling of the effects of the extrusion temperature profile and polymer grade on the properties of linear AAC as-spun fibres aims to find the better linear grade to be used. The investigation helped to establish a statistical method to optimize the extrusion temperature profile required for extrusion of AAC fibres. The effects of melt spinning conditions together with linear and branched grades of AACs on as-spun fibres were statistically modelled, programmed and evaluated. To identify the effect of the drawing process, the effect of multi stage hot and cold drawing process on AACs fibres has been statistically investigated and modelled. The additional effect gained from twisting the drawn fibres has been investigated in terms of process parameters interactions. Forecasting models have been set for optimizing and controlling the manufacturing of biodegradable AACs fibres. The novel statistical factorial method will help when taking the best experimental decision controlled by the design factors
