Optimising the fibre-to-yarn production process: finding a blend of fibre qualities to create an optimal price/quality yarn

• Autorzy: Sette S. , Van Langenhove L.
• Języki publikacji: EN

Abstrakty

EN

An important aspect of the fibre-to-yarn production process is the quality and price of the resulting yarn. The yarn should have optimal product characteristics, while maintaining as low a price as possible. Early optimisation models of the fibre-to -yarn process, based on neural networks and genetic algorithms, were severely limited in their potential applications as they generated unrealistic (ideal) conditions for the process. In this paper, a method is presented to model and optimise the fibre-to-yarn production process which avoids the aforementioned problems. A neural network is used to model the process, with the machine settings and fibre quality parameters as input and yarn tenacity and elongation as output. A constrained optimisation algorithm is used afterwards to optimise the blend of fibre qualities to obtain the best yarns. This result s in an optimal price-yarn quality surface where each point corresponds with a set of blend coefficient s and machine settings. Furthermore, constraints can easily be adjusted to correspond to real-life production environments.

Słowa kluczowe

EN

quality yarn; price yarn; production process

PL

jakość przędzy; cena przędzy; proces produkcji

• Wydawca: Lodz University of Technology, Faculty of Material Technologies and Textile Design
• Czasopismo: Autex Research Journal
• Rocznik: 2002
• Tom: Vol. 2, no. 2
• Strony: 57--63
• Opis fizyczny: Bibliogr. 4 poz.

Twórcy

autor

Sette S.

• Department of Textiles, Universiteit Gent Technologiepark 9, 9052 Zwijnaarde, Belgium

autor

Van Langenhove L.

• Department of Textiles, Universiteit Gent Technologiepark 9, 9052 Zwijnaarde, Belgium

Bibliografia

• [1] Sette S, van Langenhove L., Boullart L.; ‘Optimisation of the Fibre-to-Yarn process using Genetic Algorithms’; 23rd International Cotton Conference Bremen: Optimisation Production Process; Germany, March 6-9, (1996), pp 233-246
• [2] Sette S, Boullart L, van Langenhove L, Kiekens P; ‘Optimising the fibre-to-yarn process with a combined Neural Networks/Genetic Algorithm approach’; Textile Research Journal, Vol. 67, No. 2, (1997), pp 84-93
• [3] Garde A R, Subramanian T A; ‘Process Control in Cotton Spinning’; ATIRA, Ahmedabad, India, (1974), pp 23-34
• [4] Fletcher R; Practical Methods of Optimization; Vol 2, Constrained optimization, John Wiley and Sons, (1980)