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Optimization of the sizing process with grey relational analysis

Treść / Zawartość
Identyfikatory
Warianty tytułu
PL
Optymalizacja procesu nanoszenia preparacji przy wykorzystaniu analizy zbiorów rozmytych
Języki publikacji
EN
Abstrakty
EN
The sizing process is an important one for textile mills and affects the efficiency of the loom machine. In this study, the optimization of multiple performance characteristics based on the grey relations analysis method, which is a new approach for optimization of the sizing process was researched using the Taguchi L18 (mixed 3 - 6 level) experimental plan. The process parameters selected: warp yarn count, the viscosity of the sizing solution and the dispatch speed of the warp yarn passing from the sizing machine, were optimized. In the experimental design of Taguchi L18 (mixed 3 - 6 level), the warp yarn count factor was chosen as 3 levels (12, 10 and 8 tex), the viscosity of the sizing solution factor as 3 levels (14, 20, & 24 Ns/m2), and the dispatch speed of the warp yarn passing from the sizing machine factor was selected as 6 levels (40, 50, 60, 70, 80, & 90 m/min). Quality characteristics were determined as the warp yarn strength, and the efficiency of the loom machine. A grey relational grade obtained from the grey relational analysis is used to solve the sizing process with multiple performance characteristics. Optimum levels for the sizing process parameters were determined using the grey relation grade.
PL
Proces nanoszenia preparacji jest ważny w procesie produkcji tkanin i wpływa na wydajność stosowanych krosien. Przeprowadzono optymalizacje szeregu parametrów procesu stosując metodę analizy zbiorów rozmytych będącą nowością w analizie procesu nanoszenia preparacji . Wykorzystano plan Tagucchi dla realizacji eksperymentu. Analizę przeprowadzono dla trzech przędz o różnych masach liniowych, trzech różnych lepkościach roztworu preparacji i trzech różnych prędkościach osnowy przechodzącej przez urządzenie do preparacji. Określono charakterystykę jakościową biorąc pod uwagę wytrzymałość osnowy i wydajność krosna. Optymalne wartości parametrów procesu preparacji określono przy zastosowaniu metody zbiorów rozmytych.
Rocznik
Strony
49--55
Opis fizyczny
Bibliogr. 22 poz., rys., tab.
Twórcy
autor
  • Department of Handicrafts, Gaziantep University, Gaziantep, Turkey
autor
  • Department of Textile Engineering, Cukurova University, Adana, Turkey
Bibliografia
  • 1. KuoY, Yang T, Huang GW. The use of a grey based taguchi method for optimizing multi response simulation problems. Engineering Optimization 2008; 40: 517-528.
  • 2. Lin JL, Lin CL. The use of the orthogonal array with grey relational analysis to optimize the electrical discharge machining process with multiple performance characteristics. International Journal of Machine Tools & Manufacture 2002; 42: 237–244.
  • 3. Tosun N. Determination of optimum parameters for multi-performance characteristics in drilling by using grey relational analysis. Int. J. Adv. Manuf. Technol. 2006; 28: 450–455.
  • 4. Kopac J, Krajnik P. Robust design of flank milling parameters based on grey-taguchi method. Journal of Materials Processing Technology 2007; 191: 400–403.
  • 5. Kuo CJ, Tu H. Gray relational analysis approach for the optimization of process setting in textile calendering. Textile Research Journal 2009; 79: 981-992.
  • 6. Eşme U, Bayramoğlu M, Aydın H. Optimization of galetaj process with Taguchi Method based on grey relational analysis 2 (in Turkish). In: Engineering and Technology Symposium, University of Çankaya, 2009; Ankara/Turkey, 205-217
  • 7. Su, TL, Chen, HW, Ma, CM, Lu, CF. Improving the quality of combed yarn spun by OE rotor spinning using the grey-taguchi method. Fibres & Textiles in Eastern Europe 2011; 19: 23-27.
  • 8. Yıldırım S. Product design improvement: Taguchi design (in Turkish). Master Thesis, University of Başkent/ Turkey, 2011.
  • 9. Tarng YS, Juang SC, Chang CH. The use of grey-based taguchi methods to determine submerged arc welding process parameters in hardfacing. The Journal of Materials Processing Technology 2002; 128: 1-6.
  • 10. Lu HS, Chang CK, Hwang NC, Chung CT. Grey relational analysis coupled with principal component analysis for optimization design of the cutting parameters in high-speed end milling. The Journal of Materials Processing Technology 2009; 209: 3808-3817.
  • 11. Liao HC. Multi-response optimization using weighted principal component. The International Journal of Advanced Manufacturing Technology 2006; 27: 720-725.
  • 12. Tong LI, Wang CH, Chen HC. Optimization of multiple responses using principial component analysis and technique for urder preference by similarity to ıdeal solution. The International Journal of Advanced Manufacturing Technology 2005; 27: 407-414.
  • 13. Fung CP, Kang PC. Multi-response optimization in friction properties of pbt composites using taguchi method and principle component analysis. Journal of Materials Processing Technology 2005; 170: 602-610.
  • 14. Sarpkaya Ç. The optimization of sizing process with grey relational analysis based on taguchi method (in Turkish). PhD Thesis, University of Çukurova/Turkey, 2014.
  • 15. Minitab User’s Guide2, Minitab Inc., 2000.
  • 16. Üstünışık NZ. The research of socio-economic development ranking of provinces and regions in Turkey: grey relational analysis method and its application (in Turkish). Master Thesis, University of Gazi Üniversitesi/Turkey, 2007.
  • 17. Wen KL. The grey system analysis and its application in gas breakdown and var compensator finding. International Journal of Computational Computing 2004; 2, 1: 21-44.
  • 18. Yılmaz E, Güngör F. Determination of the optimal sets of different hardness conservative gray relational analysis 2 (in Turkish). In: National Design and Analysis of Manufacturing Congress, Balıkesir/Turkey, 2010; 1-9.
  • 19. Mondal S, Paul CP, Kukreja LM, Bandyopadhyay A, Pal PK. Application of Taguchi-based gray relational analysis for evaluating the optimal laser cladding parameters for AISI1040 steel plane surface. Int. J. Adv. Manuf. Technol. 2013; 66: 91-96.
  • 20. Lin ZC, Ho CY. Analysis and application of grey relation and ANOVA in chemical- mechanical polishing process parameters. The International Journal of Advanced Manufacturing Technology 2003; 21: 10-14.
  • 21. Khan ZA, Siddiquee AN, Kamaruddin S. Optimization of in-feed centreless cylindrical grinding process parameters using grey relational analysis. Pertanika J. Sei. & Technol. 2012; 20, 2: 257- 268.
  • 22. Pawade RS, Joshi SS. Multi-objective optimization of surface roughness and cuttingforces in high-speed turning of Inconel 718 using Taguchi grey relational analysis (TGRA). The International Journal of Advanced Manufacturing Technology 2011; 56: 47-62.
Uwagi
Opracowanie ze środków MNiSW w ramach umowy 812/P-DUN/2016 na działalność upowszechniającą naukę.
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-891b4f71-d85d-4300-ac3e-c890cbf4823f
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