[비의류제품] Predicting the Seam Strength of Notched Webbings for Parachute Assemblies Using the Taguchi's Design of Experiment and Artificial Neural Networks 출판일 : 2009.03.01 저자 : Levent Onal, Mithat Zeydan, Mahmut Korkmaz, Sheik Meeran 서지사항 : Textile Research Journal, Volume 79, Issue 5, 468 페이지 등록일 : 2011.05.20 I 조회수 : 218 작성자 : admin |
Webbings are used in parachute assemblies as reinforcing units for the strength they
provide. The strength of these seams is an important characteristic which has a substantial
influence on the mechanical property of the parachute assemblies. It is well established that
factors such as fabric width, folding length of joint, seam design and seam type will all have
an impact on seam strength. In this work, the effect of these factors on seam strength was
studied using both Taguchi's design of experiment (TDOE) as well as an artificial neural
network (ANN). In TDOE, two levels were chosen for the factors mentioned above. An L8
design was adopted and an orthogonal array was generated. The contribution of each
factor to seam strength was analyzed using analysis of variance (ANOVA) and signal to
noise ratio methods. From the analysis it was found that the fabric width, folding length of
joint and interaction between the folding length of joint and the seam design affected seam
strength significantly. Further, using TDOE, an optimal configuration of levels of factors was
found. In order to contrast and compare the results from TDOE, an ANN was also used to
predict seam strength using the above mentioned factors as inputs. The prediction from
TDOE and ANN methodologies were compared with physical seam strength. It was
established from these comparisons, in which the root mean square error was used as an
accuracy measure, that the predictions by ANN were better in accuracy than those
predicted by TDOE.
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