Further Insights into the Fatigue of Hair Fibres through Statistical Analysis and Relevance to Hair Care Applications
Résumé
The study of fatigue is a well-established discipline within the field of material science.Understanding the fatigue of materials when subjected to repeated load cycles provides insightful knowledge about fracture and failure mechanisms. Such information has become essential in the development and manufacture of products ranging from aeroplanes to car tyres. The fatigue behaviour of fibres is well studied,encompassing both textile and technical fibres.The merit of fatigue testing has been recognised within the cosmetics industry and in recent years there has been an increasingusageof cyclic fatigue testing within the hair care sector.During daily grooming practises and routines,hair fibres on the head are exposed to repeated stresses which contribute to fibre fatigue. Although the applied stresses are much lower than what is required to break the hairin a single application, over time, this leads to an accumulation of stress and eventual failure of the fibre.To study this, a repeated stress or strain can be applied to singlehairfibres until they break. Use of Dia-Stron CYC802 modulesin conjunction with anautomated platform allows for high-throughput cyclic fatigue testing of hair fibres. The aim of many cyclic fatigue studies is to make comparisons between different types of damage or to assess the performance of treatments. The number of cycles to break for each test groupcan be fitted usingeither a Kaplan Meier Estimatora 2-parameter Weibull distribution.In order to ascertain a confidence for the estimatedWeibullparameters, it is imperativeto calculate the confidence intervals[1, 2]. This can be achieved by applying a Bootstrap method to generate confidence boundsfor the experimental data[3].Also, based on the distribution obtained for the Weibull parameters, statistical comparisons between groups can be conducted using parametric or non-parametric methodssuch as Kolmogorov Smirnov tests[4]. These statistical analysis techniques,will be illustrated with examples relevant to the hair care applications.References[1]F. Islam, S. Joannès, S.Bucknell, Y. Leray, A. Bunsell and L. Laiarinandrasana.Investigation of tensile strength and dimensional variation of T700 carbon fibres using an improved experimentalsetup, Journal of Reinforced Plastics and Composites.[2]F. Islam, S. Joannès, and L. Laiarinandrasana.Evaluation of critical parameters in tensile strength measurement of single fibres, Journal of Composites Science, 3 (3), 69.[3]F. Islam, S. Joannès , S. Bucknell, Y. Leray, A. BunsellandL. Laiarinandrasana.Towards accurate and efficient single fibre characterization to better assess failure strength distribution. ECCM 18 -18th European conference on composite materials, Jun 2018, Athenes, Greece. 7 p. (hal-01958211).[4]F. Islam, S. Bucknell, Y. Leray, A. Bunsell, L. LaiarinandrasanaandS. Joannès. Improvements in determination of carbon fibre strength distribution using automation and statistical data analysis. Fiber Society's Spring Conference 2018, Jun 2018, Tokyo, Japan. 3 p. (hal-01959309).