Novel Chart for Representation of Material Performance and Reliability

摘要

In modern industrial production lines various process and material parameters determine the properties of the final product. Thus, a process optimization procedure has to take into account a large design space containing several parameters. As a consequence, the evaluation of the influenceofsingleprocessparametersonthefinal product properties can be quite complicated. Usually a certain property of a product, for example the mechanical strength, has to satisfy a defined specification. In terms of quality control not only the performance of the material but also the reliability of the specified values has to be considered. The Weibull statistic gives an interesting approach to evaluate both, material's performance and reliability. Regarding the mechanical properties e.g. in terms of the stress at break s_b the Weibull analysis leads to a characteristic failure constant σ_(b,o) at which 63.2% of the samples will break. Additionally, the Weibull modulus m can be regarded as a measure for the width of the distribution of the measuring results. High values of m represent a narrow distribution and thus a better reliability. Moreover, the Weibull modulus m is independent of the absolute value of the measuring data. Therefore, it is possible to compare samples produced under different conditions. The standard deviation and the interquartile range are often used to quantify the scatter of empirical data. It is shown within this work that theWeibullmodulusmcan beamoreprecisediscriminatorfortheevaluation of the reliability because it is rather stable against outlaying values. As an example this study concentrates on themechanical properties of melt spun fibres consisting of blends from polypropylenes with different molar masses produced under various process conditions. This work presents a novel chart which allows one to compare different samples on the basis of theWeibull statistics whereat the Weibull modulus m is plotted over σ_(b,o). Defining a reference material, the m-σ_(b,o)-map can be split into quadrants, whereat each quadrant designates an improvement or worsening of material's performance and reliability with respect to the reference. An evaluation in terms of performance and reliability of great sets of data is easily applicable. It will be shown that the Weibull statistic can also be applied to Young's Modulus, the elongation at break and the tensile energy absorption.