The computer-based bootstrap method as a tool to select a relevant surface roughness parameter

The aim of this paper is to present how to make the most of the recent and powerful statistical computer-based bootstrap method (CBBM) in roughness studies. This work shows that this statistical method can help to determine quantitatively, and without preconception, the most relevant roughness parameter that characterises the surface morphology of a manufactured product as far as a correlation with a particular function, property or application is concerned. The efficiency of this statistical method is illustrated in this paper describing the relationships between the brightness level and the surface roughness of cold-rolled low carbon steel strips; the relevance of 100 or so roughness parameters was studied via a computer software we have been upgrading for a few years.