Multivariate performance optimisation of scaffold boards with selected softwood defects

The uncertainties involved in the prediction of scaffold material performance in the machine grading process have brought forth the necessity to identify the level of influence of wood defects on the scaffold performance required to be optimised for its intended use as a construction material. This paper tackled this important aspect by employing multivariate optimisation and statistical analyses on the previously reported experimental results in the literature on the machine graded scaffold boards from UK Sitka spruce (picea sitchensis) softwoods. Initially, nonlinear multivariate regression analyses were performed for the responses of such variables as failure load, displacement, extreme fibre stress and the critical failure distance to several wood characteristics as contributing factors. The extension of the statistical analysis to the multi-objective optimisation study was accomplished using Response Surface Method (RSM) by considering the mutual interactions between the factors including total and margin knot area ratios, density, rate of growth and slope of grain. This paper represented graphically how the load bearing capacity, the deformation characteristics and the critical failure location points are influenced by the considered factors. The significance of factors and their relative influence on the performance optimisation were finally discussed by providing the essential information on the future use of scaffold board products as construction material. (C) 2019 Elsevier Ltd. All rights reserved.