Wood Shrinkage Prediction Using NIR Spectroscopy

The ability to predict wood shrinkage could help manufacturers avoid lumber with abnormal dimensional stability or match pieces with similar properties in glued assemblies. Near infrared (NIR) spectroscopy is a rapid, nondestructive technique that has been used to predict various wood properties, including extractive content and density. Fifty-seven mahogany (Swietenia macrophylla) blocks were scanned using an NIR spectrometer, and were measured for specific gravity, extractives content, and total volumetric swelling. Models were created to predict the wood properties using the NIR data. These models could provide reasonable predictions of shrinkage, density, and extractives content. The use of nonlinear kernel and wavelet statistical techniques improved model performance. It may be possible to use NIR spectroscopy for the on-line sorting of wood according to dimensional stability

Monitoring multistage processes with autocorrelated observations

In multistage manufacturing processes, autocorrelations within stages over time are prevalent and the classical control charts are often ineffective in monitoring such processes. In this paper, we derive a linear state space model of an autocorrelated multistage process as a vector autoregressive process, and construct novel multivariate control charts, CBAM and Conditional-based MEWMA, for detecting the mean changes in a multistage process based on a projection scheme by incorporating in-control stage information. When in-control stages are unknown, finding in-control stages is a challenging issue due to the autocorrelations over time and the sequential correlations between stages. To overcome this difficulty, we propose a conditional-based selection that chooses stages with strong evidences of in-control stage using the cascading property of multistage processes. The information of selected stages is effectively utilised in obtaining powerful test statistics for detecting a mean change. The performance of the proposed charts is compared with other existing procedures under different scenarios. Both simulation studies and a real example show the effectiveness of the conditional-based charts in detecting a wide range of small mean shifts compared with the other existing control charts.Scopu