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Annual Review of Statistics and Its Application

Volume 5, 2018

Statistical Challenges in Assessing the Engineering Properties of Forest Products

Abstract

While the traditional approach to engineering materials aims to reduce their variability through a (generally energy-intensive) refining process, a more environmentally appropriate approach is to keep the product as natural as possible and quantify their variability, while reducing their variability only as necessary. This is the approach for sawn lumber and other solid wood products, made possible by the application of advanced statistical theory in the manufacturing, grading, and evaluation processes and in the engineering design models. This article reviews a number of statistical advances related to these objectives, and it ends with a view of a future characterized by engineered wood products and the use of high technology.

Keyword(s): duration of load, forest products, lumber strength, monitoring, survival analysis
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/content/journals/10.1146/annurev-statistics-041715-033633
2018-03-07
2025-04-22
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Statistical Challenges in Assessing the Engineering Properties of Forest Products
Annual Review of Statistics and Its Application 5, 237 (2018); https://doi.org/10.1146/annurev-statistics-041715-033633
/content/journals/10.1146/annurev-statistics-041715-033633
/content/journals/10.1146/annurev-statistics-041715-033633
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Supplementary Data

  • Supplemental Video 1: A video of a test conducted with a bending machine that measures the modulus of rupture. The growth characteristic likely to reduce the specimen strength is randomly located in the span. By preventing upward movement of the ends, the specimen bends or flexes in response to the upward movement of two jacking points positioned symmetrically near mid-length. The amount of bending is increased at a uniform rate, which causes the specimen to push back with higher and higher force until it fails. All aspects of the test are controlled and recorded continuously and automatically.

  • Article Type: Review Article

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