ISBIS4 Abstract

Contact Author's Name: Rudolf Beran
Title of Abstract: Statistical Modeling for Process Control in the Sawmill Industry
Author(s): Rudolf Beran
Affiliation: University of California, Davis
Statistical Modeling for Process Control in the Sawmill Industry

Rudolf Beran, University of California, Davis

In soft-wood sawmills in the western U.S., the green lumber end-product is the result of several distinct sawing operations: an initial breakdown of large diameter logs by a headrig yields boards that are subsequently resawn one or more times by secondary saws of various types. Vibration of the saws contributes to irregularities in thickness of the final green lumber. Misalignment of the saws produces green boards that are systematically wedge-shaped or tapered or otherwise deformed. The green lumber is dried, either naturally or in a kiln, and is then planed to standard dimensions for the market. The green lumber must be sawn thick enough to offset random and systematic irregularities in shape and to allow for shrinkage when it dries. Control of these factors reduces waste.

Shrinkage of green lumber is well-understood. Because systematic and random errors in thickness accumulate through a sequence of sawing operations, it has not been clear how to separate out the performance of secondary sawing machines. In a pilot study organized by the U.S. Forest Service, boards selected \"at random\" as they came off a headrig were followed through one of more resawings. Initially and at each subsequent stage of the processing, the thickness of each green board was measured at standardized points along each edge. This talk will:

a) Develop a physically-based statistical model for the accumulation of systematic and random errors in resawing operations;

b) Quantify on the study data how each resawing contributes to thickness errors in the green lumber end-product;

c) Point out implications for process control in sequential resawing operations.