Doctoral Dissertations

Date of Award

5-1994

Degree Type

Dissertation

Degree Name

Doctor of Philosophy

Major

Engineering Science

Major Professor

Ken Kirby

Committee Members

Richard Sanders, Jim Bontadelli, Hal Aikens

Abstract

This research has developed a new approach to predicting the amount of lumber required to produce a given cutting bill. The method is based on the stage-wise processing of a cutting bill and explicitly considers the impact part quantity has on lumber requirements. The new prediction method is less biased and contains less variability than the prediction method used in the traditional LP approach.

The new prediction method was incorporated into a new model for solving the lumber grade mix problem for a gang rip first layout. This model, referred to as RIP_RIGHT, closely approximates an actual gang rip first layout and allows many practical aspects of the problem to be incorporated into the solution. One such aspect is the differences in defect rates of down stream processes. The model allows these defect rates (sometimes called machine loss) to be specified by part size and lumber grade.

RIP_RIGHT was compared against the program RIP-X and proved to produce solutions as good or better than RIP-X.

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