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Title: Real-time value optimization of edging and trimming operations for rough, green hardwood lumber
Author: Schmoldt, Daniel L.; Song, Hang; Araman, Philip A.;
Source: Proceedings, ScanTech 2001, The Ninth International Conference on Scanning Technology and Process Optimization for the Wood Industry. 87-100.
Publication Series: Miscellaneous Publication
Description: For edging/trimming operations in hardwood sawmills, an operator examines both sides—or just the waney-edged side—of each board, and makes a quick assessment of grade potential. The operator then decides where to edge and/or trim the board to achieve the intended grade and, presumably, maximum value. However, human operators can only achieve lumber values that are 62-78% of optimal. To achieve higher performance rates, computer-aided processing is needed to search through the millions of possible edging/trimming options. Using a computer to solve the edging/trimming problem means that board data must be provided from a scanning system. We have developed a prototype scanning system for rough, green hardwood lumber that can automatically describe a board and its defects. Those data are then used in a branch-and-bound (B&B) search for an optimal edging/trimming solution. In comparing this B&B algorithm with known maximal solutions for a suite of boards, we found that the B&B method attains the correct maximal solution for 92% of the boards and achieves 99% of the total maximal lumber value. Ninety-four percent of the boards attained the maximal value in less than 10 seconds (233 MHz processor). For all boards for which the algorithm obtained a maximal value, it did so in less than 8 seconds. Currently available computers can easily reduce that search time to 1-2 seconds per board. In comparing the B&B algorithm to the edging/trimming option in UGRS (the only other software that performs edging/trimming), our method has better accuracy (1-2% higher value recovery, 5-11% higher correctness) and is 40-100 times faster. The high value recovery of the B&B algorithm essentially eliminates that source of error for an automated edging/trimming system. Performance is therefore only limited by scanning accuracy.
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Schmoldt, Daniel L.; Song, Hang; Araman, Philip A. 2001. Real-time value optimization of edging and trimming operations for rough, green hardwood lumber. Proceedings, ScanTech 2001, The Ninth International Conference on Scanning Technology and Process Optimization for the Wood Industry. 87-100.
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