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    Author(s): Henry A. Huber; Charles W. McMillin; John P. McKinney
    Date: 1985
    Source: Forest Products Journal 35(11/12):79-82
    Publication Series: Miscellaneous Publication
    PDF: View PDF  (939 KB)

    Description

    To cut parts from boards, rough mill employees must be able to see defects, calculate the proper location of cuts, manually position the board, and remain alert. The objective of this study was to evaluate how well rough mill employees perform the task of recognizing, locating, and identifying surface defects independent of the calculation and positioning process. Using a scoring procedure developed for this study, it was found that six rough mill employees in three plants performed at about 68 percent of perfect. Thus, a computer vision system now under development need not be perfect to improve on current practice. The economic potential is considerable for such equipment if only a small yield improvement can be obtained.

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    Citation

    Huber, Henry A.; McMillin, Charles W.; McKinney, John P. 1985. Lumber defect detection abilities of furniture rough mill employees. Forest Products Journal 35(11/12):79-82

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