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Implementation of a real-time statistical process control system in hardwood sawmillsAuthor(s): Timothy M. Young; Brian H. Bond; Jan Wiedenbeck
Source: Forest Products Journal. 57(9): 54-62.
Publication Series: Scientific Journal (JRNL)
Station: Northern Research Station
PDF: Download Publication (216.19 KB)
DescriptionVariation in sawmill processes reduces the financial benefit of converting fiber from a log into lumber. Lumber is intentionally oversized during manufacture to allow for sawing variation, shrinkage from drying, and final surfacing. This oversizing of lumber due to sawing variation requires higher operating targets and leads to suboptimal fiber recovery. For more than two decades, global businesses strategies have involved the use of statistical methods to reduce variation, improve quality, and lower costs as a means to ensure competitiveness. However, the use of statistical methods by the sawmill industry as a strategy to reduce process variation and improve competitiveness appears to be an exception rather than the norm. Only a few highly competitive sawmills are currently using statistical methods to maximize recovery, minimize costs, and improve product quality. Given the current and future economic pressures faced by this industry, sawmills of the future may need to consider the use of statistical methods to maximize fiber recovery. In our study, a real-time statistical process control system was developed and implemented for green lumber thickness measurement. The system used wireless measurement of lumber thickness displayed on control charts and histograms distributed real-time to all sawyers and management. Use of the system by four hardwood sawmills located in the United States resulted in significant cost savings. Target size reductions occurred at each sawmill and ranged from 0.030 inch to 0.120 inch for 4/4 green hardwood lumber. Lumber recovery increased at all sawmills, ranging from 0.2 percent to 1.6 percent per annum. Financial performance from use of the system improved for all sawmills with an average return on investment of 17:1.
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CitationYoung, Timothy M.; Bond, Brian H.; Wiedenbeck, Jan. 2007. Implementation of a real-time statistical process control system in hardwood sawmills. Forest Products Journal. 57(9): 54-62.
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