Filling a rough-mill cutting order using a fuzzy logic controller Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/n296x1967

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  • Because of their high cost, reducing the number of boards used to fill an order of dimension parts is an important goal in a lumber rough mill. FLCO (Fuzzy Logic Cutting Order) is a computer program that achieves this goal. Using the concepts of fuzzy logic control, FLCO provides a heuristic approach to this problem. FLCO incorporates a version of the CORY lumber cut-up software, and provides a model of a rough-mill system that is able to reduce the number of boards needed to fill a cutting order. FLCO allows different control methods to be used, including fuzzy logic control, dropping sizes from the cutting order as their demands are met, and no control. Because of the modularity of its design the FLCO code can easily incorporate other control methods. CORY lumber cut-up software provides sawing solutions for boards based on the values assigned to the sizes in a cutting order. After each board is sawn, the fuzzy logic controller adjusts the value of each size to achieve the objective of filling the demand for each size in a cutting order at about the same time. These new values are subsequently used by CORY when finding a sawing solution for the next board to be processed. Upon completion, FLCO reports the number of boards required to fill the cutting order, the average percent area yield, and the number of each piece recovered. Three cutting orders, three lumber grades and two types of control provide a means of determining the effects of fuzzy logic control on reducing the number of boards used to fill a cutting order. Across all lumber grades and cutting orders, fuzzy logic control greatly reduces the number of boards as compared with dropping sizes. Fuzzy logic control slightly reduces the number of boards as compared with a more complicated method of control across all lumber grades and most cutting orders, but the difference is not statistically significant. In addition, the effect of fuzzy logic control on individual sizes is also examined.
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