Use of computer simulation in managing manufacturing systems: an application of a sawmill-flow simulator template in lumber manufacturing.
The study compared two policies on mill-wane allowance, i.e. the current mill’s wane allowance and the maximum wane allowance allowed by the Western Wood Products Association (WWPA) stud-grade rules. Different levels of wane-allowance may have different impacts on lumber recovery, grade recovery, production, machine utilization, profit, and flow of lumber. Increasing the allowable proportion of wane on lumber should increase lumber recovery and production. However, increased proportions of wane on lumber lower its grade and thus its price. The question is, would this gain in recovery and production be large enough to offset lower prices for high-waned lumber? The sawmill-flow simulator template (SFST) was used to model the study mill and investigate the impact of changing the millwane policy. Employing the maximum wane allowance allowed by WWPA grade rules, lumber production increased from the current 393.55 m3 to 416.54 m3. Also, with more wane, the recovery rate and lumber recovery factor increased by 5.9% and 5.7%, respectively. However, regardless of the increases, it was found that there was no need to change the wane allowance, because with the current wane allowance the mill generated $2,364 more per shift than did with the maximum WWPA wane allowance. In addition, the model identified the debarker machine as a bottleneck in lumber production at the study mill. By increasing the debarker speed by 10%, and maintain the current wane allowance, an average of $4,279 per shift more profit and a more synchronised mill-flow could be achieved. Managers need timely and comprehensive information on which to base important decisions. Simulation provides a method to rapidly conduct experiments that predict results of alternative manufacturing decisions. In deciding which wane allowance to use, no raw materials, no machine times, no human resources, and no production time were utilized to reach the decision. That is the real power of simulation as a decision tool.
Keywords: Simulation-decision makingwane- grade rules-resources-utilization.
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