The impact of cutting bill variability on product flow for a hardwood dimension mill as determined through discrete event simulation

Discrete event system simulation was used to study the correlation between cutting bill variability and dimension mill performance metrics. A discrete-event flow simulation model of a typical dimension mill with planing, ripping, chopping, and moulding operations under rip-first conditions was developed, and the flow of material through the system was studied. Representations of wood component requirements were generated through Monte Carlo simulation from random uniform distributions of twenty different component possibilities and served to fulfill randomly generated cutting bills, each consisting of five different orders, with a new order generated and added to the cutting bill as a current order was fulfilled. Statistical analysis of results obtained under various conditions of production and demand was conducted. Increased variability of cutting bills was found to significantly reduce order cycle times, reduce in-process inventories, and increase the total orders completed. The work establishes a theoretical foundation for the potential success of lean order scheduling techniques in the dimension mill, and demonstrates the positive contribution incurred from the integration of flow simulation and process simulation in order to address questions relative to the application and value of lean production versus yield maximization as practiced in the secondary wood products industry.