MATHEMATICAL PROGRAMMING ANALYSIS OF COMPONENT VENEER CONTRIBUTION TO INCOME IN PLYWOOD PRODUCTION

This thesis presents a new approach to solving plywood production planning problems. The traditional approach to the solution of these problems has been based upon a linear programming model in which the aim of the objective is to maximize the "unit plywood" contribution to income on profit, subject to a set of production and market constraints. This kind of analysis ignores the diverse values of the plywood components, such as various grades of veneers.;Two different approaches for the "veneer contribution" to income analysis were studied. The first approach solved the veneer-to-plywood problem. The second solved the log-to-plywood problem. These approaches permit the determination of optimum veneer grades and thicknesses in exact proportion required for the production of desired types of plywood panels. The results of the "veneer contribution" to income analysis identified not only the optimum quantities of veneers for the manufacture of requisite plywood, but because of a more refined solution the results also indicated to which types of panels each grade and thickness of veneer should be allocated to optimize the return from the manufacturing operation.;Two traditional approaches to the solution of veneer-to-plywood and log-to-plywood production planning problems were also solved for the same set of production resources and market constraints.;On the whole, the results of this study indicate that the values of the objective function achieved for the "veneer contribution" to income analysis improved significantly over the "plywood contribution" to income analysis by traditional approaches.;In this study, the proposed approach took the diverse values of plywood components into fundamental consideration. The income contributions by the veneers for all types of projected plywood were determined and used as coefficients in the objective function of the proposed linear programming model, subject to a set of production and market requirement constraints.