Particleboard Surface-Roughness Classification System Modeling, Simulation, and Bench Testing

Abstract

Particleboard panels are widely utilized as a raw material in the wood processing industry. It ends up as furniture, cabinets, and other industrial products. One of the problems particleboard mills face concerns the surface quality of their boards. As the demands of customers become more precise, very thin overlays are becoming more popular. Thus the problem of surface quality control and classification is clearly identified. In this paper, a particleboard surface-roughness classification system is modeled, simulated, and implemented. The particleboard model is based on the characterization of surface anomalies (pinholes, sander streaks, and grooves). Furthermore, an optical stylus surface-roughness measurement system is also modeled in order to determine whether it can be used to characterize a particleboard “on-ine.” A classification algorithm is proposed to serve as an aid to the quality control operator. Simulation results are presented illustrating the change of surface roughness with increasing amounts of surface anomalies. A classification algorithm is used to sort the simulated panels into different classes. A trial bench test using 225 panels is made to determine the applicability of this system to the industrial context.