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

[+] Author and Article Information
P. Radziszewski, B. Picard

Department of Mechanical Engineering, McGill University, 817 Sherbrooke Street West, Montréal, PQ H3A 2K6, Canada

A.-M. Bourret

BRCDT,  École Polytechnique, C.P. 6079, Succ. Centre-ville Montréal, PQ H3C 3A7, Canada

J.-P. Brunet

 Bioptic Vision, Inc., 1927 3 av, Val d’Or, Québec, PQ J9P 4N7, Canada

M. Tétreault

Département de Génie de la Production Automatisée,  École de Technologie Supérieure, 1100 rue Notre-Dame Ouest, Montréal, PQ H3C 1K3, Canada

K. Zaras

Département des Sciences Administratives,  Université du Québec en Abitibi-Témiscamingue, 445, Boulevard de l’Université, Rouyn-Noranda, PQ J9X 5E4, Canada

M. Cheriet

Département de Génie de la Production Automatisée, École de Technologie Supérieure, 1100 rue Notre-Dame Oust, Montréal, PQ H3C 1K3, Canada

J. Ouellet

Department of Mining, Metals and Materials,  McGill University, 3450 University Street, Montréal, PQ H3A 2A7, Canada

J. Manuf. Sci. Eng 127(3), 677-686 (Aug 01, 2004) (10 pages) doi:10.1115/1.1954795 History: Received December 02, 2003; Revised August 01, 2004

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.

Copyright © 2005 by American Society of Mechanical Engineers
Your Session has timed out. Please sign back in to continue.



Grahic Jump Location
Figure 1

Particleboard process

Grahic Jump Location
Figure 2

Industrial-quality sample

Grahic Jump Location
Figure 5

Sander streak sample

Grahic Jump Location
Figure 6

Particleboard surface roughness simulator

Grahic Jump Location
Figure 7

Particleboard with surface anomalies

Grahic Jump Location
Figure 8

Receiver’s trajectory (x,y:ft)

Grahic Jump Location
Figure 9

Straight-line receiver’s trajectory

Grahic Jump Location
Figure 10

Variation of d and df

Grahic Jump Location
Figure 11

Average roughness index for panels with pinholes

Grahic Jump Location
Figure 12

Average roughness index for panels with grooves and sander streaks

Grahic Jump Location
Figure 13

Location of the laser stylus system in the particleboard production process




Some tools below are only available to our subscribers or users with an online account.

Related Content

Customize your page view by dragging and repositioning the boxes below.

Related Journal Articles
Related eBook Content
Topic Collections

Sorry! You do not have access to this content. For assistance or to subscribe, please contact us:

  • TELEPHONE: 1-800-843-2763 (Toll-free in the USA)
  • EMAIL: asmedigitalcollection@asme.org
Sign In