Multivariate random effects model for Integrated measurement of green veneer thickness and roughness

Thickness and surface roughness are the two main veneer quality criteria affecting material recovery, plywood glue bond quality, and glue consumption. At present, on-line green veneer thickness and surface roughness are generally not measured, which causes difficulty in assessing overall veneer quality for a better control of log conditioning and veneer peeling process. In this project, we will investigate the feasibility and operational conditions of a laser-based real-time approach in the pilot plant to jointly measure those two important quality criteria and subsequently develop a statistical model for accurately predicting such two dimensional measurements. A pilot plant test will be conducted at FPInnovations, followed by a production trial in an interior BC plywood mill. The pilot plant test is aimed to assess the operational conditions, gather samples for preliminary data analysis, and get correct sample size for the mill trial. The mill trial is aimed to collect real-time data on green veneer thickness and surface roughness in real production mode. Based on the data acquired, final phase of the project is to develop statistical models to predict overall veneer quality for a better process control. The models will be applicable to all other plywood mills in BC. The outcome of this project will allow each plywood mill to have annual savings of about $500,000.

Faculty Supervisor:

Dr. Lang Wu

Student:

Hongbin Zhang

Partner:

Tolko Industries Ltd.

Discipline:

Statistics / Actuarial sciences

Sector:

Forestry

University:

University of British Columbia