The market for hardwood component production is currently affected by low-cost components importation from Asia. Industrial automation is an actual option for the secondary manufacturing industry to counter this situation. Integrating a defect detection system is a complex process and selecting the right system is even more complicated. This study proposes an approach for assessing the defect detection capabilities of different systems as well as a decision support tool to guide the producer toward the adequate equipment. The study is limited to assessing defect detection capacities; the overall system performance, the optimization software and the cutting equipment are not analyzed.
Understanding the origin and characteristics of defects to be detected and the capacities and theoretical limits of vision technology are prerequisites. A sampling with defects that, due to properties such as their small size, are hard to detect, is assessed by each system and the results are compared. To date, the assessed systems are not capable of detecting all defects pertaining to hardwood component production. A decision support tool will make it possible to methodically select the equipment most appropriate to the producer’s needs and leads to an enlightened decision in terms of the producer’s priorities and expectations.