A model for increasing yield in sawmills based on detection of subsurface defects in canted logs using Ground Penetrating Radar (GPR) system

Detecting subsurface defects by scanning canted logs and generating a process plan based on the detection process to cut the log can increase the yield of high grade lumber in a saw mill industry. The defect detection process is performed using the Ground Penetrating Radar (GPR) system. Past research has used the GPR system to scan logs and process the data using RADAN(TM) software. More recently, a defect detection algorithm was developed to process scanned data using the MATLABRTM software. This research uses the distance and depth coordinates generated by the defect detection algorithm to develop the process plan that generates a cutting sequence for the resaw machine. The process plan is in the form of an algorithm written in MATLABRTM with a simple user interface, keeping the resaw machine operator in mind.; For this research, a few sawmills were visited to study the manufacturing process and the primary focus was on the resaw machine operation and the lumber grading system. The resaw machine is used to make boards or lumber from canted log. Since a canted log has a smooth square cross section, this makes it suitable for the scanning process. The generated process plan is a series of numbers in a sequence (cutting sequence) that correspond to the face number of the canted log. The generated cutting sequence was validated by comparing to the conventional sawing sequence, where the operator of the resaw machine randomly performs the cutting of boards. A thirteen percent increase in the yield was noticed.