A review on wood machining: characterization, optimization, and monitoring of the sawing process

Sawing is the most common machining process and is present in both primary and secondary wood transformation sectors. The objective of this paper is to review how it is affected by different factors. The current challenges associated with various machining factors, process monitoring, and sensor selection were identified and explained. Consequently, four research challenges and technological gaps were outlined. (1) Contradictory results have been reported due to different cutting processes, wood species, measurement methods, and cutting speed range studied in literature, so special consideration needs to be taken when comparing results with those available in the literature. (2) Laboratory test conditions cannot yet fully represent the extreme cutting conditions in sawmills. More emphasis should be placed on those harsh industrial cutting conditions. (3) Research on wood cutting lacks multi-objective optimization approach, which suggests that sawdust generation should be simultaneously analysed with surface quality and power consumption. (4) Compared with metal cutting, little research has been conducted on wood sawing monitoring using an artificial intelligence approach, which should be prioritized in designing adaptive control systems. Combining intelligent monitoring and multi-objective optimization approaches should pave the way for controlling the sawing process so higher surface quality and cost efficient machining is achieved.