Intelligent Lumber Production (Sawmill 4.0): Opportunities, Challenges, and Pathways to Adoption

In transiting from automated to smart lumber manufacturing, the sawmilling industry should adopt cutting-edge technologies for efficient and cost-effective lumber production. This manuscript reviews the opportunities and challenges the sawmilling industry is facing to embrace a smart, data-driven manufacturing approach. Accordingly, the main steps in lumber manufacturing are introduced, and opportunities to practice smart production in sawmills, kilns, and planer mills are explained. Sawmills benefit from sensing and machine vision technology combined with artificial intelligence (AI) for efficient log breakdown, process health and equipment condition monitoring, and smart edging/trimming. The kiln drying process benefits from moisture pre- and post-sorting, in which nondestructive evaluation (NDE) of lumber moisture content is crucial. Smart lumber grading can be practiced using NDE-based techniques combined with AI. Despite the unprecedented opportunities, the lumber industry struggles to leverage big data analytics value and power. The advancement in the Internet of Things (IoT), cyber-physical systems, and cloud computing should highlight the importance of digital twins in sawmilling. AI and big data analytics will be used in the future, not just for smart quality control, processing monitoring, and optimization but for smart design and planning, material distribution and tracking, customization and flexible manufacturing, and market analysis and positioning.