China has a relatively scarce forest resource, and the volume of stored forest resources is far from meeting the needs of current national construction. The contradiction between limited wood resources and an ever-increasing demand by the consumption market has forced the wood processing industry to develop towards intelligent manufacturing production mode.
Artificial intelligence technology has great potential in the wood processing industry. In the wood drying process, it is necessary to achieve precise testing and control of temperature, humidity, and wood moisture content in the drying kiln. After drying, non-destructive testing of the wood is also required through machine vision technology to determine the quality of the wood and locate any defects. During processing, intelligent algorithms can optimize and lay out the materials to save on labor and resources.
In recent years, Weinig GmbH has launched an optimized solid wood cutting production line at the LIGNA fair in Hannover, Germany, which includes automatic identification of solid wood plate size and defects, longitudinal optimal sectioning, transverse optimal trimming, and sawing, as well as automatic feeding and unloading operations. The entire process can be automated, and it is a successful case of combining artificial intelligence and automation.
It can be foreseen that the integration of artificial intelligence technology in the wood processing process will significantly improve the intelligence level and production efficiency of China's current wood processing industry, effectively promote the upgrading and transformation of the wood processing industry, and produce wood products that better meet market requirements with higher quality.
This article will elaborate on the current application status of artificial intelligence algorithms and theories in wood non-destructive testing and classification, wood drying, and wood optimal processing in recent years. By comparing the advantages and disadvantages of related algorithms and theories, it analyzes the deficiencies of current artificial intelligence technology in the wood processing industry and proposes future development directions to find breakthrough points for the application of artificial intelligence technology in the wood processing industry.
1. The Application of Artificial Intelligence Algorithms in Wood Non-Destructive Testing
Wood plays a very important role in various industries such as construction, decoration, and furniture in China. However, the requirements for wood mechanical properties, appearance (such as texture features, color features, and defects), bending, surface roughness, and other characteristics vary among different industries.
Therefore, wood must be tested and classified to meet the specific needs of different industries for wood features and to improve wood utilization. In traditional wood processing, wood inspection and classification mainly rely on manual visual observation, which is subjective, inefficient, and low in productivity, and cannot meet the demand for wood in national construction.
Currently, other non-destructive methods for wood testing have emerged, such as ultrasound, laser, and acoustic emission technologies, which gradually transition towards automatic testing and classification. In recent years, with the continuous development and breakthroughs of artificial intelligence technology, computer-assisted visual inspection technology has gradually been applied to wood non-destructive testing, which can significantly reduce the subjective influence of manual visual discrimination and improve the accuracy and efficiency of wood non-destructive testing.
Among them, the development of image recognition technology plays a crucial role in the application of computer-assisted visual inspection technology in wood non-destructive testing, which is often applied to wood texture recognition, defect detection, wood classification, and other work.
2. The Application of Artificial Intelligence Algorithms in Wood Drying
Wood drying is the process of removing moisture from wood under certain conditions, which directly affects the quality of wood products.
After drying, wood will not crack or warp for a long time, and its corrosion resistance and strength will also be greatly improved. The role of artificial intelligence methods in wood drying mainly lies in the accurate prediction of wood moisture content and the control of wood drying kiln temperature and humidity.
The commonly used intelligent algorithms include BP neural network, fuzzy algorithm, ant colony algorithm, and improvement on these algorithms, which can achieve their functions, but their accuracy is not high.
It is possible to consider combining artificial neural networks with fuzzy algorithms, genetic algorithms, expert systems, and other intelligent algorithms to complement each other's strengths and weaknesses or consider introducing deep learning and internet communication into wood drying to achieve higher prediction and control accuracy.
3. The Application of Artificial Intelligence Algorithms in Wood Optimal Processing
To overcome serious waste and low automation in traditional wood optimal processing, wood optimal processing programs and algorithms must be optimized during wood cutting and layout processes to effectively improve the economic benefits of enterprises during the process of wood cutting and layout and improve wood processing modes and reduce wood waste.
With the development of intelligent algorithms, using artificial intelligence algorithms for layout optimization is the main research direction of rectangular component layout problems, but there is relatively little research on layout optimization for wood, especially wood with defects, and the commonly used intelligent algorithms mainly include genetic algorithms.
Combining wood defect detection and wood cutting and layout optimization is an important measure to improve wood utilization. However, the powerful randomness of wood defects, such as their types and distributions, is one of the main difficulties in researching wood optimal processing algorithms.
Therefore, in the future, targeted measures should be taken to actively introduce artificial intelligence algorithms and improve the generalization ability and robustness of algorithms as much as possible when addressing wood-cutting and layout optimization problems.
4. Conclusion
In recent years, the development of artificial intelligence technology has made rapid progress. How to integrate artificial intelligence technology with the wood processing industry to achieve intelligent control and precise allocation of the wood processing industry, thereby improving production efficiency and capacity on the premise of sustainable development, is an important issue for the development of China's forestry.