Today, the introduction of AI into various fields is no surprise. People have almost overcome the initial fear, and they talk less and less about neural networks being harmful. Now, AI is seen as a useful tool and the timber industry is no exception. AI is already actively helping people there and helping timber companies grow.
Tree Growing Stage
This stage is not directly related to the timber industry but is indispensable. Before the tree reaches the Timber Supplier, it must grow to the required size. It is also important to maintain a balance to avoid over-cutting.
Of course, new trees are constantly growing and it’s important to take into account that their number is not less than those cut down during the year.
Thus, man is faced with a serious problem at the intersection of ecology, economics, and industry. It’s here that AI comes to the rescue. Neural networks analyze a huge amount of data and provide answers regarding the scale of logging and planting new trees.
Moreover, AI calculates optimal routes, helping with logistics. Thus, timber arrives at enterprises as quickly and cheaply as possible.
Of course, not all companies have implemented such technologies yet and many companies still calculate everything manually the old-fashioned way, which is much less efficient. In addition, when using manual calculations, the possibility of error cannot be ruled out.
Wood Processing
Wood is a valuable resource that is the basis of forest industry enterprises’ business. The cost of production and competitiveness of wood processing products depend on their quantitative and qualitative characteristics.
Quality Assessment
Ensuring an accurate and transparent process of measuring wood is one of the most important tasks for the entire timber industry.
The most common way to measure the dense volume of wood along the entire chain of its movement “from the plot to the mill” is the group (geometric) method. Experts determine the grade of logs, often selectively.
This approach is an industry-standard and is generally recognized, but it can lead to errors and risks. Inaccurate measurements, an incorrectly selected coefficient of wood density, errors in calculations, and even fatigue of expert personnel at the end of the work shift can all lead to an incorrect determination of the volume and grade of wood.
For AI measurement of wood parameters, photographing the logs in the timber truck is enough. Within seconds, AI algorithms identify each log, determine its diameter, cut area, and grade, and calculate the dense stack volume without using the full-wood coefficient.
Processing
In many enterprises, people still manually control processing and sawing.
More often than not this equipment is able to be programmed, which has helped significantly improve product results and quality at the end of the last century. However, the new era brings with it its own new requirements.
Thanks to computer vision and AI, cutting as accurately as possible with a minimal amount of waste becomes possible. Such programs are already in place at certain timber enterprises, and the results of their work are amazing.
They analyze the log, create an optimal sawing pattern, and then evaluate the quality of the boards. Thus, sorting is done immediately. This process significantly saves time and resources and provides a higher quality of production.
Storage and Transportation
Finished products need to be stored in a warehouse and then transported to customers. In these matters, AI provides invaluable assistance.
For example, programs with AI elements are already being actively implemented in warehouses to optimize storage. First, the neural network distributes stocks according to established criteria.
Then, using sensors, it monitors storage conditions. Such a system will immediately notify if humidity has increased unacceptably or other conditions do not meet required standards.
Logistics can also not be done without a computer assistant. It can perfectly plan routes and vehicle fleet workload.
The program also tracks transport movements and controls conditions using highly sensitive sensors. At the same time, the influence of the human factor and disruption of orders due to overlaps are excluded.
Future of AI in Timber Industry
The future of AI in the timber industry holds significant promise, with technological advancements enabling companies to optimize processes, improve sustainability, and enhance productivity.
AI is already making an impact in the monitoring and management of forests, with machine learning algorithms and drone technology being employed to collect and analyze large datasets on forest health, tree growth patterns, and biodiversity.
Looking ahead, AI will likely drive even greater innovation in the timber industry. In the future, predictive analytics and AI-driven supply chain management systems could help timber companies optimize inventory levels, forecast demand, and reduce operational inefficiencies.
Additionally, advancements in AI for wood grading and sorting will continue to enhance product consistency, ensuring that timber meets the specific needs of construction, furniture, and other industries.
The scope of application of neural networks in the timber industry is extensive. AI is already involved in the stage of planting new trees and planning felling.
The entire path of the log from the felling site to the end consumer can be much more straightforward, thanks to artificial intelligence.
Today, many companies are already implementing such technologies to assess the quality of wood and its optimal processing and are discovering that AI is a great tool to improve the quality of their final product and reduce their environmental impact.