AI quality control solutions for wood manufacturing

What is AI quality control in wood?

AI quality control in wood manufacturing is the use of advanced tech like computer vision, machine learning, and Industrial Internet of Things (IIoT) sensors to keep control of quality throughout the wood production process.

In industries such as forestry, sawmilling, timber processing, furniture, and paper manufacturing, consistent quality is critical.

Wood is a natural and variable material, prone to defects such as knots, cracks, splits, warping, fibre misalignment, and uneven moisture levels. These issues can reduce product strength, compromise aesthetics, and create downstream waste.

AI-based systems automate this process by using sensors and cameras to collect data and algorithms to detect defects or anomalies in real time.

What are the examples of using AI for quality control in wood?

AI quality control systems are increasingly being adopted across the wood and forestry value chain. Below are selected examples demonstrating how these technologies can be applied to automate quality inspections with AI.

Furniture Manufacturing Quality Control

A furniture manufacturer, Prohan, built an AI vision system to monitor the quality of glued wood panels during peak production periods. The company needed to maintain consistent standards despite increased production volume and limited manual inspection capacity. Trained on historical defect data, the AI system identified glue gaps and other issues and helped Prohan remove low quality panels before assembly, preserving brand reputation. Read more about Prohan’s defect detection rate.

Forestry Mapping Automation

In forestry operations, companies like Komatsu use AI-powered drone imaging systems to map forest areas, classify trees, and detect unwanted objects. Computer vision powered drones that are scanning large forestry sites can classify trees and detect unwanted objects. AI reduces the need for manual field service, automating inspections and quality assessments. Read how Komatsu uses AI to map a forest.

AI for Tree Quality Evaluation

Recent research, such as the study “Advancements in Wood Quality Assessment: Standing Tree Visual Evaluation—A Review” (2024), highlights how laser-based and image-based techniques are transforming early-stage wood quality assessment by enabling ccurate measurement of stem form, branchiness, and visible damage in standing trees. Read more about it.

What types of defects and detection methods are possible in terms of AI for quality control?

Surface defect inspection with standard cameras

It’s a camera-based detection system. A standard, industrial-grade cameras are inspecting individual panels, looking for surface defects such as knots, cracks, warping or uneven grain.

AI-based system analyzes the pictures that are taken by those cameras and creates bounding boxes whenever it captures a defect.

Before the system can be effective, it needs a short training period where an engineer uses a dataset of defects to train the algorithm the difference between high quality and low quality panels.

With some human guidance AI vision systems improve over time by learning from past defect patterns. The ability to process multiple views of the wood simultaneously further improves accuracy, reducing rework and waste. It takes around 2-3 months to have the solution ready for one defect or 4-5 months to have it deployed in the factory with more defects that are needed to be inspected.

Moisture content monitoring with IoT sensors

Sensors placed throughout the drying and storage process continuously measure moisture levels in the wood. The data is transmitted to a central system that monitors moisture levels in real-time and alerts operators when levels fall outside the optimum range.

Maintaining the correct moisture content is essential to prevent warping, splitting and mould growth. Continuous monitoring ensures consistent drying and curing, minimising the risk of defects.

AI can analyse trends in moisture data and predict when adjustments to drying parameters are needed. By automatically controlling drying rates and humidity, manufacturers can prevent defects caused by improper moisture levels, optimise energy consumption and reduce drying times.

X-ray scanning for internal defects

X-ray systems provide non-destructive internal inspection of wood materials, detecting hidden defects such as knots, voids, cracks or density variations that can compromise structural integrity.

X-ray inspection is essential to ensure the reliability of wood products used in construction or furniture, where internal defects can cause long-term problems. It can analyse large batches of wood at high speed, significantly reducing inspection times.

Machine learning software analyses X-ray images, classifying defects and providing insight into their location and severity. This enables automated sorting and grading of wood based on quality. By integrating X-ray systems into production lines, manufacturers can identify defective pieces early and optimise processing for higher quality batches.

Thermography for drying control

Thermographic cameras monitor the temperature distribution of wood batches during drying or curing. Uneven heat distribution can cause localised drying problems resulting in warping, cracking or internal stresses.

Thermography provides a visual, non-contact method of assessing the drying process. It can identify potential problems before they result in defects and ensure uniform drying across large batches of lumber.

AI-powered thermography systems can automatically adjust drying schedules, temperatures or airflow to ensure optimum conditions for each batch. This reduces the risk of defects and ensures consistent quality across products, while optimising energy use.

Laser scanning for dimensional accuracy

Laser scanning technology creates 3D models of wood products to ensure dimensional accuracy. This is particularly important in woodworking applications where precise measurements are essential, such as flooring, cabinetry or engineered wood products.

Laser scanning provides highly accurate measurements in real-time, allowing manufacturers to verify that products meet exact specifications before further processing.

AI compares laser scans to digital models or blueprints to detect deviations. If a product is out of tolerance, the system can automatically adjust cutting or forming equipment, reducing errors and minimising material waste. This also leads to fewer rejects, increasing overall efficiency.

Acoustic emission testing for internal structure analysis

Acoustic sensors detect sound waves generated by the formation of cracks or internal stresses in wood. As wood is subjected to mechanical stresses such as bending or compression, AE testing identifies structural weaknesses before they lead to failure.

AE testing is a non-invasive method of detecting internal stresses and defects in wood products, particularly in structural applications such as beams, planks and engineered wood.

AI analyses acoustic data to identify patterns and predict potential failure points. This helps to adjust production techniques, such as compression or bending processes, to reduce internal stresses and improve material performance.

Fiber analysis for keeping paper and pulp quality

Optical sensors and AI-based analysis systems measure fibre length, density and uniformity in paper and pulp products. Maintaining consistent fibre quality is critical to producing high-strength, smooth and uniform paper products.

Automated fibre analysis helps ensure that paper meets specific quality standards, improving product performance and consistency in applications such as packaging, printing and hygiene products.

AI systems can adjust fibre processing parameters in real-time to maintain uniformity, while also detecting contaminants or impurities that could affect paper quality. Automated adjustments reduce waste and ensure smoother production with less downtime due to quality issues.

Does AI require a specific workflow or can it adapt to your current processes?

AI quality control systems are designed to adapt to your existing production workflow rather than disrupt it. At DAC.digital, we build each solution to fit the operational realities of your line and take care of inspection points, data flow to integration with existing equipment as well as quality management systems.

If human intervention is required at any stage, we provide hands-on training to ensure your staff can operate and interpret the system effectively.

Deployment is carried out in phases, allowing gradual integration and validation at each step. This approach ensures minimal downtime and full compatibility with your current processes. You can learn more about the deployment process here: AI quality control for manufacturing.

Choose a versatile digitisation partner for a successful long-term relationship

ML & Computer Vision expertise
Our team consists of experienced field experts with PhDs. They can help you select an existing solution or build a custom AI solution specifically for your production line.

Close on-site collaboration
Our process includes a number of solutions that lower the threshold for project entry in terms of time and budget. Workshops, Proof of Concept and MVP development allow you to deploy the first working versions of the solution in a matter of weeks.

Rapid idea validation and time to value
Nothing beats discussing your needs on site at your factory. Based in Europe, our specialists can hop on a plane or train and conduct an on-site inspection to diagnose your specific working environment.

360 competencies
We help you design a solution, build both the hardware and software parts of it, integrate it with your existing system architecture, optimise the product for ROI and solution longevity, and manage the system after deployment.

What makes DAC.digital the ideal partner for you?

Work with PhD-level scientists and experienced AI engineers

Our team is composed of PhD-level experts in AI and its subsets, such as machine learning, computer vision, and signal processing. They will help you find the optimal approach to your challenges and choose the most advanced technologies to build your solution.

All you need to start is an idea – we take care of the rest

Even if you are still unsure what system you want to build, we will assess your technology readiness and indicate possible areas where AI-powered solutions will work. Similarly, if you have a project idea but do not know what tools and methodologies to use, we will give you the answer.

Benefit from flexible cooperation models

You can count on us to take care of your AI solution development from start to finish, handle specific aspects of the project, or augment your in-house team with our experts. Additionally, you can take advantage of additional post-implementation support, as well as assistance with scaling your system.

Build a complete and scalable solution

With our extensive technological expertise, we offer not only AI solution development but also software, mobile development, hardware, and more. By leveraging our knowledge, you can build comprehensive and scalable products, adaptable to your evolving business needs.