Transforming Sawmills with AI
Perspective from John Craig, VP of Revenue & Customer Success
- Blog
Throughout my career in industrial technology, consulting, and operations, I have seen the incredible impact that technology can have on industry — both positive and negative. On the positive side, technology can lead to remarkable increases in productivity and quality. However, on the flip side, companies sometimes attempt to deploy the wrong technology or poorly execute upgrades, which can lead to costly setbacks. With this perspective, I have been closely following recent advancements in AI, particularly in AI vision, which are generating significant excitement within the industry. At RIOS, we believe these advancements offer transformative opportunities for sawmills across the United States. However, like all technologies before them, they come with the risk of wasted time, money, and potential damage to a company’s reputation if not applied to the right problems or implemented effectively. This blog post aims to highlight how AI can be strategically implemented in manufacturing operations to drive efficiency, enhance productivity, and reduce costs, while minimizing the risks of misapplication and poor execution.
AI vision systems can now perform tasks that were previously manageable only by human operators — and often with greater accuracy. This technology enables sawmills to gain deeper insights into their processes, creating numerous opportunities for automation and optimization. Here’s how it’s being done …
Enhancing Industrial Engineering
One of the interesting aspects of AI and computer vision in particular is that it can help with the job of evaluating current manufacturing operations and forecasting the impact of new technologies on them. This is a key part of the discipline of industrial engineering which all manufacturing companies do on a daily basis.
AI vision systems can serve as intelligent agents attached to sensory equipment, providing comprehensive process and material insights. This capability allows sawmills to:
- Identify and rectify inefficiencies: Detecting issues in real-time enables quick adjustments, improving overall plant layout and performance management.
- Support labor: AI can act as a co-pilot for human operators, offering real-time guidance and on-the-job training to enhance efficiency.
- Control existing machinery: AI can optimize the performance of current equipment, reducing maintenance needs, improving output quality, and minimizing material waste.
Incremental Automation: A Strategic Approach
While the idea of fully AI-controlled robotics is appealing, it’s often not the most practical or cost-effective solution for every process. Instead, a phased approach to automation can deliver substantial benefits. At RIOS, we advocate for a five-step process to determine the optimal level of AI integration:
- Step 1: Pre-sales assessment: Begin by analyzing videos of your existing processes, whether from security cameras or cell phone footage. This initial review helps identify areas where AI could add value.
- Step 2: Observe and learn: Deploy AI with cameras or other sensors to gather detailed data about the process. This stage involves monitoring production over an extended period to understand what the AI can see, predict, and improve.
- Step 3: Operator co-pilot: Use AI to support human operators by learning from the best-performing employees and providing real-time notifications and advice. This step helps new employees get up to speed quickly and ensures consistent performance.
- Step 4: Minor automation: Integrate AI to control existing machinery, addressing issues such as conveyor jams before they occur. This level of automation enhances efficiency without the need for new equipment.
- Step 5: Major automation: Based on the data collected, evaluate whether introducing new AI-controlled machinery makes sense. This stage involves a comprehensive assessment to ensure that any new investment will deliver measurable benefits.
Data-Driven Decision Making
Each stage of this process is supported by data, enabling you to simulate potential improvements and make informed decisions. For example, if AI detects that conveyor jams cost your sawmill 40 hours of downtime each month, you can clearly see the value of implementing minor automation to address this issue. This data-driven approach ensures that any automation investment is justified by tangible benefits.
Implementing RIOS Solutions
At RIOS, we offer a repeatable process tailored to various industrial settings. Our core system features a robust edge device with trainable AI models, supporting a wide range of cameras and sensors. We work closely with industrial engineering partners and our clients to ensure the AI system is finely tuned to your specific processes.
Our platform allows for real-time data collection, performance management, and automation, providing actionable insights to your staff. With standard interfaces for mobile devices and PLC-controlled machinery, our solutions aim to reduce downtime, improve quality, and enhance the reliability of your operations.
Continuous Improvement
AI implementation is not a one-time effort but a continuous improvement process. As you gather more data and refine the AI system, you can:
- Enhance AI training: Continuously improve the AI’s understanding of your processes.
- Perform new analyses: Use new metrics to identify further optimization opportunities.
- Adjust your processes: Reposition cameras and sensors as needed to capture better data and drive further improvements.
Conclusion
Deploying AI in production is a journey that requires careful planning and strategic implementation. By following a phased approach and leveraging data-driven insights, sawmills can harness the power of AI to transform their operations. At RIOS Intelligent Machines, we are committed to helping you navigate this journey and achieve sustainable success.
We look forward to exploring how AI can revolutionize your sawmill operations.
