BestCut M4: Multi-sensor wood scanner for four-sided quality evaluation
with product placement of 2D rip-cutting/cross-cutting optimization

BestCut M4 wood scanner employs hi-res visual and 3D sensors alongside AI to accurately measure wooden cants' dimensions, defects, and grain patterns. Its AI-driven defect recognition system ensures stability with minimal sensitivity to environmental factors like sawdust, oil, or ice. The scanner has been built with real-world conditions in mind, ensuring flawless operation even in the harshest environments on the factory floor.

The scanner leverages HPC, digital twin technology, and an API for real-time business intelligence to streamline operations and boost efficiency.

How does it work?

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HPC powered optimization

Digital twin based integration optimization

The cloud-based or edge-based digital twin enables continuous optimization of sawmill operations using real-time data. By simulating various scenarios and exploring what-if situations, the digital twin allows for adjustments in product goals to align with downstream processing capacity, ensuring efficient and cost-effective production.

API for Real-Time Business Intelligence

The system features an API that connects the scanner to ERP or BI systems, providing detailed data on operation performance and allowing companies' IT staff to make data-driven decisions.

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1. Measurement and Defect Recognition

The BestCut M4 Scanner utilizes hi-resolution visual and 3D sensors to accurately measure log planes' dimensions, defects, and grain patterns. Its AI-driven defect recognition system ensures stability while minimizing sensitivity to environmental factors like sawdust, oil, or ice.

2. Optimization and full 2D Product Placement for each face

The scanner leverages HPC to optimize up to 10 thicknesses and widths with up to 100 products in each thickness. It executes full 2D product placement for cross-cutting/rip-cutting optimization on each face, using this information as input for multi-step cut scenarios

3. Opportunistic Forward-Looking Optimization

The scanner employs a generic optimization system that maximizes wood utilization while considering downstream processing costs, multi-step strategies, packaging material expenses, and wood chip prices for lower-quality or waste wood.

4. Destination Pocket Selection

With up to 4 destination pockets, the scanner selects cut width, face to cut and product destination from each side during each cycle.

5. Final Cut and Further Optimization

The final cut into the final material is implemented using the BestCut M2 cut optimization and scanning system. This system scans the raw plank from both sides and manages a multi-saw system to optimize further processing of the wood, ensuring maximum utilization and efficiency throughout the entire production process.

"There were no analogues for our specific solution to the situation. Zippy Vision was ready to undertake the development of such a solution, realizing that the development of such a solution might require the development of a number of new solutions, the likes of which Zippy Vision had not yet developed. A possible alternative was to request the adaptation of existing solutions from known manufacturers. However, their price was disproportionately high and there were risks that the technical task we set may not fully correspond to the solution to the business problem."

Gatis Gulbis,