Success Story

reading time: 2 min

Manufacturing

Material Industries

Visual Inspection

Anomaly Detection

Industrial Software

Context

Springer is a leading manufacturer of machines for the lumber industry. One of their products, the screw conveyor, is used extensively to feed logs into their processing line, and Springer identified a need for optimizing their product performance. The screws on the conveyor followed a stop-go motion, thus causing high levels of mechanical stress on the components and consumes excessive energy.

Challenge

The challenge was to find the optimal settings with regard to screw speed and screw angles in order to eliminate the stop-go motion and keep the screws moving at a constant rate.

Assignment

craftworks was assigned with developing a controller that would be able to receive machine information from the PLC (Programmable Logic Controller) and calculate the required speed to be used, then sending it back to the PLC, which could, in return, adjust the required parameters in real time.

Solution

A Python based model was created which obtained and calculated the data. A PoC was then implemented using a PLC, with the next steps consisting of developing a product based upon this for future screw conveyors.

Leveraging AI to optimize screw conveyor operations, this case demonstrates a 25% error reduction, marking a significant stride towards mechanical efficiency and sustainability in the lumber industry.

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three male team members of craftworks at a meeting table looking at laptops and working

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