Artificial intelligence, coming to a log turner near you…?

One of the issues that sawmills encounter is in setting equipment control parameters. In a perfect world, the information inputted would yield the expected end results. But, as many process control and optimization personnel at sawmills know, that’s not always the case. Working towards the digital transformation of the wood products sector, FPInnovations has been looking at ways to improve the accuracy and performance of log turners used during primary wood processing using new technologies such as artificial intelligence and machine learning.

Small error but big impact

A key machine to maximizing yield in primary wood processing is the log turner – it rotates the log and position it optimally in preparation for cutting. A review of over 20 FPInnovations studies evaluating log turner performance across Canada found that the average discrepancy between the set point rotation angle and the actual rotation angle can reach up to 25 degrees or more. To put this into perspective, the benchmark for rotation error is around 10 to 13 degrees.

Why reduce rotation error? Well, each time rotation error is reduced by as little as one degree, the material yield (recovery) increases by 0.15%.

Best practices for log rotation

To aid the industry quantify of the losses associated with rotational errors, FPInnovations has been looking at ways to integrate artificial intelligence and machine-learning into the turner optimizer, and has identified a number of best practices for log rotation. These best practices are outlined in a newly available 1-pager and report (available in French only) on the work and includes several actions that can improve machine efficiency, as well as detailed descriptions of the steps needed to transition towards an intelligent turner.

One key element in reducing rotation error is to better know the capabilities of the log turner and better diagnose it. This requires emphasis on establishing control areas and perform monitoring on variables including line speed, pressure and temperature of pneumatic and hydraulic systems, log characteristics, etc.

You may obtain the full report through FPInnovations Library. For additional information on the report or the 1-pager of best practices, you may contact  Sébastien Fillion, Senior Technologist, or Foroogh Abasian, Scientist, at FPInnovations.

FPInnovations would like to thank the Ministère des Forêts, de la Faune et des Parcs du Québec and the Ministère de l’Économie et de l’Innovation du Québec for their financial contributions to this project.

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