This project was my main task while I was a Process Control Engineering intern at the Potlatch Corp. Sawmill. This is the project I presented to the corporate branch at the end of my internship. I no longer have access to the project because it was proprietary and I never made a sanitized version. The basic problem they had was that each machine in the sawmill created an Excel workbook each day containing detailed production data. This means that finding information was very cumbersome and there was no way to see a holistic view of what was going on.

The VBA script I wrote searched a folder for new workbooks, scraped the data out of those workbooks, and appended a summary of the data to the script workbook. The workbook had several pages with different summaries and charts representing the production trends over various time scales and metrics. In a sawmill the most important metric is call LRF (Lumber Recovery Factor). This is a measure of how many board feet of lumber were recovered relative to the volume of a log. This means that the LRF basically represents the efficiency of your sawmill with the maximum number being 12 and 7-8 being a good recovery. Increases in LRF over time are mostly due to decreased kerf with newer saw materials and more accurate laser scanning and cut planning. LRF is also effected by the moisture, diameter, and taper of a log. Curves have been generated that estimate the maximum efficiency based on size and taper. Typically sawmills will specify standards for the logs they will accept based on a minimum acceptable theoretical LRF and the maximum processing size of their mill.

The other metric of interest was board feet per hour. More throughput usually equals more profit, though increasing your board feet at the cost of LRF can be costly. It is important to track both of these values as well as the cost of your logs, running costs, and sale price of lumber to be able to calculate your ideal LRF and BF/hr.