Average tree volume in Eastern Canada has shrunk from 170 dm³ in the 70s to 123 dm³ today. Over the same period, the wood consumption factor dropped from 5.6 m³/Mfbm to 4.0 m³/Mfbm. Some mills even do better than this and achieve factors approaching 3.5 m³/Mfbm. The objective of this project was to generate performance indicators for Eastern Canadian mills while assessing the most recent sawing optimization techniques. In order to quantify the effect of the resource on the results, we identified distinct geographic areas, and the North-American market served as a reference for economic analyses. Wood consumption factors and mill revenue were selected as principal performance indicators; and the Optitek® simulator was used to analyze the mill scenarios corresponding to the following tables. It should be noted that resource characteristics have far less impact on results than lumber manufacturing techniques or log lengths. Similar results were obtained in the various regions, even though tree diameters were different.
Stud mills
Description of scenario Wood consumption factors
(m³/Mfbm) Value uplift
(%)
8’ mill (integrated log processor/curve sawing) 4.14 -
10’ mill (integrated log processor/curve sawing) 4.28 2.0
8’ mill (integrated log processor + canter/twin) 3.62 6.1
9’ mill (integrated log processor + canter/twin) 3.73 1.0
10’ mill (integrated log processor + canter/twin) 3.73 1.0
A stud mill needs to have a canter/twin on one of its lines to achieve a satisfactory performance level. Stud mills should also process the longest logs possible to maximize revenue.
16’ dimension mills
Description of scenario Wood consumption factors
(m³/Mfbm) Value uplift
(%)
Non-optimized (straight sawing) 4.32 -
Conventional bucking (straight sawing) 3.74 18.9
Conventional bucking (curve sawing) 3.62 2.7
Optimized bucking (straight sawing) 3.52 0.4
Optimized bucking (curve sawing) 3.46 2.4
Optimization of primary and secondary breakdown operations significantly increases revenues in 16’ mills while greatly reducing wood consumption factors. Curve sawing and optimized bucking further improve such results; these two techniques are complementary as the former does not cancel out the benefits provided by the latter. To be effective, optimized bucking needs to be integrated into a flexible line that is capable of processing logs of all lengths.