When ripping lumber, often the first thought is “How can I get the best yield.” It is important, however to ask that question within the context of what kind of products you produce. The highest yield possible is 100%, which means you do nothing to the board. The next highest yield comes from edging one edge of the lumber and then from edging two edges of the lumber. For most products produced, edging alone won’t be enough. Further ripping is necessary to produce the products you sell or components you need for production. It will be shown below that this additional ripping results in lower yields.

Edging Only

Assuming we need clean straight edges, the highest yield will be obtained by ripping down the two edges of each board, just far enough in from the edges to clean up both edges (using what we will call the maximum usable width of the board.) Since no board will be perfectly straight and free of wane, this maximum usable width will always be less than the average width of the board. In this case, our yield will be calculated by 100 times the maximum usable width divided by the average width of the board.

The following report shows the results of a simulation of over 40,000 boards being run on a saw where all of the blades can move, cutting the maximum usable width out of each board. The board data being used was gathered from an actual ripping operation.

Notice the yield of 94.31%. This is the highest possible yield that can be obtained from this lumber while maintaining finished edges. Unfortunately, this solution usually can’t be used to meet production requirements.

Ripping for Gluing

When ripping stock to be glued into panels, we can use random width pieces such as were generated in the edging example above, however we generally want to limit the minimum and maximum widths of boards going into the glued panels.

The following report shows a simulation of the same boards run again through a saw with all movable blades. This time we have limited the resulting rips to be within the range of 1 to 3”.

Opti-Rip Production Report
Setup Number: Supplier: Material Used: Thickness: Lumber Cost $/MBF: Misc: Lineal Ft. Processed: Board Ft. Processed: Board Ft/Hour: Process Time: Lumber Piece Count: Avg Lumber Width: Avg Yield: Lumber Pieces/Hour:		1 1.000 0 416476 201312 0 00:00 46696 5.780 90.28 0	Report Printed: Job Started: Job Ended: Rip Widths: Auto Deduct: Kerf: Avg Lumber Length: Avg BdFt/Board: Lumber Value: Product Value $/MBF: Product Cost $/MBF: Value Increase $/MBF:		02/28/06 01:34 pm 02/28/06 01:34 pm 02/28/06 01:34 pm 1 0.000 0.160 8.9 4.3 902 999 0 999
Width 1.000-3.000 Value/MBF 1000 Lin.Ft.Reqd 0 PCs.Prod 104180               Lin.Ft.Prod 929600 Bd.Ft.Prod 181760 Rip.Yield 90.2

Notice that the yield has dropped to 90.28%. This is due to the fact that we are taking extra saw cuts out of the middle of the wider boards.

Ripping to Specific Widths

While ripping random width rips for glue ups offers the best opportunity for achieving maximum yield, many ripping operations need to generate particular rip widths. The following shows the same lumber being ripped, but this time to five specific widths.

Opti-Rip Production Report
Setup Number: Supplier: Material Used: Thickness: Lumber Cost $/MBF: Misc: Lineal Ft. Processed: Board Ft. Processed: Board Ft/Hour: Process Time: Lumber Piece Count: Avg Lumber Width: Avg Yield: Lumber Pieces/Hour:		1 1.000 0 416476 201312 0 00:00 46696 5.780 87.92 0	Report Printed: Job Started: Job Ended: Rip Widths: Auto Deduct: Kerf: Avg Lumber Length: Avg BdFt/Board: Lumber Value: Product Value $/MBF: Product Cost $/MBF: Value Increase $/MBF:		02/28/06 01:38 pm 02/28/06 01:38 pm 02/28/06 01:38 pm 5 0.000 0.160 8.9 4.3 879 999 0 999
Width 2.625 3.000 2.500 1.125 1.875 Value/MBF 1000 1000 1000 1000 1000 Lin.Ft.Reqd 0 0 0 0 0 PCs.Prod 30825 26859 15748 15764 10143               Lin.Ft.Prod 277893 237994 140457 138451 92624 Bd.Ft.Prod 60789 59498 29261 12979 14472 Rip.Yield 88.7 86.2 90.0 86.6 88.3

Notice that the yield has dropped again to 87.92%. Because we are ripping only to specific widths, we are no longer using the maximum usable width of the each board. As a result, we are producing larger edgings (waste) and our yield drops.

Ripping for Yield

In the previous example, we ripped into five different widths, but we didn’t put any particular priority on any of the rips, so we produced whatever resulted in the highest yield. In many cases, there is a need to produce specific quantities of specific rip widths. A list of these rip widths and quantities is generally called a cut bill.

Our cut bill will generally determine whether we want to rip for yield, value, or required amounts. Ripping for yield is pretty straight forward. We will rip the lumber in such a way that we end up with the highest possible volume of the resulting product, regardless of what quantities of each rip we end up with. When ripping for glue up, ripping for highest yield makes sense because we don’t usually care how many of each width we rip. Whenever we rip to specific widths or rip for specific quantities, we are forcing the system away from the highest yield solutions, so yield drops. The harder we have to force the system to get what we want, the lower the resulting yield.

Ripping for Value

The previous example showed five fixed widths being ripped for maximum yield. There are times, however, when the highest yield doesn’t make sense. Take for example a moulding operation where we are ripping 3 1/8” and 6” moulding blanks. When a board with a maximum usable width of 6 1/2” is to be ripped, ripping for highest yield would give us two 3 1/8” rips, but one 6” moulding is probably worth more than two 3 1/8” mouldings. In such a case, it is not desirable for the optimizer to calculate the solution with the highest yield. Instead, a value (usually a value per board foot) is put on each desired rip and the optimizer then optimizes for value. Setting all rips to the same value is the same as ripping for yield. The further apart the values are set, the lower the yields that can be expected. Ripping for value can also be used to control the quantities of resulting rips. If the ripping operation is producing too little of a particular rip, increasing the value of that rip will tend to make the system produce more. Alternatively, if it’s producing too much of a particular rip, lowering the value for that rip will cause the system to produce less of that rip. Keep in mind that the further the values are changed from all being identical, the more yield will suffer.

Starting with the previous example, let’s assume we have a high need for the 1.875” rips. By increasing the value of the 1.875” rip, our simulation gives us different results.

Opti-Rip Production Report
Setup Number: Supplier: Material Used: Thickness: Lumber Cost $/MBF: Misc: Lineal Ft. Processed: Board Ft. Processed: Board Ft/Hour: Process Time: Lumber Piece Count: Avg Lumber Width: Avg Yield: Lumber Pieces/Hour:		1 1.000 0 416476 201312 0 00:00 46696 5.780 87.33 0	Report Printed: Job Started: Job Ended: Rip Widths: Auto Deduct: Kerf: Avg Lumber Length: Avg BdFt/Board: Lumber Value: Product Value $/MBF: Product Cost $/MBF: Value Increase $/MBF:		02/28/06 01:50 pm 02/28/06 01:50 pm 02/28/06 01:50 pm 5 0.000 0.160 8.9 4.3 908 1039 0 1039
Width 2.625 3.000 2.500 1.125 1.875 Value/MBF 1000 1000 1000 1000 1000 Lin.Ft.Reqd 0 0 0 0 0 PCs.Prod 19628 16217 8066 19618 49926               Lin.Ft.Prod 177155 144547 71284 170803 448358 Bd.Ft.Prod 38752 36136 14850 16012 70055 Rip.Yield 88.9 87.8 89.6 83.9 86.5

Notice that the increase in the value for the 1.875” rip resulted in a drastic increase in the quantity of 1.875” rips produced. The resulting yield dropped by another 1/2 percent as well. The further the rip values are moved from all being the same, the more the yield will drop.

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