A Product Yield Value Is Out of Range: Causes and Fixes

Yield is a pass-rate fraction that must sit above zero and no higher than one, and a value outside that range is either a critical error or a warning depending on which side it falls. EDGEBIC by User Solutions inflates a suggested build quantity by dividing the required quantity by the yield, so a yield of zero has no valid result and a yield above one would shrink the suggestion instead of protecting it. Yield lives in the product's inventory planning fields and works on the replenishment side, so an out-of-range value corrupts suggested quantities rather than the routing itself.

The anomaly report catches both cases as part of its plant-wide inventory checks. This post covers what each side of the range does, how the bad values usually get entered, and the correction, and it sits with the other master-data symptoms in the EDGEBIC troubleshooting guide. For the intended use of the field see how to set a product yield for scrap inflation, and for the concept see what is first pass yield.

What You Are Seeing

One of two things. Either the product's replenishment suggestions stop computing or come back with a quantity that makes no sense, or a plant-wide anomaly scan lists the product with a yield value the check calls out of range. The value in the product record is a zero, a negative, or a number well above one such as 95.

Why It Happens

Cause 1: Yield Was Entered as a Percentage

The field holds a fraction. A 95 percent pass rate is 0.95, not 95. A value of 95 reads as ninety-five pieces out for every one piece in, which is not a thing a process can do, so the check flags it as a warning.

This is the most common cause after a bulk edit or a data import, where a spreadsheet column held percentages and the mapping carried them across unchanged.

How to tell: the value is a whole number greater than one, and it matches a percentage you recognize.

Cause 2: Yield Was Left at Zero

A zero yield is the critical case. The suggested build quantity is computed by dividing the required quantity by the yield, and division by zero has no result, so the product's replenishment suggestion cannot be sized rather than producing a wrong number quietly.

How to tell: the value is exactly zero and the product produces no usable suggestion.

Cause 3: A Negative Value Was Saved

A negative yield is treated the same way as zero: critical, and unusable. Negatives normally arrive through an import that carried a minus sign or an inverted column rather than through manual entry.

How to tell: the value carries a minus sign and arrived with an import.

A Related Case: the Value Is Valid but Wrong

A yield of 1.0 is perfectly valid and means no inflation at all. If a product that genuinely scraps five percent of its pieces carries a yield of 1.0, no check fires, but every suggestion for it is sized short. That is not an out-of-range row, it is an accuracy problem, and it shows up as chronic shortages when the build finishes.

How to Fix It

• Convert a percentage to a fraction. Divide by one hundred: 95 becomes 0.95, 99.5 becomes 0.995.
• Replace a zero or a negative with the real pass rate, or with 1.0 if the product has no scrap inflation.
• Use realistic values. Typical figures sit between 0.90 and 0.99. A number below 0.5 says half the pieces fail, which is worth confirming before you save it.
• Refresh the inventory calendar so the affected suggestions are resized with the corrected quantity, then re-open the anomaly report to confirm the row cleared.

The Arithmetic, in One Example

A customer needs 500 good pieces. The product's yield is 0.9.

Leave the yield at 1.0 and the suggestion sizes at 500, the build finishes around 450 good, and the shortage surfaces at the end of the run when there is no time left to recover. That is the failure yield exists to prevent, and it is why an out-of-range value is worth clearing rather than tolerating. The inflation applies to the suggestion, so an order you enter by hand carries the quantity you typed and you size that one for scrap yourself.

How to Diagnose It, in Order

1. Run a plant-wide anomaly scan. The yield check is plant-wide, so a job-filtered run will not show it.
2. Read the flagged value. Zero or negative is critical; above one is a warning.
3. Open the product's inventory planning fields and compare the stored number against the pass rate the shop actually sees.
4. Correct the value and save.
5. Refresh the inventory calendar for that product, then re-open the report to confirm the row is gone.

How to Prevent It

• Treat yield as a fraction everywhere, including in the spreadsheets you import from. A percentage column should be converted before it is mapped, not after it lands.
• Audit yields after every product import. A plant-wide scan immediately after the import catches the whole batch at once rather than one order at a time.
• Set 1.0 deliberately on products that genuinely have no scrap inflation, instead of leaving the field to chance. An explicit 1.0 reads as a decision.
• Check yields against real results periodically. A value that was right two years ago drifts as processes change, and a stale yield quietly under-builds or over-builds every order. For the inventory side of the same audit see my on-hand quantity does not match the inventory ledger.