WIP sampling in Oracle Fusion Cloud Quality Management lets a planner inspect a representative sample of a work-order operation’s quantity instead of every unit, but only where the operation is not serial-tracked. Serial-tracked operations still require each serial to be inspected at that operation. Before going live, you choose one of three sampling approaches (ANSI/ASQC Z1.4, fixed count, or percentage). That choice determines both how many units are pulled and how a failing sample turns into a rejected inspection quantity.
Where WIP sampling applies
Oracle defines the capability in its own words:
“The Work In Process Sampling in Quality Inspection Management provides the ability to select representative sample(s) out of a discrete or process manufacturing work order operation quantity to determine the quality of non-serialized work in process (WIP).”
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Source: Oracle, How You Manage Inspections, https://docs.oracle.com/en/cloud/saas/supply-chain-and-manufacturing/26a/faumf/how-you-manage-inspections.html
That definition sets the scope boundary. Oracle documents WIP sampling for inline inspections at operations that are not serial-tracked, and it treats sampled WIP as non-serialized. For serial-tracked operations, the rule is different:
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- Supported: inline inspections at non-serial-tracked operations, where a representative sample of the operation quantity is inspected.
- Not a sampling case: serial-tracked operations, where each serial must be inspected at that operation. Sampling does not replace unit-level inspection of serialized items.
Sample selection is separate from the acceptance rule
Two decisions are easy to blur together. The sampling method decides how many units are inspected. The acceptance or rejection rule decides what the results mean for the whole inspection quantity. Oracle sets both through the inspection level, but they behave differently, so each method needs to be read on both counts.
ANSI/ASQC Z1.4
This option uses acceptance sampling by acceptable quality limit (AQL). The sample size and the acceptance and rejection numbers come from the sampling plan the standard defines, rather than from a figure you type in. Rejection occurs when the number of failed samples meets or exceeds the rejection number from the applicable AQL table. Oracle’s overview does not walk through the table lookup, so confirm the parameters against the standard itself. Oracle’s inspection-level data structure is listed in its schema reference, QA_INSPECTION_LEVELS_B. The standard is published as ANSI/ASQ Z1.4, and Oracle uses the ANSI/ASQC Z1.4 label.
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Fixed count
The planner specifies a fixed number of samples regardless of how many units the operation completes. The acceptance rule is strict. Oracle states:
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“With percentage-based sampling and fixed count sampling, the entire inspection quantity will be rejected if even one of the representative samples fails the inspection.”
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Source: Oracle, Inspection Levels, https://docs.oracle.com/en/cloud/saas/supply-chain-and-manufacturing/25c/fauqm/inspection-levels.html
Percentage
The planner specifies a percentage of the total operation quantity to inspect, so the sample count rises and falls with the quantity. The same one-failure rejection rule applies. Oracle’s overview does not describe how a fractional count is rounded, so check the result on a real operation before relying on it.
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| Method | How sample count is set | Response to operation quantity | Rejection rule | Detail Oracle’s overview does not give |
|---|---|---|---|---|
| ANSI/ASQC Z1.4 | Taken from the standard’s plan for the chosen AQL | Set by the standard’s tables; the lookup is not described in Oracle’s overview | Rejected when failed samples meet or exceed the rejection number | The table lookup steps |
| Fixed count | Planner-entered number of samples | Constant, regardless of operation quantity | One failed sample rejects the entire inspection quantity | Not stated |
| Percentage | Planner-entered percentage of total quantity | Scales with operation quantity | One failed sample rejects the entire inspection quantity | How fractional counts are rounded |
A worked comparison
The figures below are hypothetical. They assume a fixed count of 20 and a 10 percent sample, and they show the arithmetic rather than any Oracle default.
| Operation quantity | Fixed count of 20 (share inspected) | 10 percent (sample count, share inspected) |
|---|---|---|
| 50 units | 20 (40%) | 5 (10%) |
| 200 units | 20 (10%) | 20 (10%) |
| 400 units | 20 (5%) | 40 (10%) |
A fixed count keeps inspection workload flat while coverage shrinks as the operation grows. A percentage keeps coverage constant while the workload grows with the operation. Neither choice is inherently better; it depends on which of those two behaviors suits the operation.
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Setting up a sampling plan
Oracle’s pages describe the components and their dependencies but do not give one fixed click path for each step, so the sequence below follows the documented relationships.
- Confirm the operation is not serial-tracked. Serial-tracked operations fall outside sampling.
- Confirm a matching inspection plan exists. A matching plan is required to perform an inline inspection. Plans contain inspection elements, specifications, and criteria (see Oracle’s Inspection Plans documentation).
- Select the inspection level and its method: ANSI/ASQC Z1.4, fixed count, or percentage. For fixed count, enter the number of samples. For percentage, enter the percent. For ANSI/ASQC Z1.4, set the AQL-based parameters.
- Enter the sample quantity and unit of measure on the inspection level if you want Oracle to calculate quantity per sample and total sample quantity. Oracle calculates these values only when the level includes both inputs (see Inline Inspections).
- Set target values and limits on the plan’s characteristics, and the action rule for out-of-limit results. An out-of-limit result can create a quality issue under the configured action rule.
- Before go-live, run one work order through an inline operation transaction. Compare the calculated quantity per sample, total sample quantity, and the accept or reject outcome with the values you expected from your method.
Decisions to settle before production
Oracle does not recommend a sampling method or sample size, and the documentation does not identify one as preferable for any factory. The following are general quality-planning considerations to weigh against your own process:
- Defect consequence: how serious a missed defect would be if it reached the customer or the next operation.
- Detection expectations: how much confidence you need that a lot with defects will be rejected.
- Operation size variability: whether a fixed count’s shrinking coverage or a percentage’s growing workload is the bigger problem.
- Customer and regulatory requirements: whether a customer or regulator names a sampling standard or method.
- Characteristic limits: targets and limits that reflect your process capability and quality policy, not placeholder values.
- Serial-tracked content: which operations need unit-level inspection regardless of sampling.
Troubleshooting common setup conditions
| Condition | Documented behavior | What to check |
|---|---|---|
| Inline inspection cannot proceed | A matching inspection plan is required | Confirm the plan matches the inline inspection |
| Quantity per sample or total sample quantity is not calculated | Oracle uses these values only when the inspection level includes sample quantity and unit of measure | Add both values to the inspection level |
| Operation is serial-tracked | Each serial must be inspected at that operation | Plan unit-level inspection; do not configure sampling |
| Out-of-limit result creates a quality issue | Characteristic limits and the configured action rule govern the outcome | Review limits and action rules against process and quality policy |
| One failed sample rejects the whole inspection quantity | Applies to fixed count and percentage methods | If the plan should tolerate some failures, evaluate ANSI/ASQC Z1.4 instead |
What the published guidance does not settle
The Oracle pages cited here define software behavior and data fields. They do not publish a recommended sample size, an outcome rate, or a performance benchmark for WIP sampling. They come from the 25C, 26A, and 26B documentation sets, and feature behavior can change in later quarterly updates. Check your tenant’s release and review the configured inspection plan, inspection level, quantities, and acceptance and rejection values before you rely on them in production.
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