30,000 inspection lots a year — with 91% recorded touchlessly.
A regulated manufacturer processes approximately 30,000 SAP QM inspection lots per year. Supplier COAs and other quality evidence contain the measurements needed for results recording, but the values must first be connected to the correct inspection lot and SAP inspection characteristics, checked against specification, and handled according to the organization's quality controls.
Artificio automates that path. For incoming supplier inspection, each COA value is extracted, mapped to its SAP inspection characteristic, evaluated against the applicable specification context, and recorded to the inspection lot. The workflow can also prepare a proposed usage decision based on the configured rules and recorded results. In-spec lots can follow the approved straight-through path; out-of-specification or ambiguous results are routed to QA with the affected characteristic and evidence already identified.
The same results-recording architecture can support multiple SAP QM inspection scenarios, including inspection type 01 for goods-receipt/incoming inspection, type 03 for in-process inspection, and type 04 for inspection at goods receipt from production. The source and gating rules change by inspection type, but the automation pattern remains consistent: resolve the lot → resolve the characteristic → validate the result → record or route.
At the stated production scale, 91% of lots are recorded touchlessly, and clean-lot processing time moved from approximately 12 minutes to 40 seconds.
A measured value is useful only when it is attached to the right SAP quality context.
A result such as “4.7” is not enough. SAP needs the relevant material/product, batch or serial context where applicable, inspection lot, operation, inspection characteristic, unit, specification context and result type.
Source documents may use supplier test names rather than SAP characteristic descriptions. Units can differ. Results can appear as numbers, ranges, pass/fail statements, qualitative codes or tables. One document may contain dozens of characteristics while SAP expects each result in the correct inspection structure.
- ✕Open the COA, lab report or inspection record.
- ✕Find the related inspection lot in SAP.
- ✕Navigate to the relevant operation and characteristics.
- ✕Read each result manually.
- ✕Translate source terminology to SAP MICs.
- ✕Check units and specification limits.
- ✕Enter results characteristic by characteristic.
- ✕Investigate OOS or missing values.
- ✓Evidence enters an automated workflow.
- ✓AI extracts tests, values, units and identifiers.
- ✓Inspection-lot context is retrieved from SAP.
- ✓Source tests are mapped to SAP characteristics.
- ✓Results are validated against SAP context.
- ✓Clean results can be recorded automatically.
- ✓Only true quality exceptions reach reviewers.
- ✓Evidence remains linked to result history.
Quality specialists spend time transcribing evidence instead of investigating exceptions.
The repetitive work is more than typing. Reviewers identify the lot, locate the correct characteristic, compare terminology, verify units, inspect specification limits and determine whether the result can be accepted.
The objective is not to remove quality judgment. It is to separate results that can be deterministically matched and validated from results that require interpretation, disposition or approval.
A source-document-to-SAP-QM workflow built around inspection context.
1. Quality-document capture
Artificio identifies incoming quality evidence and preserves the original source from approved intake channels.
2. Result extraction and normalization
The platform extracts the material/product, batch or lot, inspection reference, test/characteristic name, measured value, unit, qualitative result, specification text, sample information and other configured fields.
3. Inspection-lot resolution
Available identifiers are combined with SAP data to resolve the appropriate inspection lot. If the evidence cannot be tied confidently to the correct lot, the workflow routes it for review rather than recording against a guessed lot.
4. Characteristic mapping
Source test terminology is mapped to the relevant SAP inspection characteristic, including approved aliases or mappings when supplier/laboratory terminology differs from SAP.
5. Specification and unit validation
Quantitative values can be checked against the applicable SAP characteristic context and configured limits. Qualitative observations can be mapped to permitted codes or valuation logic. Conversions are used only where explicitly configured.
6. Controlled results recording
When the lot, characteristic, value, unit and required controls are satisfied, the approved result can be sent to SAP QM. Anything outside the straight-through policy remains in an exception workflow.
One results-recording layer across incoming, in-process and production-receipt inspection.
The manufacturer can apply the same Artificio pattern across different SAP QM inspection origins while preserving the controls appropriate to each process.
| SAP inspection type | Typical quality evidence | Artificio automation focus | Time-saving opportunity |
|---|---|---|---|
| 01 — Goods receipt for purchase order | Supplier COA, certificate, receiving inspection, laboratory results | Match supplier/batch/material evidence to the GR inspection lot and MICs; validate specifications; record results; propose UD under configured policy | Removes repetitive COA-to-lot transcription and concentrates QA effort on OOS/missing results |
| 03 — In-process inspection | Operator checks, shop-floor forms, process measurements, lab/in-process test records | Associate process results with the correct inspection lot/operation/characteristics and record approved values | Reduces manual recording during production and shortens the delay between measurement and SAP visibility |
| 04 — Goods receipt from production | Final/production inspection evidence, finished-product test records, laboratory or release data | Resolve the production-receipt inspection lot, validate final results and record them before downstream quality disposition | Reduces repetitive final-result entry and can make completed quality evidence available in SAP sooner |
The measured case-study improvement applies to the customer's clean-lot workflow represented by the supplied metrics. For inspection types 01, 03 and 04, Artificio uses the same automation architecture, but time savings should be measured separately for each process because document sources, characteristic counts, sampling, review requirements and usage-decision controls can differ.
Match the evidence to the SAP characteristic before evaluating the result.
There are two confidence questions: did Artificio read the evidence correctly, and does that result belong to this SAP lot and characteristic? Both must be satisfied for straight-through recording.
| Quality evidence | SAP QM context | Outcome |
|---|---|---|
| Material + batch + inspection reference | Single applicable inspection lot | Lot resolved |
| Test name matches configured characteristic | Applicable MIC | Characteristic resolved |
| Supplier test name differs | Approved alias / mapping | Mapped / candidate review |
| Measured value + expected unit | Quantitative characteristic + limits | Validate specification |
| Different source unit | Approved conversion available | Convert & validate / review |
| Pass/fail or qualitative observation | Permitted code logic | Map to approved code |
| Required result missing | Expected SAP characteristic exists | Missing-result exception |
| Multiple possible lots/MICs | No deterministic resolution | Human review |
Artificio does not treat a value as acceptable merely because the source document shows it inside a printed range. The workflow can validate the extracted evidence against the relevant SAP QM context and configured enterprise quality rules.
Out-of-specification results should become quality work — not data-entry errors.
When a result cannot follow the straight-through path, Artificio creates an explained exception showing the source evidence, extracted result, SAP inspection context and reason the workflow stopped.
| Exception | Evidence surfaced | Typical action |
|---|---|---|
| Out-of-specification result | Measured value versus applicable limits | Quality review / disposition workflow |
| Inspection lot unresolved | Identifiers and candidate lots | Select lot / investigate |
| Characteristic unresolved | Source test and candidate MICs | Confirm mapping |
| Required result missing | Expected characteristic vs source | Request result / hold |
| Unit mismatch | Source vs SAP unit | Approved conversion / review |
| Low-confidence value | Source location + extracted candidate | Reviewer correction |
| Qualitative code unclear | Observation + permitted codes | Select approved code |
Record the results first. Propose the usage decision under controlled rules.
After validation, Artificio sends approved quantitative or qualitative results through the supported SAP integration method and retains the SAP response with the source evidence. For this use case, Artificio can also derive a proposed usage decision from the recorded results and configured quality rules.
The distinction matters. Results recording captures what was measured. The usage decision determines the disposition of the inspection lot. Artificio can automate or propose that next step only within the quality organization's approved policy. In-spec, complete, high-confidence lots can be eligible for straight-through completion where permitted; OOS, incomplete, ambiguous, or policy-sensitive lots are routed to QA before the usage decision is finalized.
This keeps quality authority explicit while still removing the repetitive work from clean lots.
Document and workflow intelligence around SAP QM as the system of record.
The exact interface depends on SAP version, deployment model, enabled APIs/BAPIs, middleware, authorizations and QM scenario. Artificio works through the enterprise's approved integration layer.
Quality automation needs stronger evidence, not less evidence.
Artificio can retain the original inspection evidence, extracted values, lot resolution, characteristic mapping, SAP specification context, validation outcome, reviewer corrections, approvals, integration request and SAP response.
Straight-through recording should be limited to scenarios approved by the quality organization. Low-confidence extraction, ambiguous lot/MIC mapping, OOS results, missing required characteristics and policy-sensitive cases remain human-in-the-loop.
Start with repeatable inspection scenarios and known document sources.
A practical pilot starts with a bounded plant/material family, known inspection types, representative lots, stable MICs and a manageable set of COA, lab or inspection formats.
Discovery should document lot identification, mandatory characteristics, quantitative/qualitative types, units/conversions, specification handling, sampling requirements, selected sets/codes, precision, source terminology, exception owners, SAP integration and which results may record automatically.
Approximately 27,300 inspection lots recorded touchlessly each year.
At 30,000 inspection lots per year and a 91% touchless rate, approximately 27,300 lots per year can follow the touchless results-recording path, leaving roughly 2,700 lots for exception or QA handling based on the supplied case-study metrics.
Reducing clean-lot processing from 12 minutes to 40 seconds removes approximately 11 minutes 20 seconds of processing time per touchless lot. Applied to 27,300 touchless lots, that equates to approximately 5,157 gross processing hours per year. This is a mathematical implication of the supplied metrics, not a separately measured labor-savings claim; actual capacity benefit depends on characteristic count, review requirements, staffing, inspection type and operating model.
For inspection types 01, 03 and 04, the same automation pattern can reduce repetitive results-recording effort, but each inspection process should have its own baseline. Incoming supplier COAs, in-process measurements and production-receipt/final inspection evidence can differ substantially in format, frequency, number of characteristics and QA controls.
Quality personnel spend less time transferring clean results into SAP and more time on out-of-specification values, missing evidence, ambiguous characteristic matches and the quality decisions that require expertise.
The differentiator is not reading the COA. It is understanding where every result belongs in SAP QM.
A generic document tool can extract test names and values. SAP QM automation requires inspection-lot resolution, characteristic mapping, unit/specification context, quantitative and qualitative handling, exception policy and controlled results recording.
An out-of-specification result is not an automation failure. It is a successful detection of quality work that requires the appropriate human or downstream quality process. The same principle applies across incoming inspection type 01, in-process inspection type 03, and inspection type 04 at goods receipt from production.
Artificio connects inspection evidence to live SAP QM context, determines which lot and characteristic each result belongs to, validates the result under configured quality rules, records clean results, and routes the exceptions that require quality judgment.