A blank template is hard to fill in without a reference. Each of these three cases carries all ten appendices — Use-Case Charter through Assessment Questions and Glossary — to completion, end to end, on real wind-sector situations from the Case Atlas. Read one before opening the blank appendix — then adapt, don't copy, the specifics to your own use case.
WORKED EXAMPLE 01 · Blade-bonding void-rate anomaly signal
A candidate-correlation flag, never a stated cause
A blade-bonding line has an intermittent void rate that inspection has not yet linked to a specific cure parameter. Process engineering wants a preventive signal before the next non-conformity, not a retrospective root-cause report.
APPENDIX A · USE-CASE CHARTER — FILLED
Quality problem / recurring decision
Void-rate excursions on the blade-bonding line are caught after cure, not predicted before it; root cause is not yet linked to a cure parameter.
Process owner
Amara Solis, Process Engineering Lead, Bonding Line 2
Manual baseline
Process engineers review cure-cycle trend charts weekly by hand; correlation to void rate has taken up to six weeks to establish per prior incident
Intended use
Flag cure-cycle windows whose temperature/pressure/dwell pattern statistically correlates with elevated void rate, ranked by strength of association, as an investigation input only
Evidence sources and revisions
Cure-cycle logs (temperature, pressure, dwell time) and void-rate inspection records, joined by lot and station, cure-log schema v2.1 since 2025-11-01
Output destination
Automated report
Human decision boundary
Human reviews flagged cases only
Acceptance measure
False-flag rate below 15% against process engineering's independent judgement on a held-out set of 40 prior lots
APPENDIX B · DATA CLASSIFICATION RULE — FILLED
Evidence class
Internal process data — cure-cycle logs and void-rate inspection records, not customer or personal data
Permitted use
Statistical correlation analysis for investigation triage only; not permitted as input to any automated process-parameter change
Retention
Retained for 3 years alongside the source cure-log and inspection records it was joined from, per existing quality-record retention policy
Access
Process Engineering and Bonding Line 2 quality staff only; no supplier or external access
Source authority
Cure-log schema v2.1 (MES export) and inspection record system are the systems of record; the tool holds no independent copy of authority
APPENDIX C · AI RISK ASSESSMENT — FILLED
consequence
medium — a missed or false preventive signal delays a real fix but does not itself release a defect
influence
medium — output opens or declines an investigation, not a disposition
criticality
medium — void rate affects a structural bonding characteristic
sensitivity
low — internal process data only, no restricted evidence
traceability
low — flagged windows link directly to the source cure-log rows and lot IDs
propagation
medium — an undetected recipe drift could affect multiple lots before caught manually
volatility
low — the statistical model is refit quarterly, not per-run
dependency
low — runs on internally held process data, no external provider
CONTROLS AND SAFEGUARDS
Output is labelled explicitly as a candidate-correlation list, never a stated cause. The tool's output destination is fixed as an investigation input; it cannot trigger a process-parameter change directly.
RESIDUAL RISK AND ACCEPTANCE
Residual risk of a missed preventive signal is accepted by the Process Engineering Lead given the existing weekly manual trend review remains in place as a backstop.
Result: Level B
APPENDIX D · ONE-PAGE TOOL SPECIFICATION — FILLED
Inputs
Cure-cycle logs (temperature, pressure, dwell time) and void-rate inspection records, joined by lot and station
Outputs
Ranked list of cure-window candidate correlations with association strength, lot IDs and source rows
Limits
Requires at least 20 logged cure cycles per lot; does not run on lots below that threshold
Configuration
Anomaly-correlation model v1.4, quarterly refit, cure-log schema v2.1
Acceptance
False-flag rate below 15% on a held-out set of 40 prior lots
Human review
Process engineer investigates every flagged window before any parameter change is proposed
APPENDIX E · GOLDEN SET AND EVALUATION REGISTER — FILLED
Known-correct cases
12 prior lots with a process-engineer-confirmed cure-parameter root cause, used to check the model surfaces the true correlation
Hard cases
6 lots with two overlapping candidate parameters, where the true cause was only resolved after supplemental testing
Borderline cases
5 lots just above the 20-cycle minimum, to check the low-confidence flag behaves correctly near the threshold
No-finding cases
9 lots with normal void rate and no known cure-parameter issue, used to check the false-flag rate on clean data
APPENDIX F · QUALIFICATION FILE — FILLED
Intended use and limits
Assistive triage only; surfaces candidate cure-window correlations for engineer investigation, never states a confirmed cause
83% of investigator-confirmed correlations from the prior 12 months were also surfaced by the model on a held-out set; false-flag rate 12%
Known limitations and controls
Degrades when a lot has fewer than 20 cure cycles logged; flagged low-confidence windows are marked, not suppressed
Approval and monitoring
Approved by A. Solis, 2026-02-14; false-flag rate reviewed monthly against the acceptance measure in the charter
APPENDIX G · PRODUCTION GO-LIVE CHECKLIST — FILLED
Operational controls
Tool output feeds the weekly cure-trend review meeting only; no direct write access to MES or cure-cycle set points
User training
Process engineers briefed on reading association-strength scores and the low-confidence flag before first live use
Monitoring
Monthly false-flag rate tracked against the 15% acceptance measure; refit schedule logged
Incident handling
Any missed preventive signal later confirmed by a non-conformity is logged and reviewed at the next quarterly refit
APPENDIX H · CHANGE AND REVALIDATION LOG — FILLED
Change
Quarterly refit of anomaly-correlation model v1.4 on the latest 12 months of cure-log and inspection data
Retested
False-flag rate re-measured on the current 40-lot held-out set after each refit
Accepted by
A. Solis, Process Engineering Lead
Why
Keeps the correlation model current as bonding-line process drift occurs, without changing the intended use or output destination
APPENDIX I · SUPPLIER AND THIRD-PARTY AI QUESTIONNAIRE — FILLED
Provider
Internally built and hosted; no third-party AI service in this use case
Source
Cure-log and inspection data originate entirely from in-house MES and inspection systems
Access
No external party has access to cure-log or inspection data used by the model
Change control
Model refits are internal changes, logged in the change and revalidation log, not a supplier-issued update
Incident and evidence responsibilities
Not applicable — no supplier relationship to notify or audit for this tool
APPENDIX J · ASSESSMENT QUESTIONS AND GLOSSARY — FILLED
Practical question
Would a process engineer trust this flag enough to open an investigation without first checking the raw trend chart?
Practical question
What happens on a lot with exactly 19 logged cure cycles — is the exclusion boundary obvious to a new engineer?
Glossary term
Candidate correlation — a statistical association surfaced for investigation, explicitly not a stated or confirmed cause
Glossary term
False-flag rate — the proportion of surfaced correlations that an investigator's independent judgement does not confirm
WORKED EXAMPLE 02 · Structural weld-package completeness check
Report what was checked, not just what passed
A structural welding package for a tower section arrives from a new supplier with a large document set: weld procedure qualifications, NDT reports and material certificates. The reviewer has a fixed window before the next assembly gate.
APPENDIX A · USE-CASE CHARTER — FILLED
Quality problem / recurring decision
Manual completeness review of large weld-package submissions is slow and inconsistent across reviewers, especially under assembly-gate deadlines
Process owner
Tomas Nkemelu, Supplier Quality Engineer, Tower Structures
Manual baseline
One reviewer manually checks each package against a 34-item checklist, approximately 3 hours per package
Intended use
Confirm every required document type and field is present, and flag where a submitted value appears inconsistent with the applicable specification revision, as a structured findings list
Completeness and consistency checking against specification revision D only; not permitted as a standalone accept/reject basis
Retention
Retained for the life of the tower structure record, matching existing supplier-document retention policy
Access
Supplier Quality Engineering and the assembly-gate review board; not shared outside the reviewing organisation
Source authority
Specification revision D and required-document checklist v3 are authoritative; the tool never overrides either
APPENDIX C · AI RISK ASSESSMENT — FILLED
consequence
high — an undetected missing NDT report or misread material certificate could allow a non-conforming weld package to pass the gate
influence
high — directly informs a gate-pass/hold decision
criticality
high — structural tower weld is a safety-critical characteristic
sensitivity
medium — supplier-submitted commercial and technical documents
traceability
medium — every flag names the document and field, but illegible scans may be silently unreadable if not explicitly reported
propagation
medium — a systematic misread could affect every package from one supplier
volatility
low — specification revisions change a few times a year, not per-run
dependency
low — runs on internally held documents, no external provider
CONTROLS AND SAFEGUARDS
The tool states explicitly what it checked and what it could not check (illegible scans, missing pages) rather than reporting silence as a pass. Every flagged inconsistency names the exact document and field. A named reviewer accepts, rejects or escalates every flag.
RESIDUAL RISK AND ACCEPTANCE
Residual risk of a missed inconsistency is accepted by the Supplier Quality Engineer on the condition that unreadable or unchecked items are always recorded as open gaps, never as passes, and every package retains a named human sign-off.
Result: Level C
APPENDIX D · ONE-PAGE TOOL SPECIFICATION — FILLED
Inputs
Supplier's submitted document package against specification revision D and required-document checklist v3
Outputs
Structured findings list: present/missing per checklist item, and any field value inconsistent with the specification, each naming its document and location
Limits
Cannot assess illegible or handwritten scans; does not issue an accept/reject disposition
Thirty-Second Lab run on 25 flagged findings: reviewers verified 24 of 25 within 30 seconds against the cited location
Known limitations and controls
Cannot assess illegible or handwritten scans; these are reported as unchecked gaps, never silently skipped
Approval and monitoring
Approved by T. Nkemelu, 2026-01-20; escalation path to Quality Director for any unresolved flagged inconsistency before gate release
APPENDIX G · PRODUCTION GO-LIVE CHECKLIST — FILLED
Operational controls
Findings list feeds the reviewer's existing sign-off workflow; the tool cannot itself pass a package through the assembly gate
User training
Reviewers trained on the unchecked-gap category before relying on the tool for a live gate decision
Monitoring
Rate of reviewer-overturned findings tracked monthly; any illegible-scan gap left unresolved at gate time is logged
Incident handling
A non-conformity that passed the gate despite an available document is investigated as a tool-and-process failure, not tool-only
APPENDIX H · CHANGE AND REVALIDATION LOG — FILLED
Change
Specification revision D superseded a prior revision; document-parsing configuration updated to v1.2 to match new field layout
Retested
Golden set re-run against the updated configuration before go-live on revision D packages
Accepted by
T. Nkemelu, Supplier Quality Engineer
Why
A specification revision changes which field values count as consistent, so the tool's configuration must be revalidated, not assumed compatible
APPENDIX I · SUPPLIER AND THIRD-PARTY AI QUESTIONNAIRE — FILLED
Provider
Internally operated document-parsing tool; documents originate from an external supplier but the tool itself is not third-party AI
Source
Supplier submits the weld package directly through the existing document intake channel
Access
Supplier has no access to the tool's findings list before the internal reviewer has assessed it
Change control
Supplier-side document template changes are tracked against checklist v3 and trigger a configuration review
Incident and evidence responsibilities
Supplier remains responsible for submitting complete, legible documentation; the tool's role is limited to checking, not correcting, submissions
APPENDIX J · ASSESSMENT QUESTIONS AND GLOSSARY — FILLED
Practical question
If a required document is present but the tool cannot parse it, does the reviewer see that as 'missing' or as 'unchecked'? The record must say which.
Practical question
How does a new reviewer learn to distinguish a flagged inconsistency from an illegible-scan gap without opening every source document?
Glossary term
Unchecked gap — an item the tool could not assess (e.g. an illegible scan), recorded as an open item, never reported as a pass
Glossary term
Thirty-Second Lab test — an acceptance measure requiring a competent reviewer to verify any flagged finding within thirty seconds against its cited source
WORKED EXAMPLE 03 · Cross-site corrective-action recurrence retrieval
A candidate match still needs the investigator's own verification
The same bolted-joint torque non-conformity keeps recurring on a tower platform across multiple sites. Each site has opened its own corrective action, but no one has compared them, so investigations restart from zero each time.
APPENDIX A · USE-CASE CHARTER — FILLED
Quality problem / recurring decision
Recurring bolted-joint torque non-conformities are investigated independently per site with no cross-site comparison, so root cause is never resolved systemically
Process owner
Priya Adeyemi, Corrective Action Board Chair
Manual baseline
Investigators manually search a shared drive of prior corrective actions by keyword, when they think to search at all; no baseline search time is currently tracked
Intended use
Cluster prior corrective actions by symptom similarity to the current investigation, surfacing candidate matches with their stated root cause and containment, for the investigator to judge relevance
Evidence sources and revisions
Closed and open corrective-action records across all sites, CAPA register export dated 2026-01-05
Output destination
Operator dashboard
Human decision boundary
Human reviews flagged cases only
Acceptance measure
Retrieval must surface at least the same matches a manual cross-site search finds on a 10-case test set, with a false-lead rate the investigator can characterize
APPENDIX B · DATA CLASSIFICATION RULE — FILLED
Evidence class
Closed and open corrective-action records across all sites — internal quality records, some naming individuals as investigators
Permitted use
Similarity clustering for investigation input only; not permitted to auto-close, merge or reclassify any corrective action
Retention
Retained per each site's existing CAPA retention policy; the retrieval index is derivative and rebuilt from the register, not a separate record of authority
Access
Corrective Action Board members and investigators across sites; no access outside the CAPA governance group
Source authority
The site-level CAPA register export dated 2026-01-05 is authoritative; the similarity index holds no independent facts about any case
APPENDIX C · AI RISK ASSESSMENT — FILLED
consequence
high — a missed systemic recurrence could leave a safety-relevant torque non-conformity uncorrected across sites
influence
medium — informs whether to escalate to a systemic investigation, not a final disposition
criticality
high — bolted-joint torque on a tower platform is a safety-critical characteristic
sensitivity
low — internal CAPA records only
traceability
medium — clusters link to source CAPA records, but similarity scoring itself is not directly inspectable
propagation
high — the failure mode is already known to recur across sites
volatility
low — the retrieval index is rebuilt on each CAPA register export, not per query
dependency
low — runs on internally held CAPA records, no external provider
CONTROLS AND SAFEGUARDS
Clustering is presented as candidate similarity, never confirmed recurrence. The investigator must independently verify that a retrieved prior case shares the actual failure mechanism, not just similar wording, before treating it as a true match.
RESIDUAL RISK AND ACCEPTANCE
Residual risk of an unsurfaced true match is accepted by the CAPA Board Chair given the tool is additive to, not a replacement for, the investigator's own judgement and existing escalation process.
Result: Level C
APPENDIX D · ONE-PAGE TOOL SPECIFICATION — FILLED
Inputs
Current investigation's symptom description plus the full cross-site CAPA register export
Outputs
Ranked list of candidate prior corrective actions with stated root cause, containment and similarity score
Limits
Similarity is on symptom wording, not confirmed mechanism; cannot itself confirm a true recurrence
Configuration
CAPA register export 2026-01-05, similarity model v1.0
Acceptance
Surfaces at least the same matches a manual cross-site search finds on a 10-case test set
Human review
Investigator independently verifies shared failure mechanism before treating any retrieved case as a true match
APPENDIX E · GOLDEN SET AND EVALUATION REGISTER — FILLED
Known-correct cases
10 known cross-site recurrences with a confirmed shared mechanism, used as the retrieval test set
Hard cases
4 cases with similar symptom wording but a different underlying mechanism, to check the false-lead rate on near-miss wording
Borderline cases
3 cases where the CAPA record's symptom description is sparse, testing retrieval quality on thin source text
No-finding cases
6 investigations with no true prior match anywhere in the register, used to verify the tool does not force a match where none exists
APPENDIX F · QUALIFICATION FILE — FILLED
Intended use and limits
Candidate-match surfacing only; the tool never confirms a recurrence or assigns root cause
Evidence and configuration
CAPA register export 2026-01-05, similarity model v1.0, rebuilt per register export
Evaluation results
On a 10-case test set of known cross-site recurrences, retrieval surfaced 9 of 10 manually-found matches; 3 additional false leads per case on average
Known limitations and controls
False-lead rate is high enough that every surfaced match is explicitly labelled 'candidate — verify mechanism', not 'match'
Approval and monitoring
Approved by P. Adeyemi, 2026-01-22; quarterly re-evaluation as the CAPA register grows
APPENDIX G · PRODUCTION GO-LIVE CHECKLIST — FILLED
Operational controls
Retrieval results appear only inside the investigator's existing CAPA workflow; the tool cannot close or merge any record
User training
Investigators briefed on the 'candidate — verify mechanism' label and the known 9-of-10 recall rate before first live use
Monitoring
Missed true matches later discovered manually are logged and counted against the retrieval recall rate
Incident handling
A missed systemic recurrence found after the fact triggers a review of the similarity model, not just the individual case
APPENDIX H · CHANGE AND REVALIDATION LOG — FILLED
Change
CAPA register export refreshed and similarity index rebuilt to include the latest closed and open cases across all sites
Retested
10-case known-recurrence test set re-run against the rebuilt index to confirm recall has not regressed
Accepted by
P. Adeyemi, Corrective Action Board Chair
Why
The register grows continuously as new CAPAs close; the index must be rebuilt and recall reverified on a known cadence rather than assumed stable
APPENDIX I · SUPPLIER AND THIRD-PARTY AI QUESTIONNAIRE — FILLED
Provider
Internally built retrieval tool operating on internally held CAPA records; no third-party AI provider
Source
Corrective-action records originate from each site's own CAPA system, exported into a shared register
Access
No party outside the CAPA governance group can query the similarity index
Change control
Index rebuilds are logged in the change and revalidation log against each register export date
Incident and evidence responsibilities
Not applicable — no external supplier is involved in this use case
APPENDIX J · ASSESSMENT QUESTIONS AND GLOSSARY — FILLED
Practical question
Would an investigator know to keep searching manually even after the tool returns zero candidates, given it is not proven to have perfect recall?
Practical question
How is a 'candidate — verify mechanism' label distinguished in the UI from a confirmed recurrence, so a rushed investigator cannot mistake one for the other?
Glossary term
False-lead rate — the number of retrieved candidates per case that the investigator's own review does not confirm as a true mechanism match
Glossary term
Recall (retrieval)— the proportion of manually-findable true matches that the tool also surfaces, measured against a known test set