Internal Quality Audit

Internal Quality Audit Program (manufacturing-quality/as9100/internal-quality-audit)

Use when the task is planning and scoring an internal quality audit program under an AS9100-style quality management system: scheduling audits by process risk, checking auditor independence and competence for the assigned scope, sampling records, categorizing findings, and verifying closure of corrective action responses. This leaf implements the audit program mechanics in pure Python, stdlib only, with no randomness. It pairs with manufacturing-quality/as9100/quality, which maps audit focus areas to AS9100 clauses and shapes the auditor evidence plan, and with manufacturing-quality/as9100/corrective-action, which owns the corrective action response record. AS9100 is referenced, not reproduced; the model below is the leaf audit program methodology.

Domain quick reference

• Audit interval: base_interval_months (12.0 default) times the risk multiplier, RISK_MULTIPLIERS = {low: 1.5, medium: 1.0, high: 0.5}. High risk processes are audited more often, so the interval is shorter. The due date is the last audit date plus that span in calendar months with the day clamped to the target month end, so a high risk audit 6 months after 2026-03-15 is due 2026-09-15.
• Auditor independence: the auditor must not be the area owner, and no conflict may be declared for the assignment.
• Auditor competence: every required area must appear in the auditor qualification list (case insensitive substring match).
• Record sampling: n = ceil(sqrt(lot_size) * factor), factor 1.0 at 0.95 confidence, 1.2 at 0.99, 0.8 at 0.90, interpolated between the anchors, at least 1 record.
• Finding ladder: impact severity 4-5 or containment required gives a major nonconformity; severity 2-3 gives minor, and systemic spread escalates minor to major; severity 1 is an opportunity for improvement.
• Closure verdict: the corrective action response closes the finding only when the corrective action taken, the root cause statement and the effectiveness check are all present.
• Confidence bounds: lot sizes below 1, confidence outside [0.5, 0.999] and severity outside 1-5 are rejected with ValueError.

Workflow

1. Schedule the audit: audit_due_date(last_audit_date_iso, risk_category, base_interval_months) returns the due date ISO string, with the risk multiplier shortening high risk intervals.
2. Check the assignment: auditor_independent(auditor_name, area_owner_name, independence_ok) returns {independent, reason}.
3. Check the qualifications: auditor_competent(qualifications, audit_scope_areas, required_areas) is True when every required area is covered by the qualification list.
4. Size the sample: audit_sample_size(lot_size, confidence_level) returns the number of records to pull from the lot.
5. Categorize each finding: classify_finding(impact_severity, containment_required, systemic) returns major, minor or ofi.
6. Verify the response: verify_closure(corrective_action_taken, root_cause_stated, effectiveness_check) gates the finding closed.
7. Chain the whole review: internal_audit_review(...) returns the schedule, interval, independence and competence verdicts, sample size, finding category and closure verdict in one dict.
8. Confirm the deterministic checks with the contract test scripts/test_internal_quality_audit.py.

Worked example

Last audit 2026-03-15 on a high risk process (multiplier 0.5 gives a 6 month interval), 400 records at 95% confidence, auditor A. Chen against area owner B. Lopez, required areas [calibration, corrective action] with matching qualifications, impact severity 3 with containment required and no systemic spread. Running the module prints:

• due_date "2026-09-15" (6.0 calendar months, the about-2026-09-15 bound holds).
• interval_months 6.0.
• auditor_independent True (auditor differs from the owner, no conflict).
• auditor_competent True (both required areas are qualified).
• sample_size 20 (ceil(sqrt(400)) = 20 at 0.95, inside the 15-25 bound).
• finding_classification "major" (containment required escalates).
• closure_verified True (all three response elements are set).

Verification

• audit_due_date clamps month ends: 2026-01-31 plus 1 month gives 2026-02-28, and 2024-01-31 gives 2024-02-29 in the leap year.
• Malformed dates, unknown risk categories, empty required area lists, lot sizes below 1, confidence outside [0.5, 0.999] and impact severity outside 1-5 all raise ValueError.
• auditor_independent is False when the auditor name matches the owner name (case insensitive) or when a conflict is declared.
• audit_sample_size(400) is 20 at 0.95, 24 at 0.99 and 16 at 0.90.
• classify_finding: severity 5 or containment required gives major; severity 2-3 systemic gives major; severity 2-3 alone gives minor; severity 1 gives ofi.
• verify_closure is False when any of the three elements is missing.
• Determinism: no RNG anywhere, run-to-run identical output.
• Run the contract test offline: python3 scripts/test_internal_quality_audit.py (30 tests, deterministic).

Related leaves

• manufacturing-quality/as9100/quality: maps audit focus areas to AS9100 clauses and shapes the evidence plan for each focus area.
• manufacturing-quality/as9100/corrective-action: owns the corrective action response record that this leaf gates on closure.
• manufacturing-quality/as9100/calibration-control: the calibration records an audit may sample.
• manufacturing-quality/as9100/nonconformance-control: disposition of product records an audit finds nonconforming.
• manufacturing-quality/as9100/supplier-control: external provider audits belong to supplier control, not to this internal audit leaf.

Pitfalls

• Assigning the area owner as the auditor: independence fails when the auditor name matches the owner name (case insensitive) or when any conflict is declared, whatever the competence record says.
• Scheduling from the base interval alone: the risk multiplier shortens the interval (high risk 0.5, medium 1.0, low 1.5), and the due date clamps to the target month end - 2026-01-31 plus 1 month is 2026-02-28 (2024-02-29 in the leap year), not March.
• Sizing the sample with sqrt(lot) at every confidence level: the factor is interpolated between the anchors (0.8 at 0.90, 1.0 at 0.95, 1.2 at 0.99), so 400 records sample 20, 16 or 24 records depending on the confidence stated.
• Scoring severity without the escalators: containment required makes any finding major, systemic spread escalates a minor (severity 2-3) to major, and severity 1 is an opportunity for improvement - not a minor finding.
• Closing a finding on the response's existence alone: closure requires the corrective action taken, the root cause statement and the effectiveness check all present; any missing element leaves the finding open.
• Ignoring the audit program's determinism: this leaf uses no randomness anywhere, so any run-to-run variation in schedule, sample size or verdict is a caller bug, not audit sampling noise - and malformed dates, unknown risk categories, lot sizes below 1, confidence outside [0.5, 0.999] and severity outside 1-5 are all rejected with ValueError.

Behavior contract (gate 3)

Run the deterministic contract test (stdlib unittest, offline):

python3 scripts/test_internal_quality_audit.py

The test covers risk-based scheduling with month end clamping, the independence rule including declared conflicts, competence against the required areas, the sample size formula at the confidence anchors, the finding ladder with systemic and containment escalation, closure verification, the worked example outputs inside the spec magnitude bounds, exact result keys, ValueError rejection of every non-physical input, and run-to-run determinism.

Compliance

• Standards referenced, not reproduced: AS9100 is a commercial SAE standard; the audit program equations above are the leaf audit program methodology, summary-only per standards-map.yaml.
• compliance: STANDARDS-REF, gated: false.