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layered-process-audit-designer

Design and run layered process audits (LPA, AIAG CQI-8, IATF 16949 and OEM requirements such as GM BIQS): layer structure (supervisors daily, managers weekly, plant leadership monthly), short risk-based yes/no question cards drawn from PFMEA, control plan reaction plans, special characteristics and recent complaints, rotation so higher layers see every area, workload per person, on-the-spot correction and escalation. Builds a rotating multi-week LPA calendar with workload from a people list, and analyses LPA results for compliance by area, layer and question, repeat failures that need corrective action, failures not corrected, layer gaps that show weak layer-1 audits, and stale always-pass questions to rotate. Use when setting up an LPA program, writing LPA questions, preparing for an automotive customer audit, or reviewing monthly LPA results.

Manufacturing & Industrial Operations / Quality Management & ISO 9001v1.0.0Updated OCT 25 20262 references2 scripts

LPAs put several layers of management on the floor, checking the same handful of critical controls at different frequencies. They work when questions are short, observable and risk-based, audits actually happen, and failures turn into action. scripts/lpa_plan.py builds the rotation calendar and workload; scripts/lpa_results.py turns results into compliance trends and escalations.

Trigger Conditions

Activate this skill when the user:

  • Is setting up an LPA program or a customer (automotive OEM) requires one
  • Needs LPA questions or a question card for a line
  • Wants an LPA schedule with rotation across areas and layers
  • Has LPA results and needs to know what to act on

Workflow

text
1. LAYERS    -> who audits at layer 1 (daily), 2 (weekly), 3 (monthly); areas in scope
2. QUESTIONS -> 5-15 observable yes/no questions from complaints, special characteristics, PFMEA, reaction plans
3. CARD      -> each question with a "look for" line or photo of the correct state
4. PLAN      -> python scripts/lpa_plan.py --people people.csv --weeks 4 --questions 10
5. RUN       -> fix on the spot when possible; record action, owner, date when not
6. ANALYSE   -> python scripts/lpa_results.py results.csv   (monthly)
7. IMPROVE   -> CAPA for repeats, coach layer 1 on gaps, rotate stale questions

Layers

LayerWhoFrequency
1Supervisors / team leaders, own areaEvery shift or day
2Managers and engineers, rotatingWeekly
3Plant leadership, rotatingMonthly

All layers use the same card. Design rules, metrics (completion >= 95%, open actions, layer gap) and rollout: lpa-system-design.md. Weak vs strong questions, sources and card format: question-writing.md.

Results Analysis (lpa_results.py)

CodeSeverityMeaningAction
LR001highSame question fails repeatedly in one areaOpen a corrective action (5 Why / 8D)
LR002mediumFailure not corrected on the spot, no follow-upRecord action, owner, date
LR003mediumLayer 1 compliance >= 15 points above higher layersCoach layer 1; review "look for" lines
LR004lowQuestion passed every timeRotate in a question on a current risk
text
LR001 [high] Q2 failed 5 times in Weld - systemic: open a corrective action
LR003 [medium] Press: layer 1 finds 100% compliance, higher layers 80% - coach layer 1 on what to check

Output Format

Deliver:

  1. Program design - layers, people, areas, frequency, audit length.
  2. Question card - numbered questions with "look for" and source (complaint, PFMEA line, control plan step).
  3. Calendar - rotation table and workload per person (from lpa_plan.py).
  4. Results review - compliance by area/layer/question, escalations and question changes (from lpa_results.py).

Scripts

bash
python scripts/lpa_plan.py --people people.csv --weeks 4
python scripts/lpa_plan.py --people people.csv --weeks 8 --questions 12 --minutes-per-question 1.5 --days 6

People CSV: name, layer (1/2/3), area (home area; required for layer 1). Layer 2/3 auditors get the least-visited area each week, without doubling up, home area last. Exit codes: 0 plan, 1 an area has no layer-1 auditor, 2 read error.

bash
python scripts/lpa_results.py results.csv
python scripts/lpa_results.py results.csv --repeat 3 --stale 20

Results CSV: date, layer, area, auditor, question_id, question, result (pass/fail/na), corrected. Exit codes: 0 no high findings, 1 repeat failures found, 2 read error.

Additional Resources

FileContent
lpa-system-design.mdLayers and frequency, design rules, metrics, rollout
question-writing.mdWeak vs strong questions, question sources, card format
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