When sampling is (and is not) appropriate
| Use sampling | Do not rely on sampling |
|---|---|
| Incoming inspection of purchased lots | Safety / critical characteristics (CC): use 100% automatic inspection or error-proofing |
| Testing is destructive or expensive | Process making the lots is unstable: fix the process |
| Large volumes with good supplier history | Customer requires zero defects and c = 0 plans are not enough |
| Audit of outgoing product | As a substitute for process control (SPC) |
Picking the AQL
AQL is the worst process average you will tolerate as acceptable; it is not a promise that each lot is that good. Common practice by defect class:
| Defect class | Typical AQL |
|---|---|
| Critical (safety) | 0 accepted: 100% / error-proofing, or c = 0 with high n |
| Major (function, fit) | 0.65-1.0% |
| Minor (cosmetic, non-functional) | 2.5-4.0% |
Use the customer's AQLs when specified. Classify each characteristic and pick a plan per class.
Reading the OC curve
| Point | Meaning |
|---|---|
| p at Pa 0.95 | Quality the producer can expect to pass 95% of the time (producer's risk alpha = 5%) |
| p at Pa 0.10 | LTPD: quality the consumer will accept only 10% of the time (consumer's risk beta = 10%) |
| AOQL | With rejected lots 100% sorted, the worst long-run average outgoing quality |
Example (n = 80, c = 2, lot 1000): accepts 1.0% lots 95% of the time, still accepts 6.3% lots 10% of the time; AOQL about 1.6%. If 6% nonconforming lots are unacceptable, this plan does not protect you.
Designing from risks
State the producer's point (AQL, alpha) and the consumer's point (LTPD, beta) and solve for n and c
(oc_curve.py design). Example: AQL 1%, alpha 5%, LTPD 5%, beta 10% -> n = 132, c = 3.
c = 0 plans
Accept only with zero nonconforming units in the sample. Sample size for LTPD p at consumer risk beta: n = ln(beta) / ln(1 - p) (about 2.3 / p at beta 10%). They reject good lots more often than Z1.4 plans at the same LTPD, so producers need a process far better than the LTPD.
Executing the plan
- Draw the sample at random from the whole lot (all boxes, layers, cavities), not from the top.
- Define what counts as nonconforming with limit samples and a calibrated gauge.
- Record lot, plan, sample, results and decision; apply switching rules over lot history.
- A rejected lot is not "re-sampled until it passes": sort it 100% or return it.
8d-problem-solving-report-writer
Write and review 8D problem-solving reports for customer complaints and serious nonconformities (automotive and aerospace practice: Ford Global 8D, VDA, GM, Stellantis formats): D0 emergency response, D1 cross-functional team and champion, D2 problem description with 5W2H and is / is-not and no cause in the statement, D3 interim containment within 24 hours with verification and clean point, D4 verified occurrence and escape (non-detection) root causes plus systemic cause, D5 permanent corrective actions for each cause verified before implementation, D6 implementation, validation with production data and removal of containment, D7 PFMEA, control plan and read-across to similar products, D8 closure and recognition. Checks an 8D discipline by discipline for missing content, human-error root causes, missing escape cause or action, late containment and dates out of order.
approved-supplier-list-manager
Manage and audit an approved supplier list (ASL) / external provider register for ISO 9001 8.4.1, IATF 16949 8.4 and AS9100 8.4.1: supplier status (approved, conditional, probation, pending, disqualified), scope of approval by commodity and process, risk class, certification and expiry, re-evaluation intervals by risk, conditions with end dates, single-source contingency, approver and customer-directed sources. Audits the list for expired or expiring certificates, overdue re-evaluations, conditional or probation status past its decision date, high-risk suppliers without the required certification, single-source suppliers without backup and missing approvers, and checks purchase orders for suppliers that are off-list, disqualified or pending, or buying outside the approved scope. Covers ERP blocks, PO requirements, off-list and emergency purchases.
apqp-phase-planner
Plan and track Advanced Product Quality Planning (AIAG APQP 3rd edition, IATF 16949) for a new or changed automotive part: back-schedule the five phases (plan and define, product design, process design, product and process validation, launch and feedback) from the start-of-production date by program complexity, with overlap, PPAP lead and safe-launch period; list the deliverables and gate for each phase (DFMEA, DVP&R, feasibility, process flow, PFMEA, control plans, MSA, Ppk, run at rate, PPAP, safe launch, lessons learned); adjust for build-to-print suppliers; flag compressed timelines and late or untracked deliverables against a status list. Covers gate reviews, red/yellow/green status reporting, run at rate and safe-launch exit criteria.
as9100-gap-analyzer
Run an AS9100D / EN 9100:2018 gap analysis for aviation, space and defence suppliers on the requirements added to ISO 9001: on-time delivery and conformity focus, management representative, ethics and human-factors awareness, operational planning and operational risk management, configuration management, product safety, counterfeit-part prevention, special requirements, critical items and key characteristics, external provider register and flow-down, FOD prevention, tooling and NC program control, special process validation, first article inspection (AS9102), traceability, in-service data and nonconforming product control. Generates and scores a worksheet, grades missing core controls as major, and checks invalid n/a claims. Covers AS9101/AS9104, OASIS, AS9102 FAI forms, counterfeit standards (AS5553, AS6174, AS6081), NADCAP and the planned IA9100 transition.
audit-report-writer
Write internal, supplier and pre-certification audit reports with the content ISO 19011:2018 6.5 expects: audit objectives, scope, criteria with revisions, dates, team and auditees, method and sampling statement, specific strengths, findings table and three-part finding details (requirement, evidence, statement), conclusion on the degree of fulfilment of criteria, diverging opinions, follow-up deadlines and distribution. Builds a Markdown report from a JSON audit record, generates the conclusion from the findings (major / minor / none) and flags reports missing required content or findings without clause or evidence. Covers conclusion wording, closing meetings, response expectations and verifying corrective actions.
capa-effectiveness-checker
Verify whether a corrective action actually worked (ISO 9001 10.2.1 d, IATF 16949, 8D D6) with statistics instead of 'no complaints so far': before/after defect-rate comparison with an exact conditional binomial test for Poisson counts and a minimum practical reduction, zero-defect demonstration size (n = ln(1-C)/ln(1-p), rule of three) with progress so far, and exact Clopper-Pearson upper bounds on the post-action defect rate. Returns effective, not yet demonstrated (with the units still needed) or not effective. Covers setting effectiveness criteria when the CAPA is opened, choosing the window by problem frequency, leading indicators for rare failures (Cpk, SPC stability, error-proofing checks, LPA), and traps such as volume changes, detection changes and containment masking.