Implementing responsibility boundaries for quality and equipment decisions in manufacturing

Assessment finding

AI-excluded quality and safety decisions are not explicit.

Service B implementation

Create an AI workflow scope list and an AI-excluded decision list.

Assessment finding

Review conditions for quality, safety, and production impact are insufficient.

Service B implementation

Create review condition lists by quality impact, safety impact, and production impact.

Assessment finding

AI-specific review criteria are missing.

Service B implementation

Create an AI judgment review procedure for thresholds, exceptions, and source data checks.

Assessment finding

Differences between AI classifications and final judgments are difficult to analyze.

Service B implementation

Introduce a Decision Log template for AI classification, human judgment, and rationale.

Assessment finding

Boundary review is not triggered by model or threshold changes.

Service B implementation

Define Boundary Governance for model updates, threshold changes, and workflow expansion.

Workflow

AI visual inspection

AI use

Good/defective classification and anomaly scoring

Design focus

Define review triggers and shipment decision ownership by product, process, and threshold.

Workflow

Predictive maintenance

AI use

Anomaly alerts and recommended maintenance actions

Design focus

Separate equipment stop, inspection, parts replacement, and production plan change authority.

Workflow

Defect cause analysis

AI use

Defect summary and cause hypothesis generation

Design focus

Prevent AI hypotheses from being treated as facts in corrective action decisions.

Workflow

Work-standard lookup

AI use

Work-standard and past trouble case search and summarization

Design focus

Require source confirmation and supervisor review for safety-related work.

Deliverable

AI workflow scope and exclusion list

Description

Defines where AI classifications may be used and where quality or safety decisions remain human-only.

Primary users

Quality assurance, production engineering, plant managers

Deliverable

Decision Boundary™ design document

Description

Defines AI role and human judgment across inspection, maintenance, defect analysis, and work-standard lookup.

Primary users

Quality assurance, maintenance, production engineering

Deliverable

Review trigger and threshold list

Description

Defines review conditions by anomaly score, product type, process, quality impact, safety impact, and production impact.

Primary users

Inspectors, line managers, quality assurance owners

Deliverable

AI judgment review procedure

Description

Standardizes source data checks, reinspection conditions, and escalation criteria.

Primary users

Inspectors, maintenance staff, supervisors

Deliverable

Decision Log template

Description

Records AI classification, human judgment, rationale, final decision, and approver.

Primary users

Operations, quality management, audit

Deliverable

Boundary Governance rules

Description

Defines review and approval for model updates, threshold changes, and process changes.

Primary users

AI program owners, quality assurance, production engineering

Phase

1. Kickoff and scope definition

Duration

1 week

Work

Confirm target processes, AI models, inspection standards, and existing procedures.

Output

Implementation scope

Phase

2. Decision type mapping

Duration

1-2 weeks

Work

Classify good/defective judgments, shipment decisions, equipment stops, corrective actions, and process changes.

Output

Decision type inventory

Phase

3. Decision Boundary™ design

Duration

2-3 weeks

Work

Define AI first-pass judgment, human review, human final judgment, and AI-excluded decisions.

Output

Decision Boundary™ design document

Phase

4. Responsibility and review design

Duration

2 weeks

Work

Define review conditions and owners for quality, safety, and production impact.

Output

Review trigger and responsibility matrix

Phase

5. Evidence design

Duration

1-2 weeks

Work

Define log fields for AI classification, reinspection, final judgment, and rationale.

Output

Decision Log template

Phase

6. Governance design

Duration

1 week

Work

Define approval processes for model updates, threshold changes, and product-scope expansion.

Output

Boundary Governance rules

Phase

7. Pilot and adoption

Duration

1-2 weeks

Work

Pilot on target lines and verify operational load and quality impact.

Output

Final deliverables and training materials

Decision type

Final judgment on suspected defects

AI role

Candidate classification only

Review condition

Threshold exceeded, critical product, customer-designated product

Final owner

Quality assurance

Log requirement

Record AI classification, reinspection result, and final judgment

Decision type

Equipment stop decision

AI role

Alert only

Review condition

Safety, quality, or production impact is possible

Final owner

Maintenance and plant management

Log requirement

Record alert, confirmation result, and stop rationale

Decision type

Engineering or process change

AI role

Excluded from final decision

Review condition

Not applicable

Final owner

Engineering and production engineering

Log requirement

If AI hypotheses are referenced, record their reference scope

Before

Reliance on AI good classifications varied by line.

After

Review conditions are defined by product, process, and threshold.

Before

Final judgment on suspected defects depended on individual inspectors.

After

Quality assurance review and escalation conditions are explicit.

Before

Responsibility for AI-triggered equipment stops was unclear.

After

Decision ownership is separated by safety, quality, and production impact.

Before

AI cause hypotheses could blend into corrective action decisions.

After

AI hypotheses remain analysis inputs; humans determine cause and action.

Before

Model and threshold changes did not trigger boundary review.

After

Boundary Governance requires review for model, threshold, or workflow changes.