Reference architecture
Production analytics evidence pipeline
A transparent pattern connecting a named operational question to source lineage, data-quality checks, versioned measures, reconciled results and human review.
Evidence baseline
What is represented
- Representative machine events, context records and operational consumer.
- Transparent measure calculation used instead of an opaque performance claim.
- No customer savings, yield, downtime or maintenance result is published.
Constraints
What shaped the engineering model
- Missing and late data must remain distinguishable from zero or normal operation.
- Metric versions and context must be retained with results.
- Correlation and causation require different evidence and claims.
Responsibility boundary
Who owns which decision
Named ownership prevents a technical work package from silently expanding into product, site, safety, quality or release authority.
Responsibility 1
Axiotech: the engineering method, scoped technical artefacts and stated verification evidence.
Responsibility 2
Customer/OEM: intended use, site constraints, acceptance authority and information supplied.
Responsibility 3
Other competent parties: safety, mechanical, process, quality or infrastructure decisions outside the stated scope.
Lifecycle proof
Decision gates used by the evidence model
The case does not equate activity with acceptance. Each gate has authority, inputs, evidence and unresolved-item visibility.
- G0Scope authorityOutcome, boundaries, roles, assumptions and commercial basis agreed.
- G1Baseline acceptedKnown installed/source state, dependencies, constraints and unknowns recorded.
- G2Design approvedRequirements, interfaces, risks and acceptance evidence ready for implementation.
- G3Release candidateBuild reviewed, verified, versioned and accompanied by defect disposition.
- G4Site acceptanceCommissioning evidence, deviations and release decision recorded.
- G5Handover acceptedSource, configuration, records, recovery and residual risks transferred.
Requirement-to-evidence assurance matrix
A compact proof structure
Public result statements remain deliberately bounded. Project-specific values require approved evidence.
| Need / requirement | Design control | Evidence | Public result status |
|---|---|---|---|
| Trusted measure | Versioned calculation | Manual reconciliation set | Method demonstrated |
| Visible data gaps | Quality/exception model | Missing/late/duplicate cases | Test cases defined |
| Owned decision | User/action boundary | Review and escalation scenario | No operational outcome claimed |
Measurable acceptance
What a real engagement would measure
These are acceptance measures, not published customer results.
- Calculated results reconciled to approved source examples
- Data-quality exceptions detected and visible
- Decision users can identify definition, version and limitation
Deliverable manifest
What makes the decision reviewable
- Decision and measure specification
- Source/lineage/data-quality map
- Versioned transformation design
- Reconciliation and edge-case test set
- Monitoring and ownership runbook
Limitations
What this evidence does not establish
- Reference data is not evidence of customer process performance.
- Analytical validity remains bounded by source coverage and intended use.
Residual risk
What still requires ownership
- Source and process drift require monitoring and periodic review.
- Human action and organisational adoption remain outside the analytical calculation.
Apply the method
Start with a bounded assessment or engineering work package.
Project facts, responsibilities and acceptance measures are confirmed before any outcome is promised.