Glossary
Industrial DX terms without the fog.
Short definitions for the concepts that shape Digital Transformation and Industry 4.0 architecture.
Digital TransformationThe movement from Industry 3.0 operating patterns toward Industry 4.0 operating patterns. In manufacturing, it changes how the organization sees, learns, decides, and improves.Deep dive →
Industry 4.0Connected assets, contextualized data, interoperability, and adaptive operations. It is an operating pattern, not a product category.Deep dive →
Industry 5.0The European Commission's framing for the next phase: Industry 4.0 foundations redirected toward human-centricity, resilience, and sustainability.Deep dive →
Digital PlatformThe technical foundation of DX: connect and collect; contextualize and normalize; expose and share the now; expose and share the past.Deep dive →
UNSUnified Namespace: a governed, event-driven information space where systems publish and consume contextualized industrial data.Deep dive →
MTRMinimum Technical Requirements: Edge Driven, Report by Exception, Open Architecture, and Lightweight.Deep dive →
Data ContextualizationAttaching meaning to raw signals — asset, hierarchy, units, quality, operating state — so people and software can interpret them without tribal knowledge.Deep dive →
MOMManufacturing Operations Management: the Level 3 capability family for production, quality, maintenance, inventory, scheduling, execution, performance, and genealogy.
MESManufacturing Execution System. MES products can implement parts of MOM, but MES is not the whole Digital Platform.
ISA-95 / IEC 62264A useful framework for manufacturing operations and enterprise-control system integration. It supports architecture language; it does not replace business value or platform design.Deep dive →
Purdue ModelA reference model used for current-state understanding and security segmentation. It should not become a target point-to-point integration architecture.
MQTTA lightweight publish-subscribe protocol often used for event-driven industrial data movement.Deep dive →
SparkplugAn MQTT-oriented specification that adds industrial payload, state, and birth/death behavior for operational data.Deep dive →
OPC UAAn industrial interoperability standard used for structured access to automation data and models.Deep dive →
HistorianA time-series system that stores industrial process data for trends, analysis, reporting, and operational evidence.
Industrial DataOpsThe practice of connecting, modeling, transforming, governing, and serving industrial data so it becomes useful to people, systems, analytics, and AI.
Industrial AIAI applied to industrial decisions and workflows. It depends on contextualized, governed, accessible data plus oversight and safety controls.Deep dive →
OEEOverall Equipment Effectiveness: availability multiplied by performance multiplied by quality, reported as the loss breakdown behind it rather than as a bare percentage.Deep dive →
Alarm rationalizationThe ISA-18.2 lifecycle stage where every alarm is justified, re-specified or removed, each surviving alarm carrying a documented cause, consequence, response and priority.Deep dive →
Shift handoverThe controlled transfer of the operating picture and its responsibility between crews: face to face, two-way, supported by a written record rather than replaced by one.Deep dive →
Predictive maintenanceEstimating when a named failure mode will develop on a specific asset. It needs a measurable precursor, sampling matched to the physics, and a labelled failure history.Deep dive →
Root cause analysisA structured investigation from an event back to the conditions that allowed it, stopping only at a cause the evidence supports and the organisation can control.Deep dive →
P-F intervalThe time between the point at which a failure becomes detectable and the point at which the asset stops doing its job. It sets how often detection has to happen to be useful.Deep dive →