Solution / Digital Manufacturing

AI Technical Monitoring & OEE

Real-time equipment condition, performance scoring and OEE analytics linked to asset context and incidents.

Business context

What this capability solves

AI Technical Monitoring & OEE addresses fragmented operational data, delayed decisions and manual intervention by converting field, equipment and enterprise-system signals into governed, measurable operating workflows.

EBP Integra delivery principle

Technology is implemented as an operating capability: architecture, integration, governance, assurance, people, procedures and measurable outcomes are designed together.

Deep-dive capabilities

Capability model

Modular building blocks allow the scope to start with a focused pilot and expand into an enterprise operating model.

Asset Telemetry

Connect machine, sensor and control-system telemetry into a normalized asset model.

Condition Analytics

Detect deviations, trends and abnormal operating states.

OEE

Measure availability, performance and quality with configurable formulas.

Asset Scoring

Combine condition, incident frequency, criticality and production impact.

Alerting

Generate threshold, rule and analytics-driven alerts with escalation.

AI Analysis

Use natural-language and analytical assistants to investigate performance.

Reference architecture

How the capability fits together

Final topology, control placement and deployment model are validated during discovery and detailed design.

Physical / OT Layer

Machines, sensors, PLC/SCADA, cameras, vehicles, field devices and operational assets.

Connectivity & Edge

Industrial protocols, gateways, private wireless/wired networks, edge processing and secure data transport.

Digital Platform

Normalized asset model, digital twin, event/incident logic, analytics, AI and business rules.

Operations & Enterprise

Dashboards, mobile workflows, command center, ERP/MES/WMS/CMMS/ITSM integration and management reporting.

Controls & governance

OT/IT segmentation and least-privilege integration
Asset ownership and data-quality controls
Safety and human override for operational actions
Audit trail for alerts, recommendations and operator decisions
Resilient/offline behavior for critical operations
Cybersecurity and change control for edge/OT components

Priority use cases

Production bottleneck visibility
Equipment health monitoring
OEE loss analysis
Critical asset prioritization

Key deliverables

Current-state process and data assessment
Reference architecture and integration map
Configured pilot/use-case design
Operational dashboards and alert logic
SOP, escalation and RACI
Acceptance/KPI baseline and scale roadmap

Integration considerations

PLC/SCADA
MES
CMMS
Historian
ERP
IoT gateways

Implementation

Phased delivery

Each phase ends with evidence, acceptance criteria and a decision gate before broader scale-out.

1. DiscoverMap assets, process, data, pain points and existing systems.

2. ConnectIntegrate selected telemetry, applications and edge/network components.

3. OptimizeConfigure digital twin, analytics, AI, incidents and operator workflows.

4. ScaleExpand sites/assets, automate integration and institutionalize KPIs.

Outcome and KPI framework

OEE improvementUnplanned downtimeAlert precisionAsset coverageMTTR