Factory Intelligence Layer
Move from classic industrial systems toan MQTT-based intelligent data layer.
We connect your PLC, SCADA, MES, and ERP landscape to one real-time event backbone without replacing the systems that already run the factory. Stops, quality risks, energy cost, and production decisions become visible in seconds.
MQTT-Based UNSOne event backbone
ERP, MES, PLCs, robots, and cameras can share the same secure data layer.
Brownfield ReadyNo rip-and-replace
The layer is added above existing control, SCADA, and business systems.
Edge AIDecisions near the machine
Critical vision, quality, and production decisions can run at the edge.
Pilot-FirstStart with one machine
Once the event flow works, it can scale across lines and plants.
Does This Feel Familiar?
The data exists. The factory still cannot decide in real time.
When ERP, MES, SCADA, PLCs, cameras, and spreadsheets describe the same factory differently, the management view becomes a delayed copy of reality.
01
Data is everywhere, truth is not
ERP, MES, SCADA, and spreadsheets disagree. Teams spend time debating which number is real.
02
The plan lags behind the line
When a machine stops, the plan still looks alive. Delivery, shift, and capacity decisions arrive late.
03
Quality issues surface too late
By the time a defect is detected, hundreds of parts may already be produced.
04
People become the decision layer
Planning, maintenance, quality, and purchasing wait for manual interpretation before action happens.
How It Works
Sense -> Contextualize -> Decide -> Act -> Learn
Offram turns physical events from the floor into business context, evaluates them with decision rules and AI agents, and triggers action across machines and workflows.
Sense
Floor reality
Machine, PLC, robot, camera, sensor, test, and energy signals are captured.
Context
Business context
Events are tied to product, order, recipe, quality rule, operator, and cost.
Decide
Decision layer
Risk, cost, delivery, and quality impact are evaluated on the same event.
Act
Autonomous action
Robots, PLCs, operator screens, messages, ERP, and MES workflows can be triggered.
Learn
Feedback
Results become data that improves maintenance, quality, and planning decisions.
Unified Namespace
From classic industrial systems to one real-time event backbone.
Point-to-point integrations become fragile as they grow. Offram adds an MQTT-based Unified Namespace above existing PLC, SCADA, MES, and ERP systems without forcing a rip-and-replace project.
ERPMESQualityMaintenanceAI AgentsDashboards
Event backbone through an MQTT broker
PLC / SCADA / Robot / CameraFloor events and machine signals
MQTT Broker / Secure BridgePublish-subscribe flow under TLS/SSL
Unified NamespaceThe contextual event source for the factory
ERP / MES / AI / DashboardSystems consuming the same event at the same time
Single Source
Everyone sees the same event
Stop, quality, or energy events reach maintenance, quality, ERP, MES, and dashboards with the same meaning.
Event-Driven
No waiting for reports
When a value changes, an event is published. Systems listen instead of pulling stale data.
Brownfield
Existing systems stay useful
PLC, SCADA, SQL, OPC UA, Modbus, API, and file sources can be connected in a controlled way.
Secure
Encrypted data movement
Authentication, topic-level access, and secure bridge design are scoped to the project.
Store-Forward
Resilient to connection loss
Critical events can buffer at the edge and synchronize when connectivity returns.
AI Ready
AI receives context
Agents process events with product, order, quality, and operational context instead of raw signals.
AI Agents & Edge Execution
Do not just monitor. Build the decision layer.
The V7 direction positions Offram not as another dashboard, but as a modular execution layer that carries action between maintenance, quality, planning, and business systems.
Maintenance
Predictive Maintenance Agent
Vibration, temperature, cycle, and stop behavior make maintenance risk visible earlier.
Quality
Quality Agent
Camera, test, and process data create a faster response path for escaping quality issues.
Scheduling
Scheduling Agent
Stops, energy cost, and delivery priority can feed production sequence decisions.
Edge AI
Decisions near the machine
Vision and critical production decisions can run locally instead of waiting on the cloud.
ERP/MES
ERP and MES experience the event
Serial, lot, test, calibration, order, and maintenance events connect to real-time flow.
Execution
Action orchestration
Robots, PLCs, operator screens, messages, and workflows can be triggered from one event.
From the Field
Architecture shaped by real factory contexts.
This proof layer describes the operating contexts behind Offram without turning them into public case-study claims. Final copy should use only approved examples.
Automotive and LPG
Test, assembly, and ERP records
Events across valve blocks, fitting assembly, vehicle software, test result, and production record flows.
Meters and valves
Serial and lot traceability
Production data connecting calibration, quality result, product identity, and line behavior.
Wood processing
3D camera and edge analytics
Log positioning, yield optimization, and decision functions near the machine.
Robotic production
Action orchestration
Robotic workflows across laser cutting, welding, spot welding, feeding, and oven lines.
Autonomous Factory
The difference between a traditional factory and the Offram layer.
The goal is not to tear out the large systems. It is to add a secure, real-time, event-driven decision layer above them.
Capability
Traditional setup
With Offram
Data Flow
Point-to-point integration, files, spreadsheets, and delayed reports.
MQTT-based Unified Namespace and one event backbone.
Security
Scattered connections, unclear permissions, and traffic that is hard to audit.
Encrypted messaging, authentication, and topic-level access design.
Decision
People inspect, interpret, and act.
Rules and AI evaluate risk and can trigger the action path.
Quality
Defects are analyzed after the fact.
Camera, test, and process data create a real-time response path.
ERP/MES
Late records and missing floor data.
Real-time production events, serial, lot, test, and calibration records.
Connection Loss
Lost data, manual correction, and later cleanup.
Edge buffering, store-forward, and retransmission design.
First Step
Start with one machine. Grow toward a factory-wide UNS.
The first step should be small but architecturally correct: turn the most visible loss point into a pilot with secure messaging, edge decisioning, and ERP/MES event flow.
1. Architecture Review
Where does the data layer break?
We map where PLC, SCADA, ERP/MES, spreadsheets, and operator flows are late, missing, or unsafe.
2. MQTT / UNS Pilot
Connect one line to a secure backbone
Events from the selected machine enter an encrypted MQTT flow, gain context, and update ERP/MES.
3. Autonomous Scaling
If it works, scale it
AI agents, Edge AI, store-forward movement, and new machines join the same UNS architecture in a controlled way.