Industrial Data Visualization
Normalize shop-floor signals into a shared event history and role-based dashboards for operations, maintenance, and management
Our role
We defined the signal model, OPC UA integration, event storage, and role-based interface so scattered control data became a traceable operational product rather than another isolated dashboard.
The Problem
Production sites generate constant machine data, yet insight stays fragmented across PLCs, historians, and informal shift notes. When a stop happens, teams reconstruct events from memory instead of evidence, and the same faults repeat because root causes never become visible.
- Critical signals sit in silos with no common timeline across machines and shifts
- Post-incident analysis depends on whoever was on the floor, not a reliable event record
- Dashboards are either too technical for daily operations or too shallow for improvement work
Why It Matters
Without traceability, improvement stays reactive. Operations loses time guessing, management loses confidence in the numbers, and learning from one shift rarely carries to the next.
- Ability to explain stops with evidence instead of assumptions
- Visibility of recurring fault patterns across shifts and lines
- Alignment between shop-floor reality and management reporting
Our Solution
Event-store architecture capturing alarms, state changes, and selected process values on a searchable common timeline
OPC UA ingestion and normalization layer that maps mixed machine signals into a documented operational data model
Role-appropriate dashboards giving operators a live view while leadership sees the same underlying facts
Signal dictionary with units, context, and naming conventions so data stays interpretable as the system grows
Results
Data exists everywhere but nowhere in a form teams can trust during or after an incident
Unified event history and live dashboards that turn machine behavior into shared operational insight
- Faster troubleshooting because teams can replay what happened instead of debating it
- Fewer repeated stops as patterns become visible across machines and time
- Better cross-functional decisions because operations and management reference the same source
Project context
A manufacturing environment with multiple production cells and mixed control platforms needed a practical way to reconstruct line behavior and support daily decisions. neexo scoped the signals with automation and operations teams, implemented the ingestion and event-recording architecture, and delivered views tailored to operators, maintenance, and leadership.
Deliverables
- OPC UA data capture setup with documented signal mapping
- Flight-recorder event database and search interface
- Role-based live and historical dashboards for operations, maintenance, and management
Related reading
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