Industrial Intelligence Platform

Where Factory Data
Meets Precision
Engineering

Altiora Dynamics builds industrial monitoring systems, real-time data pipelines, and operator dashboards — turning raw process signals into operational clarity.

PLANT STATE SIMULATOR — LINE 3 INTERACTIVE
Status
OPERATIONAL
Latency
12ms
OEE
87.4%
Press Speed — Bimodal Detection RUN
0 CPM1,842 CPM2,400 CPM

Drag the slider or toggle plant state — this mirrors the actual bimodal clustering and alarm-pipeline logic running on deployed systems.

Engineering
Standards
<14ms
Telemetry latency, tag read to UI
42%
Unlogged downtime reduction*
<15s
Dashboard refresh cadence
Zero
Proprietary client lock-in
What We Build

End-to-End Industrial Intelligence

From Raspberry Pi GPIO pulse counters to Ignition WebDev APIs to wall-mounted operator dashboards — we engineer the full stack.

01
Edge Data Collection

Hardware-level signal acquisition using Raspberry Pi, GPIO pulse counting, bimodal cluster analysis for speed detection, and robust serial/network I/O.

02
🔗
Ignition Integration

Deep Ignition SCADA integration via WebDev endpoints, tag historian queries, and real-time OPC-UA bridging to modern web UIs.

03
📊
Operator Dashboards

Production-grade NiceGUI and Streamlit dashboards built for factory floors — touchscreen-optimized, auto-refreshing, with TV wall display scaling.

04
🏭
OEE Monitoring

Real-time Overall Equipment Effectiveness tracking across availability, performance, and quality — with shift-by-shift trend analysis and offline detection.

05
🌡️
Utilities Monitoring

Continuous tracking of boilers, air and steam pressure systems, plant health scoring, and multi-utility anomaly detection for proactive maintenance.

06
📐
Custom Analytics

Bespoke quantitative models for production intelligence — including regime detection, bimodal speed clustering, and predictive quality scoring.

Signal Path Architecture Explorer

Click a node to see the protocol, latency budget, and code for that layer. Ignition serves as the historian, OPC gateway, and API layer throughout.

🎛️
PLC / Field Sensors
Allen-Bradley · Siemens · Modbus TCP
📟
Raspberry Pi Edge
GPIO · RS-232/485
🔗
Ignition WebDev API
Auth JSON bridge
📊
Custom Web UI
NiceGUI · Streamlit
Proof of Work

Case Study: Multi-Line Plastics Manufacturing Plant

Client details generalized to protect confidentiality — no proprietary source or client-specific data is shown.

Industry: Plastics / Thermoform & Extrusion Facility: Multi-line production, Southeast US Engagement: Embedded plant engineering + dashboard buildout
The Situation

Line-level performance was tracked manually at shift change. OEE existed only as an end-of-shift number, utilities were monitored by walking the floor, and unplanned stops were reported by operators after the fact rather than detected automatically.

Technical Constraints

Ignition SCADA already held the tag data, but no operator-facing layer existed outside the native Ignition client. Any kiosk deployment needed to survive factory-floor conditions — dust, vibration, non-technical operators — without a proprietary client on every touchscreen.

Full-Stack Architecture
  • Raspberry Pi kiosks with GPIO pulse counting for press speed
  • Bimodal cluster analysis for automatic RUN / IDLE classification
  • Ignition WebDev REST bridge exposing tag historian data as authenticated JSON
  • NiceGUI dashboard rendered via iframe srcdoc injection to eliminate Quasar CSS scoping conflicts and refresh flicker
Quantified Outcomes*
  • Manual walk-through cadence (30–60 min) → automated refresh under 15 seconds
  • End-of-shift OEE reporting → real-time, line-level, wall-mounted
  • Operator-reported stops → automatic bimodal-state alarm within seconds
<15s
Automated refresh vs. 30–60 min manual walk-throughs
Real-Time
Line-level OEE vs. end-of-shift reporting
Seconds
To automatic stop-detection vs. operator-reported

*Directional figures based on deployed-system behavior; not yet independently audited for this specific engagement.

Before — Manual, Delayed
Shift Log — Line 3
07:00Startup OK
09:15Speed ~ok?
11:30Down 20min (unlogged)
14:00OEE — calc EOD
"Boiler seemed a little hot around noon — didn't write down temp." — handwritten note, actual shift log
After — Real-Time, Automated
Line 3 — Shift A● LIVE
87.4%
Overall Equipment Effectiveness
Whiteboard + walk-throughsDrag to compareLive wall dashboard
Entry Engagement

Know exactly where your plant is blind — in 30 days.

A fixed-scope audit of your current signal chain — from PLC to operator — that identifies unlogged downtime, latency gaps, and quick-win visibility fixes. No commitment beyond the audit.

🗺️
Signal-Path Map
A full map of your current SCADA/historian setup, Ignition or otherwise.
📉
Visibility Gap Report
Quantified breakdown of where you rely on manual logs vs. automated capture.
📋
Prioritized Recommendations
3–5 scoped fixes with rough effort and impact sizing — no vague roadmaps.
🖥️
Live Proof-of-Concept
A working dashboard walkthrough built from your actual, sanitized tag structure.
Format: Remote + optional 1-day on-site Fee: Fixed scope, quoted up front Deliverable: Written report + live demo
Apply for an Edge Data Audit
The Team

Engineering Depth Meets Operational Reality

Altiora Dynamics was founded on a simple premise: industrial data is only valuable when it reaches the right people, in the right format, at the right time.

We bring a rare combination of materials science, software engineering, and hands-on factory floor experience. Every system we build has been tested against real production environments — not just proof-of-concept labs.

From Raspberry Pi hardware integration to Ignition SCADA architecture to pixel-perfect operator dashboards, we own the full stack — faster iterations, fewer integration gaps, and solutions that work when the line goes down at 2am.

🎓
Georgia Institute of Technology
Materials Science & Engineering
🏭
Manufacturing Operations Experience
Industrial monitoring systems deployed in active production plants
📡
Full-Stack Industrial IoT
Hardware → SCADA → Dashboard → Analytics
Technology Stack
Hover a badge for how we use it. Click to jump there.
Python
NiceGUI
Streamlit
Ignition
OPC-UA
Raspberry Pi
GPIO
Plotly
FastAPI
PostgreSQL
WebDev API
Modbus TCP
Field Notes

Engineering Lab

Short, specific write-ups on real decisions from real deployments — not tutorials, postmortems.

NiceGUI · CSS
Why We Render NiceGUI Dashboards Inside an iframe srcdoc
What Quasar CSS scoping breaks on a plant-floor TV wall, and the injection pattern that fixes refresh flicker for good.
Coming soon
Signal Processing
Bimodal Clustering for Run/Idle Detection
A simpler alternative to threshold alarms for classifying machine state from noisy GPIO pulse data.
Coming soon
Ignition · REST
Designing an Ignition WebDev REST Bridge
Auth options, polling-interval tuning, and historian query patterns for exposing tag data as JSON.
Coming soon
Let's Build

Ready to Instrument
Your Plant?

Whether you need a single dashboard, a full Ignition integration, or an edge data collection system from scratch — let's talk about what's possible.

Schedule a Live Demo

A short, no-pitch walkthrough of a live dashboard on real (sanitized) tag data. Bring a rough sense of your PLC/SCADA setup.

View Capabilities
Ready to see it running on your tag data? Schedule Live Demo