7 min read
OT/IT convergence without a flat network: zones, conduits, and the mistakes IT teams make.
OT Security · Architecture
_industries / Manufacturing: OT/IT
The line can't stop. We've modernized the systems running it without ever pulling the plug.
iFlux modernizes the systems running your plant floor: the control software nobody wants to touch, the maintenance models that cry wolf, the shop-floor and back-office systems that never quite agree. We reverse-engineer what the existing systems actually do, including the undocumented behavior operators rely on, then build and validate replacements before any cutover — so the line keeps running while we work.
// from PLCs and SCADA to MES and ERP.
// from predictive maintenance to full-unit traceability.
// from the plant floor to the cloud — securely.
We know where industrial systems break, because we've fixed them mid-shift.
Tell us about your manufacturing challenge →// from predictive maintenance to full-unit traceability.
// from the plant floor to the cloud — securely.
We know where industrial systems break, because we've fixed them mid-shift.
OT/IT ConvergenceMESSCADAERP IntegrationPredictive MaintenanceIndustrial IoTQuality SystemsTraceability
_problems we've actually solved
// legacy modernizationsystems of record
The 20-year-old system running the line that nobody wants to touch
The control system at the center of your operation was written before half your engineers were hired, and the risk of changing it feels higher than the cost of keeping it. We start by understanding what the old system was actually doing — the undocumented behavior, the workarounds the operators depend on — before we build something better that does all of it too.
// OT/IT convergencefloor to cloud
Connecting the factory floor to the cloud without opening it to attack
The pressure to get plant data into the cloud runs straight into the reality that your PLCs (programmable logic controllers) and SCADA (supervisory control and data acquisition) network were never designed to be exposed. We bridge OT and IT (operational technology and information technology) with segmented architectures, one-way data diodes where they matter, and IEC 62443 zones and conduits — so you get the visibility without turning the shop floor into an attack surface.
// predictive maintenanceplant-floor ML
Models that earn the maintenance team's trust, not just the demo's
A failure-prediction model that cries wolf gets ignored by the third false alarm. We build predictive maintenance that quantifies its own uncertainty, explains why it flagged a bearing, and proves out against real downtime events before anyone is asked to pull a machine off the line on its say-so.
// MES / ERPshop floor to back office
The shop floor and the back office that never quite agree
When the MES (manufacturing execution system) says one thing and the ERP says another, someone spends their morning reconciling spreadsheets instead of running the plant. We build the integration layer that keeps work orders, inventory, and production counts consistent across systems in real time — with the ISA-95 mapping that makes the boundary between them explicit.
// downtimeobservability
Observability where a minute of downtime costs thousands
In most software, a slow dashboard is an annoyance. On a production line, the gap between a fault happening and someone seeing it is measured in dollars per second. We instrument for the failure you haven't had yet — real-time alerting, root-cause context, and the historian data that turns a recurring stoppage into a fix.
// traceabilitygenealogy & recall
Traceability that answers the recall question in minutes, not weeks
When a quality issue surfaces, the question is always the same: which units, which lot, which supplier, which shift. We build genealogy and traceability systems that can reconstruct the full history of any unit on demand — the difference between a targeted recall and shutting down a product line while you guess.
On a production line, the edge case has a dollar figure. It's the fault that hits at 2am on the third shift, when the one person who understood the old system retired last spring.
// we plan for it before we touch the controller.
// not after the stoppage report.
_the standards
layer// we know the
// difference
// between IT
// security and
// OT safety.
layer// we know the
// difference
// between IT
// security and
// OT safety.
ISA-95
The model for integrating enterprise and control systems. We use it to make the boundary between MES and ERP explicit, not accidental.
IEC 62443
Industrial security zones and conduits. OT/IT convergence built on a segmented architecture, not a flat network with hope on top.
ISO 9001
Quality management systems that hold up to audit. Traceability and process controls engineered in, not documented after the fact.
NIST CSF
Cybersecurity framework alignment for the IT side of the plant, mapped to the OT controls that keep production safe.
FDA 21 CFR Part 11
For regulated manufacturing: electronic records and signatures, audit trails, and validation that survives an inspection.
ITAR / EAR
Export-controlled data handling for defense and aerospace production. Access boundaries and data residency built to the regulation.
_what a manufacturing audit looks like
iflux: plant_system_audit.sh
~/iflux/Industries/Manufacturing $ audit --scope=plant --ot-it=true --assumptions=false
→ Scanning OT/IT network topology...
⚠ SCADA network flat-routed to corporate LAN. No 62443 segmentation.
⚠ PLC firmware endpoints reachable from IT subnet. Attack surface exposed.
→ Reconciling MES against ERP...
⚠ Production counts drift 4.2% between MES and ERP. Manual reconciliation daily.
⚠ No ISA-95 mapping. System boundary undefined, integration ad hoc.
→ Reviewing predictive maintenance pipeline...
⚠ Model false-positive rate 31%. Maintenance team ignoring alerts.
→ Checking traceability coverage...
✗ Unit genealogy incomplete. Recall scope cannot be reconstructed below lot level.
→ Measuring downtime detection latency...
⚠ Fault-to-alert latency: 6.4 min average. Revenue loss window unmonitored.
✓ Historian data intact. 3 years of sensor history available for modeling.
✓ Audit complete. 7 issues found. 1 critical traceability gap flagged.
→ Priority fix list generated. Downtime-cost impact estimated per issue.
~/iflux/Industries/Manufacturing $ _
_what we've built on the plant floor
✓
MES / ERP integration layers keeping work orders, inventory, and production counts consistent in real time
✓
OT/IT convergence architectures with IEC 62443 zoning and segmented plant-to-cloud data flow
✓
Predictive maintenance systems with uncertainty quantification and explainable failure alerts
✓
Industrial IoT pipelines ingesting PLC, SCADA, and sensor data at plant scale
✓
Quality & traceability systems with full unit genealogy and recall-ready lot tracking
✓
Real-time downtime observability with root-cause context and historian integration
✓
Legacy control-system modernization that preserves undocumented behavior operators depend on
✓
Production analytics platforms turning OEE (overall equipment effectiveness), yield, and scrap data into decisions
_services we bring to Manufacturing
Every manufacturing engagement is backed by the full iFlux capability stack, matched to the reality of your plant floor and the systems already running it.
_frequently asked
Can you modernize a legacy control system without disrupting production?
Yes. We start by reverse-engineering what the existing system actually does, including the undocumented behavior and operator workarounds, then build and validate the replacement in parallel before any cutover. The line keeps running while we prove the new system matches the old one behavior for behavior.
How do you connect factory-floor equipment to the cloud securely?
We use IEC 62443 zones and conduits to segment OT from IT, expose plant data through controlled boundaries rather than a flat network, and apply one-way data flows where the OT side must never be reachable. You get cloud visibility without turning your PLCs and SCADA network into an attack surface.
Do your predictive maintenance models actually reduce downtime?
They do when the maintenance team trusts them, which is what we engineer for. Our models quantify their own uncertainty, explain why they flagged a machine, and are validated against real historical downtime events before anyone acts on them, so alerts drive action instead of alarm fatigue.
Which manufacturing standards do you build to?
ISA-95 for MES/ERP integration, IEC 62443 for OT security, ISO 9001 for quality systems, and NIST CSF for IT-side cybersecurity. For regulated production we also build to FDA 21 CFR Part 11, and for defense and aerospace we handle ITAR/EAR export-controlled data.
Can you integrate our MES and ERP so they stop disagreeing?
That is one of the most common engagements we take. We build a real-time integration layer with an explicit ISA-95 mapping so work orders, inventory, and production counts stay consistent across systems, ending the daily spreadsheet reconciliation between the shop floor and the back office.
_thinking / Manufacturing
8 min read
Your predictive maintenance model is right 70% of the time. That's exactly why maintenance stopped trusting it.
Predictive Maintenance · ML
8 min read
Modernizing a 20-year-old line control system without stopping the line.
Legacy · Manufacturing
Modernizing what keeps the line running?
Talk to a Flux who's done it mid-shift.
// no rip-and-replace fantasies.
// no team that learns your process after the outage.
// just an honest conversation with someone
// who already knows what a stoppage costs.