The bottom line: When OEE data is delayed, slow production can run for hours before anyone acts. ProAlert pushes live OEE every 10 seconds so supervisors can intervene while there is still time to recover the shift. At RHA Manufacturing, a Toyota Tier 1 automotive supplier, this approach drove OEE from 65% to 89% over 39 months, delivering $800K+ in annual value on a $3,500 investment.

Why Most OEE Programs Fall Short

Traditional OEE programs share a structural flaw: the data arrives after the window to act has closed.

End-of-shift data is historical, not actionable.

A machine running at 40% Performance for three hours generates a report entry after the fact. By shift end, the loss is permanent and cannot be recovered.
Spreadsheet OEE depends on manual data collection.

When operators fill in downtime logs from memory, data is rounded, delayed, or skipped entirely. The resulting OEE number is a best guess dressed as a metric.
Disconnected systems produce disconnected OEE.

When your downtime tracker, cycle counter, and scrap log live in separate systems, calculating true OEE requires manual stitching that introduces error at every seam.
Die-driven environments are poorly served.

Standard OEE software sets targets at the machine level. In metal stamping and injection molding, the active tooling determines cycle time and cavity output. The machine number alone tells you nothing meaningful about expected production.

How ProAlert Calculates OEE

ProAlert's OEE engine draws from a unified database that also drives Andon alerts, cycle counting, and scrap entry. Every input is live and automatic.

Availability CORE

Calculated directly from active Downtime (DT) calls. The moment a DT call opens, Availability begins falling. When the call closes, it recovers. No manual entry required at any step.

Performance PREMIUM

Actual cycle counts vs. expected cycles per hour. Data flows from EdgeSense IoT (Internet of Things) devices via GPIO (General Purpose Input/Output) sensors, or from manual production entry.

Quality PREMIUM

Good parts divided by total parts produced. Scrap entries feed the Quality component automatically from the same interface operators use to log rejects. No duplicate entry.

Composite OEE

OEE = (Availability × Performance × Quality) / 10,000. Calculated continuously and broadcast to every connected client every 10 seconds. Live, not cached.

Subscription-Gated Tiers: Availability is always included. Performance and Quality are subscription-gated with per-asset expiration date tracking. Assets without active subscriptions do not consume server resources calculating metrics they cannot display. The system stays efficient at scale.

10-Second Live Broadcasting

ProAlert's background OEE service queries all active assets, calculates metrics with the appropriate tier flags enabled, and pushes updates to every connected client on a 10-second cycle. This is a live calculation, not a cached snapshot refreshed on page load.

Broadcast Target	Content	How It Works
Asset Dashboard	Availability, Performance, Quality, Composite OEE	Pushed to the `asset:{assetId}` SignalR group. Any client subscribed to that asset receives the update instantly.
Mobile App	Live OEE tile with target vs. actual display	The .NET MAUI (Multi-platform App UI) mobile app receives the same SignalR push. Greyed tiles indicate unsubscribed tiers.
Andon HUD (Heads-Up Display)	Live asset status with OEE overlay	Shop floor Andon display updates automatically when each 10-second OEE broadcast arrives.
Support Users (Multi-Plant)	All-asset OEE stream	Users subscribed to the global group receive OEE data for every asset across all facilities simultaneously.

Die-Driven OEE Resolution

In metal stamping and injection molding, production targets must follow the active tooling, not the machine. ProAlert resolves OEE parameters automatically from the die or tool selected at run start.

Cavity-Level Cycle Attribution

A 4-cavity die produces 4 parts per press stroke. ProAlert attributes output by cavity count, not as single units. Your Performance metric reflects actual throughput, not raw stroke count.
Per-Cycle Output (PCO) Threshold Resolution

Performance targets seed from the die's PCO configuration. Change the die at the press, and the OEE target updates automatically. No supervisor intervention required to maintain accurate metrics.
OEE Baseline Snapshots

A ProductAssetStatsHistory snapshot captures the OEE state at product selection. Post-shift trend analysis starts from a documented baseline, not a reconstructed estimate.

Automated Anomaly Detection

ProAlert surfaces performance problems before a DT call is ever placed. Three automated detection conditions alert supervisors while there is still time to act.

Condition	Trigger	Why It Matters
Slow Production	Rolling average cycle time exceeds the configured threshold	A machine running 15% below target rate produces fewer parts per hour without ever triggering a Downtime call. Slow Production surfaces the loss before it compounds.
Production Lull	No cycle activity detected beyond the configured gap period	An idle machine that should be running shows as Running status. Lull detection surfaces the gap before a full shift of lost production accumulates invisibly.
Production Warning	Cycles detected on an asset marked Down or Planned	Highest-priority alert state. A machine running while marked Down means the official record and physical reality are out of sync. This condition requires immediate supervisor attention.

Proven Results: RHA Manufacturing

RHA Manufacturing, a Toyota Tier 1 automotive supplier. Results tracked across 39 months (January 2023 through March 2026) and 21,346 production runs:

Sustained OEE

89%

65% baseline → 89% sustained (39 months)

Scrap Reduction

-65%

8,945 scrap parts (2023) → 309 parts (Q1 2026 pace)

Quality Rate

99.8%

up from 98.79% in 2023; Q1 2026: 99.78%

Annual Value

$800K+

estimated annual value on $3,500/year: 23,000%+ ROI

How RHA achieved this: The management team exports OEE data every morning and reviews it before the shift starts. Downtime events, scrap incidents, and production gaps are correlated to find root causes. Action items are assigned and resolved that same day. The improvement was not instant... it took 8 to 12 months to see the breakthrough. But it was sustained, and RHA subsequently deployed ProAlert to their Mexico manufacturing facility.

How ProAlert Compares

Typical OEE Tools (Vorne XL, Parsec TrakSYS)

OEE only — no maintenance management included
$5,000–$20,000 per line per year plus hardware
Separate CMMS required: additional $6,000–$15,000/year
Integration between OEE and CMMS: $50,000–$200,000
No video evidence capability

ProAlert

OEE, Andon, CMMS (Computerized Maintenance Management), and Video in one platform
Availability always included; Performance and Quality subscription-gated per asset
EdgeSense IoT device for cycle counting at approximately $500 per unit
No integration cost: single shared database
Proven: 65% to 89% OEE over 39 months at a Tier 1 automotive supplier

For IT and Systems Teams

ProAlert's OEE engine runs on standard, supportable technology with no proprietary middleware dependencies.

Component	Technology	Notes
Real-Time Delivery	SignalR WebSockets (ASP.NET Core 9)	Broadcasts to asset-specific groups every 10 seconds. Falls back to long-polling on restricted networks automatically.
Data Storage	SQL Server + Entity Framework Core	All OEE data in a normalized relational schema. Standard SQL Server backup and disaster recovery applies.
Cycle Counting Input	EdgeSense IoT (Raspberry Pi) or REST API (Representational State Transfer)	Cycles submitted via GPIO sensor on the EdgeSense device, or via the Production REST endpoint for ERP (Enterprise Resource Planning) system integration.
OEE Data Access	60+ REST endpoints	Live OEE snapshots and historical data available for Business Intelligence (BI) and ERP integration. JWT (JSON Web Token) bearer authentication on all endpoints.
Deployment Options	On-premises, LAN-based (recommended)	Windows Server and SQL Server on your plant's local network. Cloud-hosted deployments are available on request for facilities with specific requirements.

See live OEE on your machines.

Book a 30-minute demo... we'll walk through your specific production floor challenges and show you what real-time OEE looks like in practice.

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