Production Intelligence

Real-time OEE. Every asset.
Every shift. Every second.

Live visibility into production performance. Detect anomalies in 30 seconds, not 8 hours later. OEE, utilization, bottlenecks — all visible in real time.

Real-time

OEE Tracking

Every second

100%

Asset Visibility

No blind spots

30 sec

Alert Speed

Problem detection

7-15%

Shift Variance

Typically found

Six Types of Intelligence

The data you've been missing.

Most plants measure production at day-end. By then, the opportunity to act is gone. We deliver intelligence in real time.

Live OEE Dashboard

Every machine's OEE updated every 10 seconds. Overall line OEE, machine OEE, shift OEE. See where you stand against baseline and world-class 85%.

Real impact:

Your line supervisor watches: Shift starts at OEE 78%. By 10am it drops to 72%. They have the data on what changed. They investigate now, not waiting for day-end reports.

Asset Utilization Heatmap

Which machines run which products. Which are bottlenecks. Which sit idle. Color-coded in real time: red=constraint, yellow=warning, green=running well.

Real impact:

Your production manager sees Machine A is the constraint 40% of the time. They also see Line B runs with 3 available machines idle 30% of the day. They rebalance work.

Shift Benchmarking

OEE by shift, every day. Shift A does 82%. Shift B does 73%. Same equipment, same product. Why the 9% gap? Data shows you.

Real impact:

Your shift leaders compare: Shift A starts machine checks 15 minutes before shift start. Shift B doesn't. Leaders standardize pre-shift checks across all shifts. Gap drops to 2%.

Bottleneck Detection

Automatically identifies which machine constrains line throughput. Cycle time analysis reveals Machine X holds back the whole line by 8%.

Real impact:

Your engineers see they've been optimizing all machines equally. Data reveals 80% of improvement potential lives in one machine. They focus there.

Throughput Optimization

Real-time throughput trending. Are we hitting target? If not, why? Which loss (downtime, speed, quality) is costing us most?

Real impact:

Your supervisors see throughput target is 500 units/day, current is 465. Loss breakdown shows 20 units lost to downtime, 15 to speed variance. They fix those two gaps.

Anomaly Alerts

Micro-stops increase 15%? Cycle time drifts 8%? Quality rate drops below 98%? You're alerted in 30 seconds, not 8 hours later.

Real impact:

Your operators are alerted at 2:15pm. Root cause is identified by 2:45pm. Fix is implemented by 3:00pm. Cascading losses are prevented for the rest of the shift.

What You Track

A complete production view.

OEE (%)

Current, target, world-class, shift vs shift

Availability

Uptime %, downtime category, MTTR, MTBF

Performance

Speed loss %, cycle time variance, throughput vs target

Quality

Defect rate, first-pass yield, defect by cause

Energy

kWh per unit, energy cost per shift, idle waste

Throughput

Units/hour, daily total, efficiency vs baseline

A single minute of real-time intelligence.

2:15 PM

OEE Alert: Down 8%

Speed loss detected on Machine A. Cycle time increased from 4.2 to 4.6 minutes.

2:18 PM

Root Cause Found

Correlation analysis: Speed loss correlates with Material Batch #R4521 + Shift B. Only happens on this combination.

2:22 PM

Action Taken

Supervisor swaps material batch. Speed returns to 4.2 min. OEE recovers. 10 units saved from being outside tolerance.

The 30-second decision advantage.

Without Real-time Data

  • • Problem occurs at 2:15 PM
  • • Discovered at 10:30 PM shift-end review
  • • Root cause analysis delays solution to next day
  • • Lost production for 20+ hours
  • • Pattern repeats next week

With Real-time Intelligence

  • • Problem occurs at 2:15 PM
  • • Alert at 2:16 PM
  • • Root cause found by 2:18 PM
  • • Action taken by 2:22 PM
  • • Lost production: 7 minutes

Get real-time visibility into production.

Know what's happening as it happens. Detect problems in 30 seconds. Act before they cascade.

Enable Real-time Intelligence →