CASE 003 / APPLIED INTELLIGENCE

ENERGY OPTIMIZATION · CERAMICS MANUFACTURING

ONE PROBLEM, DECODED.

Energy waste,
made visible.

A real-time system that detects abnormal energy use and recommends operating settings that bring the process back within its desired range.

TWELVE MONTHS · MULTIPLE PRODUCTION LINES · ONE FACTORY
OBSERVED
+15%
DESIRED
SET

DETECT THE GAP / CORRECT THE SETTING

The setpoint is not
the process.

Ceramics manufacturing is energy intensive, with natural gas accounting for a substantial part of operating cost. Small inefficiencies can persist unnoticed across equipment and production lines.

The relevant signal lives in the difference between intended settings and observed behavior. During certain periods, those discrepancies produced materially higher energy consumption.

Detect the gap. Recommend the setting.

Detection alone was not enough. The system also had to identify a better operating point without violating production constraints.

We combined temperature, pressure, energy consumption, and controllable set parameters from individual equipment across multiple lines.

The deployed models identify abnormal energy behavior, infer the settings required to return consumption to its desired range, and surface both the anomaly and recommendation through a real-time operational view.

MODEL INPUTS
  • Temperature
  • Pressure
  • Energy consumption
  • Controllable set parameters
  1. 01

    Observe

    Connect equipment-level process and consumption data.

  2. 02

    Compare

    Measure the gap between desired parameters and actual behavior.

  3. 03

    Recommend

    Find corrective settings within the operation's constraints.

  4. 04

    Integrate

    Deliver anomalies and setpoint guidance in real time.

Less energy. Same operating reality.

OBSERVED

15%

excess energy identified

up to this level during anomalous periods
PROJECTED

5%

lower energy use

expected overall reduction under live validation
DEPLOYED

LIVE

decision support

anomaly detection and setpoint guidance

The system turns energy efficiency from a retrospective report into an operational decision: detect the excess, identify the cause, and recommend the next setting.

What looks fixed
may only be familiar.

Bring us the problem