EC.DATA — Energy Intelligence Platform

Factory & Industrial Energy Intelligence — Line Metering & Compressed Air | EC.DATA

Factory & Industrial Energy Intelligence — Production Line Monitoring

EC.DATA monitors production line energy, compressed air systems, motors, and HVAC across manufacturing plants — identifying idle-running equipment, demand charge peaks, and maintenance indicators before they become outages.

Industrial Energy Challenges

  • Energy-intensive machinery and process loads with poor sub-metering visibility
  • Compressed air leaks wasting 20–30% of compressor energy
  • Motors and VFDs running at full speed regardless of production load
  • Demand charge spikes from simultaneous machine startups at shift change
  • No correlation between production output and energy cost per unit
  • Fragmented maintenance data: equipment faults discovered after failure

EC.DATA Factory Solutions

  • Machine and line-level sub-metering via Modbus-connected CTs (EC.EMS)
  • Compressed air pressure trend monitoring for leak detection (EC.IoT — EC.PQ correlation)
  • Demand charge optimization: staggered startup sequencing and peak alerts
  • Power quality monitoring for VFD-generated harmonics (EC.PQ — IEEE 519)
  • Motor current trending for bearing fault early warning (EC.GAIA)
  • Energy cost per unit of production KPI dashboards

Manufacturing: turning energy data into production cost clarity

Most factories know their total electricity bill but cannot answer which line, machine, or shift is responsible. EC.DATA places CT-based Modbus meters on every production line feeder and compressed air circuit, then correlates energy consumption with shift schedules and production counts. A line that uses 30% more kWh per unit than its twin on the same floor is immediately visible — usually explained by a failed power factor correction bank, a VFD running at 100% speed when 70% would do, or a compressor cycling against a partially blocked discharge valve.

The demand charge optimization alone typically saves 8–15% of the electricity bill in plants with multiple large motors, by alerting operators before peak demand is set for the month and suggesting startup staggering during shift changeovers.