Beyond X for Smart Factory

FEMS (Factory Energy Management System)

Factory energy management solution that monitors, analyzes, and controls based on IT+OT technology to optimize energy supply and demand at manufacturing sites.

Solution

FEMS (Factory Energy Management System)

Power/Energy Management

We are facing complex energy challenges such as continuously rising power/energy unit costs, difficulties in introducing energy-efficient equipment, and increasing carbon border tax (CBAM) burden.

Continuous Increase in Power/Energy Unit Price

Increased manufacturing costs due to higher operating expenses in energy-intensive processes

Difficulties in Introducing Energy-Efficient Equipment

Difficulty in improving equipment with high initial investment costs
Lack of optimization in daily manufacturing operations

Limitations of Energy Usage Monitoring

Limitations of simple energy data measurement and collection systems in achieving meaningful efficiency improvements

Burden of Carbon Border Tax (CBAM)

Need for measures to ease the burden of mandatory carbon emissions reporting and carbon taxes

Key Features

Optimizing energy production in line with process load variability (eliminating over-supply/off-operation) and minimizing system waste.

Energy Usage in Manufacturing Plants

Energy Consumption Structure Map
Production Planning + Local Shift

Energy Demand (Per Unit)

Optimizing Supply Volume to Meet Energy Demand

Energy Production (Utilities)

Voltage
Stabilization

Power (Transformer)
Load
Balance

Compressed Air (Air Compressor)
Proportional
Control

Steam (Boiler)
Coefficient of Performance Optimization

Chilled Water (Refrigerator)

Real-Time Collection of Large-Scale Equipment Data

Real-time calculation of per unit metrics
Alerts for deviations from standard metrics

Insights through Visualization of Equipment Data

Multivariable control of high-consumption processes (MPC)
Process equipment recipe optimization (Golden Run)

PLC and Standard Protocol Support

Configuration of energy-greenhouse gas inventory
Automatic calculation of greenhouse gas by process

Core Technologies

Features optimal control guidance for manufacturing equipment through energy consumption per unit forecasts, efficiency assessments, real-time monitoring, and energy waste tracking.

Real-time Data Integration & Storage

Realtime Data (4M + 2E + Manufacturing Production + Energy + Environment)

Energy Normalization Establishment of Rational Standards such as Energy Per Unit

Setting energy unit and baseline standards, and forecasting consumption
Energy efficiency assessment and benchmarking comparison

Energy Tracking Data Analysis-Based Waste Cause Tracking

Real-time monitoring and anomaly alerts
Energy target/performance management, ESG management, and carbon emissions control

Energy Optimization Optimal/Autonomous Control of Energy Efficiency

Optimal control of utility equipment and process manufacturing equipment
Operational guidance

Expected Benefits

Elimination of Idle Operation and Overconsumption

Prevent unnecessary equipment operation and energy waste through real-time energy monitoring

Process Energy Reduction

Optimize energy consumption by analyzing energy usage per process and improving low-efficiency areas

Production Yield/Quality Improvement through Optimal Process Control

Enhanced productivity and quality by maintaining stable operational conditions with energy efficiency-based equipment control

Continuous Improvement Initiatives Based on Energy Data

Support for analyzing energy consumption history and trends to derive sustainable improvement strategies and implementation tasks

References

Starch/Processed Food Manufacturing Process

Requirements

Standard energy management system
Performance management through production monitoring

Key Achievements

Standard energy management system
Utilities monitoring (compressed air, refrigeration, etc.) and per unit management function for each product

Automated General Assembly Process

Requirements

Energy management system in the manufacturing area
Energy management framework for production processes

Key Achievements

Quantitative data management of energy performance indicators
Per product per unit management and energy demand forecasting using baselines