Background Story
A leading manufacturing facility specializing in industrial components was experiencing a steady increase in energy costs due to inefficient processes and aging equipment. With long operating hours and high energy demands, the company needed a smarter approach to energy management. Additionally, the company faced increasing pressure from regulatory bodies to report and reduce carbon emissions as part of its commitment to corporate sustainability and environmental compliance.
Problems
The facility lacked real-time visibility into energy consumption across different production lines, making it difficult to pinpoint inefficiencies and optimize usage.
Some key challenges included:- High Energy Costs: Without granular data on energy use, excessive consumption and waste remained unaddressed
- Manual Data Collection: Plant operators relied on spreadsheets and periodic meter readings, leading to delays in decision-making and missed opportunities for optimization
- Unplanned Downtime: Equipment failures due to undetected inefficiencies resulted in costly production delays
- Carbon Reporting Compliance: Meeting government regulations and sustainability commitments required accurate tracking of carbon emissions, which was previously done manually and prone to errors
Main Objective
- The primary goal was to implement a comprehensive digital system that could:
- Provide real-time monitoring of energy consumption at the machine and production line levels
- Enable predictive consumption patterns and improve operational efficiency
- Identify and address inefficiencies to reduce overall energy costs and improve sustainability performance
Approach
To achieve these objectives, the company deployed our arkEMIS and CarbonHUB supermodules, integrated with IoT-enabled smart meters, sensors, and cloud-based analytics. The implementation involved several critical steps:
- Digitalization and Carbon Assessment: Existing digital infrastructure and carbon baseline were assessed to identify data gaps and acquire the necessary sensors for a digitally mature facility
- IoT Sensor Deployment: Smart meters and power quality sensors were strategically installed on major production lines, high-consumption equipment, and HVAC systems to capture real-time energy usage
- Cloud-Based Data Integration: Energy data from sensors was transmitted to a secure, cloud-based platform, allowing facility managers to access detailed consumption patterns and trends
- AI-Driven Analytics and Alerts: Machine learning algorithms analyzed energy patterns, detecting anomalies and predicting equipment failures before they occurred
- Load Balancing and Optimization: The system provided recommendations for optimizing energy distribution, reducing peak demand charges, and shifting loads to off-peak hours where possible
- Automated Carbon Reporting and Compliance: The platform automatically calculated and logged carbon emissions data, generating reports aligned with government and industry sustainability standards
- User Training: Facility operators and energy managers were trained to effectively use the system, interpret data insights, and implement energy-saving measures
Results
Within the first year of implementation, the company achieved substantial improvements in both energy efficiency and operational performance
- 10% Reduction in Energy Costs: By optimizing machine runtimes and eliminating wasted energy
- 30% Faster Response to Anomalies: Real-time alerts enabled proactive maintenance, preventing equipment failures and reducing downtime by 20%
- 12% Reduction in Total Carbon Emissions: Through optimized operational efficiency
- Improved Carbon Footprint Management: Automated tracking and reporting streamlined regulatory compliance, reducing reporting errors and administrative workload