Fault Detection and Diagnostics
Real-time equipment monitoring: continuously monitors equipment performance in real-time, detecting any anomalies that may indicate a problem.
Equipment and system diagnosis: provides detailed information about the underlying causes of the issue and potential solutions.
Alerts and notifications: sends notifications to facility managers, maintenance teams, or other relevant personnel when issues arise.
Historical trend analysis: uses historical data to identify patterns and trends that may indicate potential equipment or system failures in the future.
Integration with Building Management Systems (BMS): integrates with BMS systems to automatically detect and diagnose faults in building systems, including HVAC, lighting, and electrical systems.
Service Management
Work order management: creates and tracks work orders for maintenance activities, including equipment repairs, preventive maintenance, and asset management.
Service request management: streamlines the process for submitting and managing service requests.
Asset management: tracks and manages all assets in the facility, including equipment, tools, and vehicles.
Inventory management: manages inventory levels of spare parts and supplies required for maintenance activities.
Contractor management: tracks the performance and service history of contractors and vendors, ensuring timely and effective maintenance.
Prescriptive Recommendations
Energy efficiency analysis: uses data analytics to analyze energy consumption patterns and identify potential areas for improvement.
Cost-benefit analysis: provides cost-benefit analysis for each potential improvement, helping facility managers to prioritize investments based on ROI.
Actionable recommendations: provides clear, actionable recommendations to improve energy efficiency and reduce operating costs.
Measurement and Verification (M&V): provides ongoing measurement and verification of energy savings to ensure the effectiveness of implemented improvements.
Predictive Maintenance
Equipment failure prediction: uses historical data to predict when equipment is likely to fail and proactively schedules maintenance to avoid downtime.
Asset lifecycle management: tracks the lifecycle of assets, predicting when they will need maintenance, repairs, or replacement.
Condition-based maintenance: uses sensors and other monitoring technologies to track the condition of equipment and trigger maintenance activities based on real-time data.
Work order automation: automates the creation and assignment of work orders for maintenance activities, reducing administrative workload for maintenance teams.