Predictive Facility Management System

Core Logic

Continuously scans sensor data from all 37 properties, analyzing temperature, vibration, energy consumption, pressure, and air quality metrics. Calculates equipment health scores (0-100), detects anomalies by comparing current readings against baselines, and generates prioritized alerts. Operates fully autonomously with 85% approval threshold, making 47+ decisions daily with 98.7% success rate.

Core Logic

Applies machine learning pattern recognition to cross-reference current sensor anomalies with 2,847+ historical failure patterns. Uses Weibull failure prediction to estimate time-to-failure windows. Identifies specific root causes (e.g., compressor bearing wear) with confidence scores. Achieved 94.2% prediction accuracy, enabling preventive action before critical failures.

Core Logic

Performs deep-dive root cause analysis by fusing data from multiple sensors, comparing against historical equipment performance, and analyzing maintenance history. Cross-references patterns with documented failure modes and provides specific component-level diagnoses (e.g., 'Carrier 39M compressor bearing wear - 94% match with historical failures').

Core Logic

Evaluates 156+ cost scenarios including preventive maintenance costs, emergency repair costs, parts pricing, labor rates, tenant impact costs, and energy waste from degraded equipment. Calculates cost-benefit analysis of preventive vs. emergency repair approaches. Projects ROI and payback periods for replacement recommendations.

Core Logic

Auto-populates work orders with 47+ fields extracted from diagnostic data including property location, equipment details, issue classification, required expertise, parts needed, estimated duration, and SLA targets. Achieves 98.9% accuracy on generated work orders, significantly reducing administrative overhead and ensuring complete documentation.

Core Logic

Evaluates all available technicians (typically 12+) against work order requirements using skill matching algorithms. Considers HVAC certification levels, proximity to job site, current workload, first-time-fix rates (targeting >95%), and customer ratings. Generates match scores and selects optimal technician (e.g., 'Marcus van der Berg - 98% match score').

Core Logic

Calculates optimal multi-stop routes using A* algorithm with real-time traffic analysis. Considers travel time between properties, job durations, SLA deadlines, and time-of-day traffic patterns. Achieves 35% travel time savings compared to sequential dispatch. Outputs total distance, estimated duration, and optimized stop sequence.

Core Logic

Monitors real-time SLA compliance for all active work orders. Predicts potential delays based on current progress, traffic conditions, and job complexity. Sends proactive alerts when SLA targets are at risk. Achieves 99.1% accuracy on timeline predictions and 100% SLA compliance through early intervention.

Core Logic

Provides real-time monitoring of technician activities including arrival confirmation, work step logging, parts consumption tracking, photo documentation, and sensor reading validation. Logs 34+ activity types with timestamps, enabling accurate job costing and progress visibility for all stakeholders.

Core Logic

Validates completed work against 18+ quality checkpoints including procedure compliance, safety protocols, post-repair sensor readings verification, and before/after metric comparison. Confirms equipment health scores return to normal ranges (target: 95+). Flags any deviations requiring follow-up inspection.

Core Logic

Analyzes work order history across all 37 properties to detect recurring patterns, common failure modes, and systemic issues. Identifies correlations like 'Carrier 39M compressors show bearing wear at 28,000-32,000 operating hours' and recommends preventive replacement schedules. Processes 2,450+ data points to surface cross-property insights.

Core Logic

Automatically orders required parts from preferred vendors based on price comparison, delivery speed, vendor ratings (targeting 4.8+ stars), and sustainability scores. Auto-approves orders under €5,000 when confidence exceeds 95%. Achieved same-day delivery coordination for urgent parts. Tracks vendor performance including response time, completion rate, and SLA compliance.

Core Logic

Auto-generates personalized maintenance notifications using tenant-preferred channels (email, app, SMS). Sends notifications 48+ hours before scheduled work per SLA requirements. Provides estimated duration, expected impact, and completion confirmations. Operates semi-autonomously (92% approval threshold), maintaining 97.1% success rate and reducing complaints by 94%.

Core Logic

Continuously optimizes HVAC, lighting, and other building systems based on real-time occupancy data, weather forecasts, and energy spot prices. Reduces HVAC output by 15% during low occupancy periods. Operates fully autonomously (80% approval threshold), making 156+ decisions daily with 96.8% success rate. Achieves €85/day savings on typical optimization cycles.

Core Logic

Tracks regulatory requirements and deadlines across all compliance categories. Auto-generates required reports (e.g., quarterly F-Gas compliance per EU Regulation 517/2014). Files documentation with regulatory portals automatically. Operates fully autonomously (75% approval threshold) with 99.1% success rate, ensuring zero missed compliance deadlines.

Core Logic

Captures learnings from each completed workflow including diagnostic accuracy validation, prediction model performance, parts usage patterns, and technician efficiency metrics. Updates knowledge base with new failure patterns, optimal intervention timing, and best practices. Improves future prediction accuracy through continuous machine learning model retraining.