Make All Operation More Sustainable-In Real Time
PETRAN unifies AI, IoT, and workflows to cut energy use and emissions, conserve water, reduce waste, and prove results, site by site, line by line
What Ombrulla Mean by Operational Sustainability
Operational sustainability turns everyday production decisions into measurable environmental improvements without compromising throughput, quality, or safety. Using AI + IoT, Ombrulla captures real‑time data across utilities, processes, and assets, then predicts, prescribes, and automates actions that lower kWh, m³, and tons of CO₂e, while sustaining operational performance.
Business Benefits
Lower Operating Cost
Reduce energy, water, and materials spend with continuous optimization and automated setpoint control.
Verified Emissions & ESG
Automate GHG accounting and audit-ready evidence for internal and external reporting.
Resilient Operations
Detect anomalies early, prevent wasteful downtime, and maintain quality during demand or pricing shocks.
Scalable Governance
Standardize policies and KPIs across plants; replicate best practices in weeks, not quarters.
What We Monitor From Energy and Emissions to Process and Asset Health
PETRAN gives you a single, trusted view across energy and utilities (electricity, steam, gas, compressed air, chilled/hot water, renewables), emissions and carbon (combustion data with CO₂e factors, optional fugitive/flaring), water and effluents (intake, process, cooling, discharge with conductivity/temperature), and end-to-end process & asset health (temperature, pressure, flow, speed, torque, quality, vibration, power quality, loading, start/stop) so you can pinpoint losses, prove compliance, and act before issues become downtime.
Operational Benefits
Energy & Utilities
Monitor electricity, steam, gas, air, water, and renewables to identify losses and load profiles.
Emissions & Carbon
Capture combustion and activity data, calculate CO₂e using regional factors, and include fugitive and flaring emissions.
Water & Effluents
Track water intake, process & discharge with conductivity and temperature to optimize cycles and ensure compliance.
Process & Asset Health
Measure temp, flow, pressure, speed, torque & quality with vibration, power & load data to detect faults.
Core Capabilities-Where AI, IoT, and Action Converge
Unify real-time telemetry with AI-driven anomaly detection, optimization, and closed-loop workflows to cut energy, water, and carbon while lifting yield and uptime. PETRAN ingests plant data at scale, spots inefficiencies before they become losses, automates corrective actions, and streamlines ESG reporting all through open, secure integrations with your historians, control systems, and enterprise apps.
Real-Time Telemetry
Continuously ingest meters, sensors, and PLC signals (energy, utilities, process variables) for time-aligned visibility across assets.
AI Anomaly Detection
Detect leaks, steam-trap failures, drift, fouling, compressed-air losses, and suboptimal cycles with evidence-backed alerts.
Optimization & Control (MPC)
Apply advanced control to hit target throughput while minimizing kWh, m³, and CO₂e per unit.
Energy & Water Management
Run ISO 50001-aligned baselines, targets, and M&V to verify savings and sustain improvements.
Waste & Yield Intelligence
Correlate scrap and rework with process conditions and asset health to pinpoint root causes and reduce losses.
Carbon & ESG Reporting
Calculate Scope 1–2 (with integrations for Scope 3) and auto-assemble GHG-aligned evidence packs for disclosures.
Event-to-Action Workflows
Drive every alert to root cause, corrective action, and verification with closed-loop tracking.
Open, Secure Integrations
Connect historians, BMS/SCADA, LIMS, EAM/CMMS, ERP, and data warehouses with enterprise-grade RBAC/SSO, audit trails, encryption, and cloud/on-prem/VPC options.
Why Ombrulla
One Source of Truth for Operations
A unified data fabric merges production, utilities, and asset health into a single model, enabling faster decisions and cross-functional accountability.
Edge + Cloud AI for Results Now and at Scale
Sub-second detection at the site keeps lines running, while fleet-level learning in the cloud compounds gains across plants.
Open by Design, No Lock-In
Standards-based integrations plug into your existing systems, protect prior investments, and keep switching costs under control.
Enterprise-Grade Trust & Adoption
Human-centered UX drives operator and engineer buy-in, backed by governance, RBAC/SSO, audit trails, and encryption that satisfy enterprise requirements.
KPIs & Proof of Impact
Energy & Carbon Intensity
Well-run programs typically reduce site energy use and CO₂e per unit by ~10–15% within the first 12–18 months, normalized for weather, utilization, and product mix.
Reliability & Downtime
Predictive maintenance and condition-based workflows commonly cut ~30–36% of unplanned downtime, lifting throughput and OEE without major capex.
Utilities (Air & Water)
Systematic leak management and tower optimization often save 20–30% of compressed-air load and trim cooling-tower make-up by ~40% with blowdown reductions near ~50%.
Waste & Verified Savings
Mature diversion programs reach ~90% landfill avoidance, with savings validated via measurement & verification baselines and operational normalization.
Use Cases by Domain
Modern manufacturing aims to run safer, leaner, and greener maximizing throughput while minimizing energy, waste, and unplanned downtime.
Predictive Maintenance for Zero Unplanned Downtime
- AI-driven condition monitoring predicts equipment failures early, allowing planned interventions that reduce breakdowns, scrap, and energy spikes.
Energy-Optimized Production Scheduling
- Production plans are automatically adjusted to align high-load processes with off-peak tariffs and renewable availability, cutting both cost and carbon.
Real-Time Workforce & Safety Monitoring
- RTLS-based employee tracking and worker monitoring software ensure workers stay clear of high-risk zones while optimizing staffing in bottleneck areas.
Closed-Loop Quality & Scrap Reduction
- Machine vision and IoT data detect defects in real time and feed insights back to process settings, steadily reducing rework and material waste.