O&M Optimization

AI-powered operations and maintenance optimization for solar assets using the OODA loop methodology.

Overview

O&M optimization transforms reactive maintenance into proactive, data-driven operations. Using the OODA (Observe-Orient-Decide-Act) loop methodology, Ona Terminal provides comprehensive solar asset management that maximizes uptime, minimizes costs, and protects revenue.

The OODA Loop Methodology

🔍 Observe Phase - Fault Detection

Real-time monitoring and fault detection with energy production forecasting integration:

# Run fault detection on new telemetry data
ona ooda detect run --asset "inverter-001" --data "latest_telemetry.csv"

Enhanced Capabilities:

Physical Sensor Analysis: Monitor temperature, voltage, power, and other critical parameters
Forecast Integration: Compare actual power output with forecasted values
Anomaly Detection: Identify deviations that may indicate performance issues
Real-Time Alerts: Instant notification of potential problems

🎯 Orient Phase - Diagnostics

Advanced diagnostics with Energy-at-Risk (EAR) calculations:

# Run comprehensive diagnostics
ona ooda diagnose run --asset "inverter-001" --horizon "7d"

Diagnostic Features:

Fault Categorization: Group issues by type and severity
Energy Production Analysis: Detect anomalies in power output
Forecast Deviation Analysis: Compare actual vs. forecasted performance
Degradation Detection: Identify long-term performance trends
Risk Assessment: Calculate Energy-at-Risk over multiple time horizons

🧠 Decide Phase - Risk Assessment & Scheduling

Optimized maintenance scheduling with financial impact analysis:

# Calculate Energy-at-Risk with forecast integration
ona ooda ear calc --asset "inverter-001" --confidence "95%"

Decision Support:

Risk Quantification: Precise financial impact calculations
Forecast Accuracy Integration: Factor in forecast confidence levels
Maintenance Optimization: Schedule maintenance to minimize revenue impact
Resource Planning: Optimize staffing and parts availability
Cost-Benefit Analysis: Compare maintenance costs vs. potential losses

⚡ Act Phase - Work Execution

Actionable work orders and execution tracking:

# Build Bill of Materials with economic comparison
ona ooda bom build --asset "inverter-001" --variants-per-type 3

Execution Features:

Automated BOM Generation: Create parts lists with multiple vendor options
Economic Comparison: Compare price vs. lead-time vs. downtime costs
Work Order Creation: Generate detailed maintenance instructions
Execution Tracking: Monitor work progress and completion
Documentation: Centralize evidence for audits and compliance

Key Use Case Scenarios

Scenario A: Rapid Fault Triage and Revenue Protection

Challenge: Intermittent inverter underperformance detected during routine monitoring.

Ona Solution:

# Detect and analyze the issue
ona ooda detect run --asset "inverter-001"
ona ooda diagnose run --asset "inverter-001" --horizon "48h"
ona ooda ear calc --asset "inverter-001" --confidence "95%"

Business Impact:

Risk Quantification: “We detected a persistent deviation vs forecast over the last 48 hours. The EAR estimate shows a $X–$Y band of potential loss if unaddressed.”
Optimized Scheduling: “Here’s a schedule that minimizes downtime within your staffing constraints.”
Revenue Protection: Prevent significant revenue losses through proactive intervention

Scenario B: Parts/OEM Advisory and Lead-Time Risk

Challenge: Diagnostic analysis indicates likely DC fan failure requiring immediate parts procurement.

Ona Solution:

# Generate BOM with multiple vendor options
ona ooda bom build --asset "inverter-001" --variants-per-type 5
ona ooda bom compare --bom "bom-001" --include-downtime-cost

Business Impact:

Immediate Action: “Based on the error signature, the inverter’s DC fan is high-probability. We prepped the BoM so procurement can act immediately.”
Lead-Time Optimization: “Lead-time risk is included in scheduling to minimize revenue impact.”
Economic Trade-offs: Compare multiple vendor options with different price/lead-time combinations

Scenario C: Regulatory and Compliance Readiness

Challenge: Need to prepare for regulatory audits and warranty compliance requirements.

Ona Solution:

# Generate compliance documentation
ona ooda compliance report --asset "inverter-001" --period "30d"
ona ooda warranty evidence --asset "inverter-001" --issue "fault-001"

Business Impact:

Audit Preparation: “We centralize evidence for warranty and regulatory audits (diagnostics, risk assessments, maintenance schedules, orders).”
Compliance Risk Reduction: “This shortens audit prep and reduces risk of non-compliance penalties.”
Documentation Management: Automated generation of compliance-ready documentation

Asset Management

Asset Registration

Manage assets through the CLI instead of editing JSON directly:

# Add an asset with OEM components
ona ooda assets add \
  --id "inverter-001" \
  --type "inverter" \
  --model "SolarEdge SE5000" \
  --location "Site A" \
  --oem "SolarEdge" \
  --serial "SE123456"

Parts Catalogue

Import comprehensive parts catalogues for price/lead-time optimization:

# Import parts catalogue
ona ooda catalog import --file "parts_catalogue.csv"

# View catalogue contents
ona ooda catalog list --type "cooling_fan"

AI-Assisted Analysis

Interactive AI Mode

Leverage AI for deeper insights and analysis:

# Start interactive AI mode
ona ooda interactive

Example AI Prompts:

“Analyze the cost-benefit of replacing vs. repairing the DC fan”
“What are the warranty implications of this fault pattern?”
“Generate a customer-ready explanation of the energy-at-risk calculation”
“Compare the economic impact of different maintenance schedules”

AI Capabilities

Diagnostic Interpretation: Explain fault patterns and implications
Economic Analysis: Quantify costs and benefits of different approaches
Regulatory Guidance: Provide compliance and warranty insights
Communication Support: Generate customer-ready explanations

Economic Optimization

Price vs. Lead-Time vs. Downtime Analysis

When building BOMs with multiple vendor options:

# Build BOM with economic comparison
ona ooda bom build --asset "inverter-001" --variants-per-type 5
ona ooda bom compare --bom "bom-001" --include-downtime-cost

Economic Factors:

Component Cost: Direct parts cost from different vendors
Lead Time: Delivery time impact on downtime
Downtime Cost: Revenue loss during maintenance
Total Cost of Ownership: Comprehensive economic analysis

Vendor Optimization

Preferred Vendors: Filter catalogue by preferred suppliers
Quality Tiers: Compare OEM vs. aftermarket options
Bulk Pricing: Leverage volume discounts
Emergency Options: Identify fast-delivery alternatives

Integration Capabilities

Data Sources

SCADA Systems: Real-time operational data
Weather Data: Environmental conditions and forecasts
Energy Markets: Price forecasts and market conditions
Maintenance Records: Historical work orders and outcomes

API Integration

from ona_sdk import OODAClient

# Initialize OODA client
client = OODAClient(api_key="your-api-key")

# Run complete OODA loop
detection = client.observe(asset_id="inverter-001")
diagnosis = client.orient(asset_id="inverter-001")
decision = client.decide(asset_id="inverter-001")
action = client.act(asset_id="inverter-001")

Performance Metrics

Operational KPIs

Mean Time to Detection (MTTD): Average time to identify issues
Mean Time to Resolution (MTTR): Average time to resolve issues
Uptime Improvement: Percentage increase in asset availability
Cost Reduction: Reduction in maintenance and downtime costs

Financial Impact

Energy-at-Risk Reduction: Prevented revenue losses
Maintenance Cost Optimization: Reduced operational expenses
ROI Improvement: Enhanced return on asset investment
Compliance Cost Avoidance: Reduced regulatory penalties

Getting Started

Prerequisites

Ona Terminal installed and configured
Sample data files in appropriate directories
AWS credentials configured (for forecast integration)

Quick Start

# 1. Set up sample data
ona ooda sample_data setup

# 2. Add your first asset
ona ooda assets add --id "inverter-001" --type "inverter"

# 3. Run your first OODA loop
ona ooda detect run --asset "inverter-001"
ona ooda diagnose run --asset "inverter-001"
ona ooda ear calc --asset "inverter-001"
ona ooda bom build --asset "inverter-001"

Support & Resources

Documentation

Community

Support

📧 Technical Support: support@asoba.co
📖 Documentation: code.asoba.co
💬 Community: Discord

Get Help & Stay Updated

Contact Support

For technical assistance, feature requests, or any other questions, please reach out to our dedicated support team.

Email Support Join Discord

O&M Optimization

Overview

The OODA Loop Methodology

🔍 Observe Phase - Fault Detection

🎯 Orient Phase - Diagnostics

🧠 Decide Phase - Risk Assessment & Scheduling

⚡ Act Phase - Work Execution

Key Use Case Scenarios

Scenario A: Rapid Fault Triage and Revenue Protection

Scenario B: Parts/OEM Advisory and Lead-Time Risk

Scenario C: Regulatory and Compliance Readiness

Asset Management

Asset Registration

Parts Catalogue

AI-Assisted Analysis

Interactive AI Mode

AI Capabilities

Economic Optimization

Price vs. Lead-Time vs. Downtime Analysis

Vendor Optimization

Integration Capabilities

Data Sources

API Integration

Performance Metrics

Operational KPIs

Financial Impact

Getting Started

Prerequisites

Quick Start

Support & Resources

Documentation

Community

Support

Get Help & Stay Updated

Contact Support

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