Industrial Digital Assets
Computational platforms that integrate technical models, operational logic, and business outcomes into unified decision systems
What Is an Industrial Digital Asset?
An Industrial Digital Asset (IDA) is a computational platform that integrates technical, operational, financial, and risk-related models into a unified system for decision-making under uncertainty.
It answers one core question: "What action maximizes business value across the lifecycle of this asset?"
Core Characteristics
Causal Integration Across Domains
An IDA maps how changes in physical performance propagate into financial outcomes, linking equipment failure → system unavailability → production loss → revenue impact.
This causal logic is formalized using PDEL® (Performance Dependency Elucidation Language), ensuring traceability from sensor to P&L.
Dynamic Simulation & Forecasting
Built on probabilistic models, an IDA runs hundreds of simulations over multi-year horizons, forecasting availability, production losses, and sensitivity to feed variability, crew availability, and maintenance delays.
Decision Support Functionality
An IDA enables users to explore thousands of operational scenarios, identify optimal configurations, and evaluate trade-offs between redundancy, cost, and risk—delivering actionable insights, not just data summaries.
Living and Evolving Structure
An IDA is updated with real-world performance data, model refinements, and new rules. It grows more accurate and valuable over time, serving as a permanent knowledge repository.
What an IDA Integrates
Reliability & Maintainability Models
Failure distributions, degradation curves, maintenance effects on performance
Process & Control Systems
Real-time operational data, process historians, configuration states
Logistics & Planning
Spare parts availability, maintenance windows, crew scheduling
Market & Contractual Data
Price curves, contractual obligations, delivery commitments
Real-World Application: Major Gas Processing Plant
Context
A large gas processing facility needed to optimize compressor configurations across dry and wet gas compression systems, evaluate mixed-mode operations, and link technical decisions to EBITDA impact.
IDA Implementation
- Integrated reliability models for all compressor units and critical equipment
- Simulated 100 scenarios over five-year horizon to forecast availability and production
- Used MiRO v1 (Minimizer of Operational Risk) to identify optimal configurations
- Linked equipment performance to market delivery capability and contract obligations
- Enabled exploration of thousands of scenarios for risk-reward optimization
Business Value
Operators gained the ability to maximize EBITDA by choosing configurations that balanced production targets, maintenance costs, and reliability risk. The IDA continues to support investment decisions and operational planning.
MiRO v1: Minimizer of Operational Risk
Proprietary Framework
MiRO v1 is Knar's optimization engine for exploring operational configurations and identifying strategies that minimize risk while maximizing value across:
- Equipment failure scenarios and reliability constraints
- Feed variability and composition shifts
- Market price fluctuations and contract requirements
- Regulatory constraints and emission limits