Introduction: You're Not Missing Technology — You're Missing Architecture
Most companies believe they have a "Digital Asset" because they use SCADA, dashboards, or even AI tools.
But if your digital system doesn't answer this question:
"If we change this configuration, delay this maintenance, or switch this energy source — how much will EBITDA increase or decrease?"
Then you don't have a Digital Asset.
You have data.
At Knar, we define a Digital Asset not by its technology, but by its function:
It is a computational engine that links physical reality to financial performance through traceable causality.
And we don't just implement them — we architect them.
1. What Is a Physical Asset? The Foundation of Value
A physical asset — a turbine, compressor, pipeline, or reactor — enables value by transforming matter and energy in a controlled way.
But alone, it cannot decide:
- •When to run
- •How fast to operate
- •Which maintenance action to prioritize
It needs direction.
Without intelligent control, even the best equipment produces waste, downtime, and risk.
So value isn't created by hardware alone. It's created by the integration of physical execution and decision-making.
2. Why "Digital" Doesn't Mean "Asset"
Calling every piece of software a "Digital Asset" dilutes the term.
A dashboard showing uptime percentages?
→ Not an asset. It's information.
A spreadsheet forecasting production?
→ Not an asset. It's an estimate.
A control loop in a PLC preventing overfill?
→ Closer — it enables safety and cost savings. But still only a component, not the full system.
True Digital Assets are not isolated tools. They are integrated decision-support platforms that:
- •Model how value is produced
- •Simulate thousands of scenarios
- •Prescribe optimal actions under uncertainty
- •Evolve with the asset over time
If it doesn't shape decisions that move the P&L, it's not an asset.
3. The Real Definition of a Digital Asset
A Digital Asset is a computational representation of an industrial system that integrates:
- •Equipment reliability (RAM models)
- •Process constraints
- •Maintenance logistics
- •Market dynamics
- •Financial outcomes
...into one executable model capable of answering:
"What should we do next to maximize business value?"
This is not animation.
It is causal engineering.
Examples include:
- •An iDSS (Integrated Decision Support System) for a sulfuric acid regeneration unit
- •A dynamic optimizer for hybrid power generation (grid + solar + storage)
- •A living Fidelis-based model updated with real-world failure data
These systems don't reflect reality — they predict and prescribe within it.
4. Case Example: Malvinas Plant Digital Asset
We built a Digital Asset for Pluspetrol's Malvinas facility that goes far beyond monitoring.
It allows operators to:
- •Explore literally thousands of operational scenarios
- •Identify optimal compressor configurations
- •Minimize risk using MiRO v1 (Minimizer of Operational Risk)
- •Quantify EBITDA impact of each choice
This isn't guesswork.
It's simulation-driven decision-making — where physics meets profit.
And because it uses PDEL® (Performance Dependency Elucidation Language), every input has a traceable path to financial output.
How They Work Together: Industrial Gas Processing Case Study
Consider our work with a major integrated gas producer's processing facility in South America.
5. Common Misconceptions About Digital Assets
| Myth | Reality |
|---|---|
| "Digital Assets are about collecting more data." | No — value comes from modeling dependencies, not volume. |
| "AI will solve everything." | AI fails without causal structure. Garbage in, garbage out. |
| "We need better visualization." | Dashboards don't make decisions — people do, guided by models. |
| "One vendor can deliver our Digital Asset." | Only possible through integration across domains — which requires architectural leadership. |
Knar does not sell vendors' tools. We integrate them into systems that work.
6. How Knar Builds Digital Assets That Generate Value
Our approach follows six principles:
Start with Business Objectives
What value are we trying to protect or unlock?
Map Causal Dependencies (PDEL®)
Link equipment failure → system unavailability → production loss → revenue impact.
Build Executable Models
Use AspenTech Fidelis, Wolfram Mathematica, or custom solvers to simulate behavior under uncertainty.
Validate Against Reality
Apply QA protocols (e.g., Formal Delivery Protocol) to ensure fidelity.
Embed Into Decision Processes
Connect outputs to planning, scheduling, contracting, and operations.
Institutionalize Capability
Train teams so the Digital Asset lives beyond our engagement.
This is how we turn data into institutional intelligence.
7. Conclusion: Digital Assets Are What Make Physical Assets Profitable
Hardware depreciates.
Data decays.
But a well-architected Digital Asset appreciates in value over time.
Because it learns.
Because it adapts.
Because it ensures that every decision — from the boardroom to the field — is aligned with business value.
At Knar, we don't digitize plants.
We engineer decision resilience.
And we do it so organizations can navigate complexity with confidence — not guesswork.
"We walk with you to architect a new solution."