Industrial performance rarely fails dramatically — it drifts.

Small inefficiencies accumulate.
Operating envelopes shift.
Assets run below optimal conditions.

VROC’s Performance Optimization solution enables organisations to continuously identify, simulate, and implement improvements across assets and processes — without compromising safety, reliability, or compliance.

 

Move from Reactive Correction to Continuous Optimization

Traditional optimization relies on:

  • Static engineering models

  • Periodic reviews

  • Manual calculations

  • Isolated improvement projects

VROC delivers continuous optimization by combining real-time operational data with advanced analytics and simulation — enabling engineers to understand not just what is happening, but what could happen under different conditions.

What this solution enables

Assets perform best within specific operating ranges — but those ranges shift with wear, load, environment, and process conditions.

VROC enables:
* AI-defined operating envelopes
* Identification of efficiency loss and constraint points
* Dynamic optimization of throughput, energy use, and performance
* Continuous benchmarking against optimal conditions

This ensures assets are not just running — they are running at their best achievable performance.

Before implementing operational changes, teams need to understand risk and trade-offs.

VROC supports:
* Digital twin modelling of assets and processes
* What-if scenario testing
* Sensitivity analysis
* Performance forecasting under varying conditions

Engineers can test decisions virtually before applying them in live operations.

In multi-site or fleet environments, performance variability often goes unnoticed.

VROC enables:
* Asset-to-asset performance comparison
* Site-to-site benchmarking
* Identification of best-performing operational patterns
* Replication of optimal configurations across fleets

This turns operational data into measurable competitive advantage.

Optimization must connect to measurable outcomes.

VROC links operational improvements to:
* Throughput gains
* Energy intensity reduction
* Emissions performance
* Cost reduction
* Asset life extension

Improvements are tracked and quantified — not assumed.

Designed for Operational Teams

Optimization should not require advanced modelling expertise.

VROC provides:

  • Self-serve configuration tools

  • Explainable model outputs

  • Integration with live operational data

  • Rapid iteration for engineers

Decisions remain in the hands of those who understand the process best.

 

From Insight to Measurable Performance Gains

Performance Optimization builds directly on:

With a strong monitoring foundation, optimization becomes continuous, scalable, and repeatable — rather than project-based and reactive.

Get Started

Why VROC

Real-time performance intelligence

Supports smarter maintenance decisions

Safe scenario testing before implementation

Measurable performance improvement

Scalable optimization across sites

Optimise with Clarity. Execute with Confidence.

Explore how VROC enables continuous performance improvement across your operations.

Explore Control & Automation

Talk to our team
Customer Benefits

Our client's success is our success

“We have prolonged the gas compressor reliability to four months, from a maximum of 2 weeks running. The GCM uptime has improved to a value of 21.7m USD.â€

Head of Offshore Operations

“Let everyone use, don’t restrict to any process engineer or operation engineer, give everybody access including business planners, let everyone use it. Because the beauty of this is that it will open the eyes of the importance of Artificial Intelligence in Oil and Gas.â€

Manager Head Strategy & Performance Health Safety & Environment, Gas and New Energy

“It took our Focus group 2 weeks to come up with the problem with the gas compressor and form an action plan. When we met with VROC, the VROC model gave all the problems that we needed to focus on in less than 10minutes. This helped the engineers pinpoint the problem.â€

Manager Head Strategy & Performance Health Safety & Environment, Gas and New Energy

“Trying to scale machine learning models across thousands and thousands of failure modes on a plant, is probably not practical in the traditional approach to data science, where you can spend three to six months building a model, training it testing and operationalising it, maybe longer.â€

Global Vice President, Data Science Customer Solutions, Worley.
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Operate with clarity. Perform with confidence

Gain real-time visibility, predict failure earlier, optimize performance, and take control of your operations with VROC’s integrated solutions.