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Performance

Asset performance monitoring provides data crucial for optimizing operations and ensuring the reliability of energy-producing assets. Twinify’s engineer-friendly dashboards provide full-fleet visibility down to equipment-level performance metrics. By continuously collecting and analyzing data from various sensors and systems and leveraging engineering and AI models, Twinify enables energy companies to predict and improve performance across their portfolio.

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Risk

The Twinify platform taps into performance standards to aid in anomaly detection and incorporates failure probability calculations to support proactive risk management. Scenario models help asset managers explore risk mitigation options and compare alternatives, mapping uncertainties and sensitivities ahead of time. Visibility into where degradation is occurring helps predict upcoming issues and determine the appropriate time to schedule repairs.

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Financial Analysis

Production cost metrics and variable cost pro formas help organizations optimize financial performance across all their assets. Comparisons, benchmarking, and transparent consumption data enable financial modeling to gain a competitive edge in volatile markets. Twinify’s financial model builds on performance calculations and forward simulations to define your historical and future financial picture.

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Sustainability

Twinify’s platform is a catalyst for achieving sustainability goals. By offering valuable insights into asset performance, Twinify empowers maximum production while minimizing environmental footprint. Monitoring key plant metrics, such as TPM, NOx, and CO2, provides a comprehensive overview of each facility’s impact. Understanding failure risk enables more sustainable maintenance practices by reducing unnecessary resource expenditures such as truck rolls. Embrace Twinify to take a significant step towards a greener and more sustainable future.

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Strategy

Twinify’s forward-looking digital twins examine performance, capacity, reliability, sustainability, market influence, risk, and financial outcomes. These engineering calculations enable direct analysis of different outcomes, risk, and profitability by exploring actions against potential future conditions such as weather, markets, regulations, or rate of technology adoption.

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Twinify’s Digital Twin Solutions: Composable & Embeddable

Twinify’s digital twin technology integrates deep industry domain knowledge, domain-specific models, specialized content and artificial intelligence to deliver integrated, OEM-agnostic, future-focused insights. Two features are built into the Twinify platform to unlock the full power of digital twins:

Composable

Twinify’s reusable content building blocks rapidly deliver value by combining intelligence and insights to create new, tailored solutions for the energy producer.

Embeddable

Twinfiy’s ecosystem-friendly digital twin platform leverages APIs to both be embeddable in other platforms, and to embed externally-built content.

By combining composability and embeddability, the Twinify digital twins provide easy-to-augment content that can adapt with new assets and as your business needs evolve.

OEM-Agnostic Integrated Solutions

Twinify is ideally suited for energy producers with multiple types of power generating assets. Regardless of asset type, the powerful Twinify platform aggregates data from all data sources into one place to provide rapid insight that unlocks the power of your data. Where other providers may require you to replace your existing systems and implement their proprietary interface, Twinify integrates into a wide range of existing client and partner systems.

Frequently Asked Questions

Find answers to common queries about our solutions and how they can benefit your business.

How does the Twinify platform secure client data and protect against cyberattacks?

Ensuring the security of digital twin data is very important to us. Our application authentication is provided by the AWS Cognito managed service. Data is encrypted at rest and in transit.

Twinify’s deep visual and analytic environment allows asset managers to effectively navigate KPIs of their entire fleet. Using a combination of aggregated metrics and an asset hierarchy, managers can quickly understand the performance, health, reliability, profitability, and flexibility of their assets.

Our calculations are developed using first principles, engineering, machine learning, domain specific standards, and relevant documentation. Documentation includes but is not limited to the International Electrotechnical Commissions (IEC) technical documents, American Society of Mechanical Engineers Performance Test Calculations (ASME PTC), and Original Equipment Manufacturer (OEM) design documentation.

Twinify leverages a rich engineering history, industry standards, and subject matter expertise when developing digital twin solutions. Each solution is driven by standardized data mapping, calculations from reputable documentation, and communication with our clients.

When you schedule a call with one of our representatives, we can discuss your data availability and how Twinify’s solutions can integrate into your current processes to provide greater value to your operations, planning, and decision-making. Our pilot program provides the opportunity to test drive a Twinify application.

Absolutely – our core offering includes a baseline of industry best practice visuals, models, and calculations, but our platform is designed to allow us to quickly add specific content that a client values.

Twinify can import client data from a SCADA historian or other data sources. Our platform uses machine learning and AI-powered insights to make predictions based on historical and current data. Twinify’s scenarios and risk advisory applications provide predictive capabilities that build upon clients’ existing tools with first principles and engineering calculations to provide additional value.

Twinify works closely with customers to align their available data with Twinify’s library of digital twin content. The quantity of data necessary to establish a foundation for digital twin analysis can vary depending on the nature of the physical system(s) and the desired granularity and capabilities of the digital twin solution. Base solutions primarily utilizing standard domain calculations may only require high-level system configuration and minimal measured data to deliver value to a customer. Anomaly detection capabilities may require weeks or months of historical operational data. Some use cases, such as solar power generation, may require specialized environmental measurements.

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