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What is DC-OM DigitalClone for Wind O&M ?

Sentient Science presents DigitalClone for Wind Operations and Maintenance (DC-OM), a validated software-as-a-service (SaaS) solution tailored for wind turbine operators. This innovative platform enables providers and original equipment manufacturers (OEMs) to collaboratively assess the remaining useful life (RUL) and health of essential systems and components within an asset. By enhancing predictive maintenance strategies, DC-OM aims to significantly lower operations and maintenance (O&M) expenses while simultaneously prolonging the lifespan of equipment assets. The versatility of DC-OM allows users to deploy it as an independent monitoring solution or as an enhancement to current condition monitoring systems (CMS) and diagnostic tools, ensuring it is optimized for both scenarios. Notably, DC-OM can autonomously identify damage in assets that are presumed to be healthy, providing actionable insights, and it also tracks the evolution of damage with comprehensive uncertainty quantification. The insights generated by DC-OM are driven by a proprietary fusion framework that leverages physics-informed machine learning, supported by a distinctive architecture for unifying data from multiple sources, making it a unique asset in the wind energy sector. This comprehensive approach not only empowers operators to make informed decisions but also fosters greater efficiency and reliability in wind turbine management.

What is Cherrywork Predictive Asset Maintenance?

The Cherrywork® Predictive Asset Maintenance Application is crafted to reduce, optimize, and improve costs related to asset lifecycles at every phase, spanning from initial investment planning and network setup through procurement, installation, management during operations, and eventual disposal or replacement. This cutting-edge solution is vital for pinpointing unexpected equipment failures that could threaten consumer satisfaction and the overall dependability of services. Clients expect timely notifications about planned outages, which empowers them to manage their energy consumption effectively. By utilizing this application, users can engage in proactive asset maintenance, thereby sidestepping potential penalties that might arise from unanticipated failures. It utilizes historical data from multiple sources to construct accurate and credible predictive models, which facilitate the creation of forecasts and risk assessments. Moreover, the application integrates information from online monitoring systems, weather predictions, and various non-operational factors such as operational protocols, equipment specifications, and industry benchmarks, thus providing a holistic strategy for asset upkeep. This multifaceted integration of data sources not only bolsters decision-making but also significantly enhances operational effectiveness and efficiency. As a result, organizations can achieve greater sustainability and improved performance in their asset management endeavors.

Media

Media

Integrations Supported

Integrations Supported

SAP Analytics Cloud
SAP Extension Suite
SAP Integration Suite
SAP Store

API Availability

API Availability

Pricing Information

Upon request
Fleet size dependent

Pricing Information

$30,000 one-time payment

Supported Platforms

SaaS

Supported Platforms

SaaS

Customer Service / Support

Standard Support

Customer Service / Support

24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Training Options

Documentation Hub
Online Training

Company Facts

Organization Name

Sentient Science Corporation

Date Founded

2001

Company Location

United States

Company Website

sentientscience.com

Company Facts

Organization Name

Incture Technologies

Date Founded

2006

Company Location

India

Company Website

store.sap.com/dcp/en/product/display-0000053552_live_v1/Cherrywork%C2%AE%20Predictive%20Asset%20Maintenance

Categories and Features

Fleet Management

Incident Reporting
Inspection Management
Maintenance Management

Maintenance Management

Predictive Maintenance
Preventive Maintenance

Preventive Maintenance

Condition Monitoring
Inspection Management
Predictive Maintenance

Categories and Features

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