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Asset Management

Boost Asset Lifespan and Performance with IIoT and Predictive Solutions.

In the circular economy, Asset Management solutions shift from an efficiency-driven approach to one focused on resource durability. The emphasis is on designing products to be upgradeable and reusable, while promoting collaborative consumption. Achieving these goals requires significant changes in underlying processes, technologies, and infrastructure.

Our Capabilities

Optimizing asset management solutions processes is essential for manufacturing companies, as it ensures high performance and longer asset lifespan while reducing maintenance costs and energy inefficiencies. We support our clients with digital consulting services and tailored solutions to enhance the end-to-end governance of their assets.

A SUCCESS STORY

Machine Learning Safeguards Solar Panels From Extreme Wind

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Extending the Asset Lifespan

The Industrial Internet of Things (IIoT) provides real-time data on critical assets, enabling the monitoring of usage, performance, and maintenance. This allows for optimizing operating conditions, performing predictive interventions, and extending asset lifespan while reducing operational costs. Our services help clients effectively integrate IIoT into their asset management solutions, improving efficiency and resource longevity.

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Digital Twin

A digital twin is a digital replica of a physical asset, created using its configuration and real-time sensor data. It is used for predictive maintenance, as it can simulate the asset’s performance under various conditions, including stress. This enables optimizing usage, running simulations to ensure optimal operation, and testing responses, with the goal of improving performance and extending asset lifespan.
We support clients in defining a digital twin roadmap for their most critical assets and implementing the necessary technologies to bring it to life.

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Optimizing Performance

To optimize asset performance, companies need to collect and analyze data from various sources such as IIoT sensors, cameras, and other monitoring technologies. This data provides valuable insights into asset usage and performance. By integrating it with other, like quality control data, companies can make data-driven decisions to enhance performance, adjust operating conditions, reduce downtime, and improve overall efficiency.
Our approach helps clients modernize their maintenance practices, from digital enablement to implementation and ongoing support. We offer a comprehensive solution that leverages the latest technologies and analytical tools to optimize asset performance.

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Predictive Maintenance

Anticipating maintenance before a failure occurs allows companies to optimize asset operational performance, reduce total cost of ownership, and prevent downtime, while extending asset lifespan. This is achieved by collecting real-time data from sensors and using predictive machine learning algorithms to identify patterns and forecast potential failures. Advanced models can also automate maintenance service requests, scheduling them based on production plans and the criticality of the required maintenance.
We support companies in implementing the asset management solutions, processes and technologies needed to manage predictive maintenance of their assets.

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Life Cycle Assessment: Why and Who Should Adopt It

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Are you ready to drive the next wave of sustainable innovation?

Book a free discovery call with our experts to adapt your business for a circular future.

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Our Partners

SAP

Case Study

City of Milan – Smart City Platform

Discover how Avvale has established an environment marked by extensive integration and interoperability of information systems, commonly referred to as the "Urban Digital Ecosystem".

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Saras Digitizes Oil Refinery Maintenance, Enhances Worker Safety and Productivity

Discover how Saras overcomes field connection roadblocks to enhance worker safety.

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Gates Corporation Captures Critical Customer Insights

Manufacturing industry giant Gates Corporation's growth demanded a clear line of sight into customer data. Using SAP BTP, Avvale created a real-time analytics solution to bridge the gap.

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Case Study

Machine Learning Safeguards Solar Panels From Extreme Wind

Violent wind gusts can thwart and damage solar panels, a costly and disruptive challenge. Discover how Avvale created a machine learning algorithm to accurately predict the weather and protect solar panels.

Explore