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Why You Need to Add Asset Lifecycle Management to Your Digital Twin

The specific definition of “Asset Lifecycle Management” (ALM) remains disputed with many different interpretations in common use. Fortunately, there are some points of agreement among the competing meanings, specifically the philosophy that to get the most value out of an asset, you must carefully manage it over its entire lifetime.

Multiple factors can affect the asset lifecycle. Modification projects have their own lifecycle, which in turn becomes part of the individual asset’s own lifecycle. An Asset Lifecycle Information Management (ALIM) platform like HxGN SDx tracks and manages these various interrelated lifecycles to provide a true understanding of asset value.

The role of digital twins in ALM
The initial project twin is an integral aspect of the design and build phases, ensuring the new construction is fully planned and understood. However, the model is not fixed and unchanging – the digital twin evolves continually over the course of an asset’s lifecycle as it is designed, fabricated, constructed and commissioned, and then during operations as it is upgraded, modernized or reconfigured.

The initial project twin that accompanies initial design construction is often considered a greenfield activity; the digital twin then evolves during modernization projects to support brownfield activities.

Every asset lifecycle is different, rarely travelling in a straight, predictable line. Digital twins must be updated after every inspection, overhaul or outage to help build a complete understanding of its role and lifetime cost-benefit.

Why is Asset Lifecycle Information Management Important?
Monitoring and recording every detail of every asset in a digital twin sounds like an unwanted layer of bureaucracy that will slow operations and add to running costs. But there are significant benefits to adopting ALM.

  1. Maximizing effectiveness – An optimized production delivers optimal yields. Using ALM, it is possible to improve quality, availability and performance by ensuring every asset is performing within acceptable parameters. More effective assets offer opportunities for additional revenue, cost reductions and improved profit margins.
  2. Maximizing asset longevity – ALM provides early warning of potential failure, allowing you to plan and complete maintenance cycles before failure, extending the lifespan of each asset. Extending asset replacement cycles while maintaining effectiveness will reduce long-term costs.
  3. Remote workforce trends – Pandemics aside, improving health and safety standards requires operators to reduce employee exposure to harmful or dangerous environments. Improvements in technology mean that remote working is not only desirable, but also increasingly possible, and automated ALM plays a role in enabling hands-off operations.
  4. Improving workforce efficiency – ALIM supported by a complete, consistent digital twin provides rapid access to information in context. This reduces search and waiting time and increases wrench time of field workers. Preparing information for modification projects and to support Shutdowns, Turnarounds and Outages is also dramatically reduced.
  5. Simplified data collection – By reducing the manual element of data collection, technology is helping to reduce the cost of ALIM. Inexpensive sensors, Industrial Internet of Things (IIoT) and cloud technologies are opening new opportunities and improving the quality of digital twin modeling.
  6. Preparing for the future – Digital twins allow progressive executive sponsors to see the future. IT/OT convergence and digitalization efforts are now run at the C-suite level, so if they can literally see the asset lifecycle, it becomes easier to secure funding for digital twin and ALM projects.

Digital twins and ALM offer value at every level, from day-to-day operations to strategic planning and budget allocation.

Consolidating and Sharing Data
As mentioned earlier, constantly updating digital twins delivers measurable benefits, but there is a cost and resource overhead to consider. The OSIsoft™ PI System™ data historian helps to automate much of the data collection and update process.

The PI System imports data from almost any source, providing context for every metric. Visualization tools and integrators deliver insights to people, platforms and applications across your business. Centralization, collation and the ability to break through information silos help to bring together the many phases of the asset lifecycle.

With over 400 interfaces, the PI System can collect data from virtually any source across your production line. Built for the largest of enterprise environments, the PI System can store and visualize up to 1 million signals per second – in real-time.

Once data has been processed and shaped, the PI System can send it back to third party systems like ERP software, data warehouses, business intelligence and analytics tools. Ready-to-consume data can be put back to work immediately by the rest of the business.

Context and Notifications
By combining so many different sources, the PI Asset Framework can collate and align relevant data / meta-data to deliver information in context. This allows for the creation of a more meaningful digital twin representation of each physical asset. The PI System allows you to update your digital twins with information that enhances predictive maintenance, shift handover logs, batch runs and other meaningful metrics.

The PI System also applies intelligence to incoming data. Each signal is analyzed in real-time, raising alerts and notifications when abnormal operating parameters are detected.

Ensuring that data is available – and usable – by all authorized stakeholders, PI Vision™ offers web-based visualizations. As well as making key metrics available at-a-glance, the interface is fully editable, using drag-and-drop elements so that users can see exactly what they need – and share their dashboards with their colleagues.

Feeding into Digital Twins
The PI System accepts raw data from every sensor on and around each asset, storing it in the PI Data Archive. The PI Asset Framework then organizes the raw data according to asset, forming the basis for the equivalent digital twin. The model offers engineering and design consistency and can be integrated with HxGN SDx to ensure an evergreen, fully-up-to-date operational twin.

Using the HxGN SDx Connector for OSIsoft, the PI System can feed operational data into an asset lifecycle information management and digital twin platform. This interface also allows the PI System to access other relevant information, such as manufacturer performance tables, and combine that with real-time process data to visualize useful information for operators, such as a pump’s actual efficiency versus its efficiency curve, helping the operator to find the peak flow rate for the pump based on current operating conditions.

Sharing data is vital for successful ALIM
The ability to access and centralize all data about an asset is the only way to truly understand its lifecycle. The combination of HxGN SDx and the PI System can not only make it easy to access that data but also turn it into actionable metrics and insights – and to build and maintain digital twins for all your assets.

To learn more about how HxGN SDx and the PI System complement each other – and how your business will benefit – please watch the Hexagon and OSIsoft “Essential Elements of an Operations Digital Twin” webinar series.

About the Author

Adrian Park has been with Hexagon since 2007 and currently serves as the Vice President for Pre-sales for the EMIA region. From 2007 to 2018 he worked in Global Business Development for Information Management solutions. He is based in Sandnes, Norway.

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