SAP Asset Analytics
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Predictive Asset Analytics is the use of statistical modeling, data mining techniques, machine learning, and digital twin technologies to make predictions about future outcomes. A cloud deployment or cloud native solution is required to gain insights from sensor data and engineering simulations. With advances in data storage and loT sensor technology organizations can learn about each asset’s individual performance to predict asset productivity.
Improving reliability, performance, and safety are top priorities for organizations today. But organizations are also focusing on controlling costs and maximizing value from existing investments by supporting predictive maintenance and service. Predictive asset analytics is a solution for end-to-end asset management to provide early warning signals and give a diagnosis of equipment long before failure.
Key Capabilities of SAP Predictive Asset Insights include:
- A 360 view of assets: A holistic view of the asset model with a single predictive tool increasing visibility into master, transactional, performance, and loT data sensor data.
- Intuitive and scalable machine learning: Ability to detect abnormalities and predict failure without data scientist intervention, extending the intelligence of predictive maintenance by machine learning capabilities.
- Advanced analytics: Gain insights into failure modes and leading indicators by benefiting from purpose-made analytical capabilities augmented with predictive asset intelligence.
- Digital twin simulations: Apply ANSYS digital twin technology to analyze assets in action and over time in a live environment where engineering simulations support virtual sensors.
Predictive Asset Analytics is the use of statistical modeling, data mining techniques, machine learning, and digital twin technologies to make predictions about future outcomes. A cloud deployment or cloud native solution is required to gain insights from sensor data and engineering simulations. With advances in data storage and loT sensor technology organizations can learn about each asset’s individual performance to predict asset productivity.
Improving reliability, performance, and safety are top priorities for organizations today. But organizations are also focusing on controlling costs and maximizing value from existing investments by supporting predictive maintenance and service. Predictive asset analytics is a solution for end-to-end asset management to provide early warning signals and give a diagnosis of equipment long before failure.
Key Capabilities of SAP Predictive Asset Insights include:
- A 360 view of assets: A holistic view of the asset model with a single predictive tool increasing visibility into master, transactional, performance, and loT data sensor data.
- Intuitive and scalable machine learning: Ability to detect abnormalities and predict failure without data scientist intervention, extending the intelligence of predictive maintenance by machine learning capabilities.
- Advanced analytics: Gain insights into failure modes and leading indicators by benefiting from purpose-made analytical capabilities augmented with predictive asset intelligence.
- Digital twin simulations: Apply ANSYS digital twin technology to analyze assets in action and over time in a live environment where engineering simulations support virtual sensors.
Benefits of SAP Predictive Asset Insights are:
- Improves service effectiveness
- Lowers maintenance costs
- Increases asset availability
Vendors partners for predictive asset analytics are: SAP , PWC, KCT
Key Considerations for SAPinsiders are:
- Advanced Analytics and Performance Intelligence. In the recent state of the market for process automation, SAPinsiders indicated that intelligent automation and process intelligence are key capabilities they are planning to build in the next two years. This analyst insight explores some critical aspects to be aware of on your path to develop these capabilities.
- Achieve Business Clarity with Process Intelligence. Process intelligence provides an understanding of where process deficiencies exist and where leverage opportunities reside. SAPinsider sat down with Shoeb Javed, Chief Strategy and Product Officer for software testing firm Worksoft Inc., to discuss the latest Achieve Business Clarity with Process Intelligence process intelligence trends.
- Digital twins are on the Rise to Mitigate Risk. Companies are searching for greater efficiencies to improve operational efficiencies and be more resilient. In this analyst insight learn what digital twins are, how they work, how they have evolved, and benefits that they can bring to your organization. Optimization is where digital twins excel to test contingency plans and build resilience.
1279 results
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Published: 28/September/2012
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Published: 01/January/2004
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Define Your Own Sort Versions in FI-AA Reports
Published: 15/February/2008
Reading time: 14 mins
You can use transaction OAVI to create your own sort versions for standard Asset Accounting reporting, adjusting for business scenarios that aren’t covered by your system’s standard sort versions. Also, see some SAP Notes that are useful for troubleshooting. Key Concept The Asset Accounting (FI-AA) module contains a sort version (formerly called a sort variant)...…
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Streamline Asset Acquisitions with Investment Management
Published: 03/October/2013
Reading time: 11 mins
The asset acquisition process is very important for many companies. Discover the advantages of setting up a standard process for asset acquisitions using functionality within the investment management (IM) and project system (PS) modules. Key Concept An appropriation request (AR) can be interpreted as a funds request that is subject to business approval. It can also be...…
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Proven Techniques and Strategies to Fortify Your SAP Landscape from Cybersecurity Threats
Published: 01/March/2017
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A New Era In Analytics: SAP BusinessObjects and Journey to the Cloud
Published: 30/July/2021
Reading time: 10 mins
Over the last three decades, SAP BusinessObjects Enterprise has amassed an immense userbase. As a leading solution for enterprise and ad hoc reporting, users continue to rely on the software to compile large amounts of data into universes for analytical modeling and report against it. However, as changes in the market occurred and the needs…
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Live from SAPinsider Studio: Ty Miller of SAP on Cloud for Analytics
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