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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- SAP Analytics
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Advanced Analytics and Process Intelligence
Published: 10/May/2022
Reading time: 3 mins
Role of Advanced Analytics in Process Intelligence In the latest SAPinsider process automation state of the market research, majority of SAPinsiders indicated that intelligent automation and process intelligence are key capabilities they are planning to build within next two years. Advanced analytics methodologies will play a key role in building intelligent automation solutions. In this article,...…
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Oil well drilling contractor reduces downtime and improves asset reliability with SAP APM implementation.
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Published: 12/October/2024
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Effective Enterprise Asset Management (EAM) systems depend on high-quality data, and companies like AssetOn have proven this by auditing and improving Glencore Coal’s SAP data to enhance operational efficiency, reduce costs, and ensure accurate maintenance planning across multiple sites.
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IBM is RISE with SAP’s New Hyperscaler Option
Published: 10/July/2025
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SAP has launched RISE with SAP on IBM Power Virtual Server, enabling existing SAP S/4HANA customers to migrate to SAP Cloud ERP more efficiently while maintaining architectural consistency and reducing complexity, with additional resources and tools from IBM to support the transition.
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- SAP Enterprise Asset Management
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Defining ‘Good’ in SAP Today: Enabling Innovation Through Integrated Technologies and a Novel Approach to AI in Asset Management
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Published: 15/November/2005
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