Intelligently Manage Assets With Custom Analysis Apps

Anubhav Bhatia

In the modern world of digitization, manufacturers and operators managing assets must be able to bring their home-grown industrial processes into the cloud to complement the solutions they purchase from software vendors. This is driven by factors such as the existence of heterogeneous data lakes and industry-specific business processes that are proprietary to asset manufacturers and operators.

Asset-management companies need new applications in the cloud to enrich the features of their critical business processes and enable them to work in a secure, reliable, and performant way with the standard asset-management software they purchase from software vendors.

Reliability engineers and planners at asset manufacturers’ and operators’ sites could use these custom apps in combination with the ones offered by software vendors to streamline root-cause analysis and evidence gathering for poorly performing assets, which would enable them to take meaningful, proactive actions to improve them. Data scientists at asset-management companies could then use industrial algorithms and statistical analyses for simulations, what-if analyses, and predictions of asset failures using these custom analysis apps with the standard apps delivered by the software vendor.

Asset manufacturers’ and operators’ and software vendors’ requirements include facilitating analytics app development in the cloud with an integrated development environment and workflow-driven processes for the creation, deployment, and lifecycle management of apps. These newly developed custom apps must also be able to interact with software vendors’ standard asset management apps.

Once these custom apps are created by asset manufacturers and operators and co-exist with software vendors’ apps in the cloud, the new business functionalities must be shared with partner channels for better asset accountability and maintenance. This extensibility in the cloud can help the asset network bring new asset management processes to the cloud that benefit asset operations and reduce the overall total cost of ownership.

Explore how the SAP Predictive Maintenance and Services solution, part of SAP Intelligent Asset Management, offers functionality to create custom analysis tool applications in the cloud that could help customers’ business processes and data lakes work with standard SAP applications in a seamless manner.

About Anubhav Bhatia

Anubhav Bhatia is currently vice president, Engineering, at SAP Labs, Palo Alto, California. He leads efforts in area of intelligent asset management especially in area of predictive maintenance and services using AI. Anubhav has more than decade of experience in engineering, architecture, platform development, and senior management roles. He has proven expertise in innovations, application development, and business process orchestration in enterprise systems. Anubhav is also an official member of Forbes Technical Council, IEEE Senior member, ASUG Member, and speaker at many SAP and ASUG events.