SAP Asset Performance Management - Visual Asset He...

Pardhasaradhi_Reddy_Chelikam

Visual Health Monitoring is a powerful tool that uses vision to assess the asset condition and identify the potential problems. As part of the SAP Asset Performance Management (APM) June 2025 release, SAP introduced Manage Visual Inspection Results application for reviewing, verifying, and approving visual inspection results.

In this blog, I will outline how an asset`s condition can be documented with an image using a visual health monitoring application. In this demonstration, I will use SAP standard API to upload the image to the equipment indicator.

My Business Use Case: My organization uses Non Lubricated, Horizontal Air Compressor to produce plant air. When I was working as a mechanical engineer, I conducted daily rounds to visually inspect equipment in my section, recorded key operational parameters, and took corrective actions whenever deviations observed.

Now, let us assume that we have visual health monitoring application to record operational parameters. For Instance , I go for a daily round to visually inspect the air compressor, and record the suction filter condition with an image and allow maintenance manager confirm the recorded condition. In this process, for demonstration purpose, I will use POSTMAN tool to upload the image and measurement reading.

If you want to gain deep understanding of certain key functionalities in SAP Asset Performance Management (APM), i.e. Failure Curve Analytics, Achieving Sustainability with SAP APM through Industrial Systems, and Embedded IoT Metadata Synchronization, check out my previous posts below.

Let us dive in and explore...

Visual Asset Health Monitoring is effective for:

Early Detection Of Defects: This helps identify the potential failures and prevents unexpected functional failures.

Automated Inspections with AI: Integrating Artificial Intelligence (AI) into inspection process can efficiently identify the anomalies.

Cost Savings: Early detection of potential failures can lead to substantial savings in maintenance expenses.

Regulatory Compliance: This helps comply to the regulatory body requirements if any.

Customer Satisfaction: This streamlines maintenance activities and ensures that assets remain functional and safe to operate, thus enhances maintenance team efficiency.

Operational Efficiency: By identifying the defects in advance using image analysis, maintenance can minimize the disruptions and thus improves efficiency.

Risk Management: Leveraging image analysis, maintenance team can execute more effective risk assessments on technical objects.

Prerequisites and Limitations: Please find the link below to know more about prerequisites and limitations for visual asset health monitoring Apps/APIs.

Prerequisites and Limitations for Visual Asset Health Monitoring Apps/APIs

Master Data Setup in SAP S/4HANA: Create an Equipment with relevant attributes and Measuring Points.

Equipment In S4HANA Asset Management

Create a Characteristic for each visual inspection AI results.

Characteristic for Visual Inspection in S4HANA Asset Management

Data synchronization with APM : Navigate to the Integration Monitor to facilitate the data transfer between S/4HANA and APM. Explore Technical Objects application to view the detailed information of technical objects.

Air Compressor Master Data in SAP APM

Create a "Local Indicator" for each AI model results to analyze images in health monitoring activities.

Air Compressor Indicators in SAP APM

Configure the local indicator as a "Visual Inspection" to designate the indicator for visual data input.

Categorizing the indicator for Visual Inspection

The master data setup has been completed. Now let us post Inspection results to the indicator. This involves uploading the image and associated data (such as, dot annotation coordinates). The Dot Annotation Coordinates are crucial in guiding the system on where the AI should focus its analysis within the image. The Dot Annotation`s position is determined by coordinates sent in the payload.

Get the "Manage Visual Inspection Results - POST API" from API hub.

Manage Visual Inspection Results -POST API

Payload Structure

Download the "OpenAPI JSON" file for "Manage Visual Inspection Results" from the API hub. Then use the "Import" feature in the POSTMAN tool to set up the collection request.

Following the successful collection request setup, input the parameters for the indicator. To get the indicator position ID and Characteristic Id for the AI Indicator, call the READ API : Metadata Sync-Technical Objects.

For instance, I have updated the suction filter obstruction to 49.44% and uploaded the following image.

Once the data for the AI indicator is set, upload the Image of the suction filter and POST the corresponding values.

Now, let us navigate to "Manage Visual Inspection Results App." in SAP APM to validate and approve visual inspection results, updating the status to "Confirmed".

Now the status has become "Confirmed". The "Confirmed" status indicates that user has validated and approved the inspection results.

Now, let us check the annotation details of the uploaded Image to ensure accuracy.

Now, let us review what happens when the visual inspection results are rejected. We can reject when the inspection results are unsatisfactory or incorrect.

Finally the feedback summarizes the human review of inspection results as Pending, Confirmed, and Rejected.

Now, let us navigate to the "Explore Technical Objects" to view the readings and uploaded image for the AI indicator linked to Air Compressor (10001729). We can view both Confirmed and Rejected Visual Inspection Results.

😊This brings me to the end of the process walkthrough on "Manage Visual Inspection Results" application in SAP Asset Performance Management (APM). I hope my blog proves useful to the plant engineering/maintenance team, and I look forward to seeing them leverage this feature effectively to measure asset health along with condition based rules.

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Yours Sincerely,

Pardhasaradhi Reddy.C

SAP Asset Performance Management - Visual Asset Health Monitoring (Part-1)