When industrial machinery breaks down, it often results in significant operational downtime. Predictive maintenance can alleviate many issues related to equipment upkeep, but its implementation is not without challenges. The process usually requires the integration of sensors, data infrastructure, data analysis, and machine learning, a blend of software and hardware skills that often leads to lengthy setup periods and delayed return on investment. Therefore, it is vital to find a solution for managing equipment failure that seamlessly integrates with existing business procedures for asset management and plant maintenance.

                Amazon Monitron enables the customers to implement a predictive maintenance program and reduce unplanned downtime. SAP customers use SAP Enterprise Asset Management to create maintenance notifications for industrial equipment. 

In this blog post, we will walk you through a framework on SAP Business Technology Platform (SAP BTP) with which we can provide an integration framework between Amazon Monitron and SAP S/4HANA Asset Management and thereby automating the process of creating maintenance notifications. 

In the upcoming sections of the blog post, we will describe the solution architecture, systems involved, PoC scenario and a quick demo followed by the instructions to deploy the solution from a GitHub repository. 

Engagement

The outcome described in this article was facilitated by an engagement between SAP and Amazon Web Services which resulted in the creation and validation of a joint reference architecture use cases and PoC. Teams from PVN Pavan Kumar (SAP Labs India) and Soulat Khan (Amazon Web Services) have participated in this engagement.

Business Scenario

Predictive maintenance plays a crucial role in helping industries avoid downtime by using advanced analytics and machine learning algorithms to predict equipment failures before they occur. By analyzing historical data and real-time sensor readings, it can identify patterns and anomalies that indicate potential issues. This enables proactive maintenance thereby minimizing the impact on production.

In this scenario, abnormal conditions are detected and the events are generated and sent to the Events-to-Business Action Framework which maps it to an associated business action, which in this case, is to create a maintenance notification in SAP S/4HANA Asset Management. The business value of this integration helps industries to improve operational efficiency and ensure uninterrupted production.

Amazon Monitron is an end-to-end system that uses machine learning to detect abnormal conditions in industrial rotating equipment, enabling you to implement a predictive maintenance program and reduce unplanned downtime. It includes sensors to capture vibration and temperature data, a gateway to securely transfer data to AWS, a service that analyzes the data using machine learning (ML), and a companion mobile and desktop app to set up the devices and track the condition of your machinery. The Monitron service can export data to a kinesis stream and S3, making data available for downstream SAP integration. For more information, please check out  Amazon Monitron.

Image courtesy : https://aws.amazon.com/pm/monitron

SAP Enterprise Asset Management (EAM) helps organizations to plan, optimize, execute, and track the necessary activities, priorities, skills, materials, tools, and information associated with an asset. Failure to manage and maintain enterprise assets can lead to unplanned downtime, suboptimal asset performance, and supply shortages. Customers also rely on EAM systems to demonstrate compliance with regulatory bodies to preclude liability if a failure occurs. To learn more about SAP EAM solution, refer SAP Enterprise Asset Management

Solution Architecture

The following steps depicts the information flow across systems:

(1) Event is triggered from Amazon Monitron Hardware and sent to Amazon Monitron Software.

(2) and (3) Amazon Kinesis streams the sensor data from Amazon Monitron and lands it into the Amazon S3 bucket.

(4) AWS Lambda is a serverless function, which will orchestrate the process of detecting a stream contains any alerts related to failure or warnings, and then the inference result is passed to SAP Advanced Event Mesh.

(5a) AWS secrets manager is used to store credentials; these are used by the lambda function to provide payload to SAP Advanced Event Mesh.

(5) Event-to-Business-Action framework (extension app) processor module’s endpoint is subscribed to SAP Advanced Event Mesh, hence receives this event.

(6) Event-to-Business-Action framework processor module leverages the Decisions capability of SAP Build Process Automation to derive a business action (for example, in this scenario, Plant Maintenance Notification creation in SAP S/4HANA system) based on certain characteristics of incoming event.

(7), (8), (9) (10) and (11) Event-to-Business-Action framework processor module triggers the defined action in the SAP S/4HANA system by using the SAP Destination Service and SAP Private Link Service.

The integration architecture uses SAP “Events-to-Business Actions” architecture which is an event-driven framework on SAP Business Technology Platform (SAP BTP) to respond to and integrate with events generated from industrial production processes in plants, warehouses, and logistics into enterprise business systems, triggering associated business processes to enhance enterprise operations and enable rapid decision-making.

Scenario Setup and Deployment

To get the entire scenario working, there are prerequisites and initial configurations required in SAP Business Technology Platform, Amazon Web Services, and SAP S/4HANA.

Please refer to the published GitHub repository which contains code samples and instructions for implementing this scenario

• GitHub Repo
• Discovery Center Mission (to be updated shortly)

We have created this reference architecture with accompanying sample code which can be configured and extended as per your requirements. However, it is up to the end user to utilize the code, make modifications and keep it maintained for productive use.

If you are using AWS IoT services for your own sensors, please follow the instructions here:

• GitHub Repo

Benefits

The business value and technical benefits of this integration are  the following:

• Detect machine issues before they occur with machine learning (ML) and take action to reduce operational costs.
• Start monitoring equipment in minutes with easy installation and automatic, secure analysis through the Amazon Monitron end-to-end system.
• Improve system accuracy continuously as Amazon Monitron learns from technician feedback entered in the mobile and web apps.
• Network security-focused design with SAP Private Link specifically for RISE with SAP customers between SAP BTP on AWS (any region) and SAP S/4HANA on AWS
• Event-driven integration architecture with SAP Advanced Event Mesh as a central hub.

Demo

The industrial equipment in Manufacturing plant is connected to Amazon Monitron that sends an event to SAP Advanced Event Mesh for abnormal condition detection and the Event to Business Actions framework process the event and enriches it will relevant business context using decision tables from SAP Build Process Automation and creates a maintenance notification in SAP S/4HANA.

In Closing

We hope this blog has given you a brief idea on how to integrate events generated from industrial equipment to trigger different business actions/workflows/process in SAP backend systems.

On the SAP side, Many thanks to Uma Anbazhagan from SAP for driving this topic by collaborating with all the stakeholders involved in the engagement, Swati Maste and Ajit Kumar Panda  for supporting the development of this solution, Madankumar Pichamuthu for enabling collaboration and finally Anirban Majumdar, PVN Pavan Kumar, Sivakumar N for leadership support for this project.

On the Amazon AWS side, Many thanks to Soulat Khan, Ganesh Suryanarayanan, Sunny Patwari, Renga Sridharan, Aiyappa Machanda, Abhik Ray, Suresh Pulivarthi, Krishnakumar Ramadoss and the SAP APN Partner Innovation team for their support in this project.

To learn more about SAP BTP, see the learning journey on SAP Learning called Discover SAP Business Technology Platform, a great introduction to BTP and the Intelligent Enterprise strategy to see what it’s all about for free.

As part of the global partnership between SAP and AWS, we have jointly developed an openSAP course titled “Build Resilient Applications on SAP BTP with Amazon Web Services 

[Registration link]  https://open.sap.com/courses/aws1

By joining this free openSAP course, you’ll delve into multiple Joint Reference Architecture patterns, gain in-depth knowledge of the architectural patterns and also have the opportunity to enhance your skills through hands-on exercises.

To learn more about Amazon AWS, visit AWS training

For more information about this topic or to ask a question, please contact us at [email protected]