How Siemens Energy uses AWS for its IIoT platform and smart manufacturing

Introduction

Siemens Energy is one of the world’s largest energy technology companies with world-class manufacturing facilities across the globe. Siemens Energy leverages Amazon Web Services (AWS) capabilities to enhance the efficiency and sustainability of its factory shopfloor operations. The company is at the forefront of driving the global energy transition by providing innovative technologies and data-oriented services and applications that optimize the design and production of equipment for energy generation, storage, transmission, and utilization. Siemens Energy is empowering its factories to achieve greater efficiency and sustainability through a standardized approach of integrating Internet of Things (IoT) data from physical assets while consolidating and structuring the data using AWS native services. This enables citizen-developers or Operational Technology (OT) personnel to leverage the data to create individual and customized factory use cases.

In this blog, we explore how Siemens Energy leverages AWS for their IoT Connected Factory Platform, which collects, structures, and analyzes data from different manufacturing assets. This integration provides a comprehensive interface for factory operators to monitor their production process, monitor energy usage, and predict maintenance needs in a smart, efficient, and proactive manner.

Challenges

For Siemens Energy, each factory and production line operated with different procedures, methods, and machinery. This presented a host of unique challenges:

• There was no standard IoT solution across all sites, just isolated proof of concepts in a few. The complexity is amplified by the presence of multiple machine connectivity and data aggregation applications that ends up being isolated data silos.
• Multiple sites are large brownfield environments with assets that have over ten different machine data protocols. Integrating data from such an environment further complicates efforts to create a cohesive and efficient system.
• Ensuring that security is built-in from the ground up adds another layer of difficulty, as it requires robust solutions to protect a diverse array of devices and protocols from potential cyber threats.
• Siemens Energy needed the management of a platform to be orchestrated centrally. They wanted to use DevSecOps practices for faster deployment and rapid scaling with less operational overhead through automation.

Overcoming these challenges required a strategic approach to standardization, a seamless integration, and comprehensive security measures. The main goal is to achieve a secure, interconnected, efficient, and resilient operational environment using AWS managed services, specifically an IoT stack and native management tools for edge.

Solution Overview

The solution is deployed and updated from a central shared services AWS account into multiple individual factory AWS accounts. This approach allows for systematic updates and controlled deployment of new features, while ensuring that billing is accurately allocated to the appropriate cost centres.

Figure 1 – Siemens Energy factory account provisioning workflow

Upon receiving the hardware and ensuring it’s ready for setup, the factory user will request a customized image for the Industrial PC (IPC). The image will be installed in the Industrial PC with the help of a bootable USB stick requiring minimal user interaction. A set of temporary credentials is used to register the corresponding factory AWS account. The self-installation process ensures that the system is securely hardened and configured correctly before going online, to avoid compromising any OT system or data. When the IPC registers with service, an automation is triggered to install the required AWS IoT Sitewise components, turning the device into a fully functional SiteWise Edge Gateway, ready to securely ingest data from OPC Unified Architecture (OPC UA) data sources in less than 30 minutes. AWS IoT SiteWise is at the core of the solution. It allows Siemens Energy to implement use cases of conditioning monitoring, energy consumption monitoring and predictive maintenance using industrial data from multiple sources at scale, with common hardware building blocks. It also helps to organise the data from different types of factories with the same set of tools and a unique interface for analysis and monitoring.

To connect the diverse OT assets to the AWS IoT SiteWise Edge Gateway, Domatica EasyEdge integration with AWS IoT Sitewise was leveraged. Thanks to its easy-to-use and intuitive user-interface, the factories are able to collect data from legacy PLC protocols like Siemens S7, Modbus, and more with minimal configuration. The native integration between AWS IoT SiteWise and EasyEdge helps standardise the edge deployment on the factory floors, eliminating the need for third-party protocol converters. This significantly reduces complexity and onboarding time of the factory assets.

The Connected Factory platform also manages the lifecycle of the industrial gateways, including Operating System (OS) and component updates, using AWS Systems Manager. The lifecycle module can do periodic checks to report operating anomalies and compliance failures that could compromise the security of the system. This module runs at factory account level, but reports the results to the central account, to ensure clear visibility and quick escalations when needed.

Figure 2 – Siemens Energy Connected Factory Platform Architecture

Outcomes

After only six months into the project, Siemens Energy started rolling out the solution to the first few factories. Today, Siemens Energy connects and monitors a variety of assets, like large autonomous vehicles, robots, and Computer numerical control (CNC) machines across multiple factories (e.g., plants of switchgears and gas turbines). Thanks to this AWS Industrial IoT solution, the local factory teams are can identify anomalies in assets and processes, reduce non-conformance in parts and equipment, and speed up implementation of projects, which results in increased productivity.

Another key use case for Siemens Energy is energy consumption monitoring, and it is relevant for all sites and assets. Beyond power consumption, Siemens Energy is metering pressured air, heat, flow of water, and more. This use case is expected to contribute not only to significant cost savings, but also to Siemens Energy’s goal of becoming carbon neutral by 2030 in internal operations.

Overall, the IIoT use cases led to the following business outcomes so far:

1. Reduced the time of manual data collection by up to 50%.
2. Lowered OT asset maintenance efforts and costs by up to 25%.
3. Increased asset availability by up to 15%, impacting the bottom line.

Outlook and Conclusion

Looking ahead, Siemens Energy aims to further integrate artificial intelligence (AI) and generative AI (GenAI) into their IIoT platform to enhance the capabilities and efficiency of their smart manufacturing processes. By leveraging AWS services, Siemens Energy can implement advanced predictive maintenance algorithms, which can anticipate equipment failures before they occur, minimising downtime and reducing maintenance costs. The integration and continuous evolution of AI and GenAI into Siemens Energy’s IIoT platform will be the next significant step towards creating a more intelligent and efficient manufacturing environment.

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