Real-time Value of Data: Siemens MindSphere & IBM Red Hat Collaboration

Shorten Time to Value and Reduce IT Complexity for Manufacturing in Private Clouds

Customers embarking on their digitalization and IoT journey can now choose from the public cloud and private cloud deployment options for MindSphere, Siemens’ industrial IoT as a service solution. Siemens plans to leverage IBM Hybrid Cloud capabilities based on Red Hat OpenShift for the new private cloud offering.

As the world becomes increasingly connected, digitalization – using digital technologies to transform business and manufacturing operations – is a key differentiator that will enable companies to remain competitive. Digitalization promises lower costs, improved production quality, flexibility and efficiency, shorter response time to customer requests and market demands, and opens new and innovative business opportunities. Turning data into value is a critical success factor.

MindSphere is the leading industrial IoT as a service solution that collects and analyzes real-time sensor data

Take condition monitoring as an example, which requires analytics for manufacturing equipment to ensure productivity and availability of production at any time; smooth operation of machines in production environments is the key. Early detection of upcoming faults is essential for optimized condition-based maintenance plans.

A typical manufacturer on his digitalization journey must address several avenues before he will get the return on investment and intended benefits. Typical challenges include how to handle the volume of required machine data and the data collected through connecting to automation systems or adding special sensing equipment. Then this data needs to be stored, analyzed to build monitoring models, or used through AI-driven anomaly detection approaches.

Data is specific to operation domains coming with high-frequency, big volume, and industry domain-specific formats. This specificity has been one factor in preventing IT groups from gaining insights into this data over the last decade. Another challenge is the global distribution of manufacturing or operations sites and their remote locations. Typically manufacturing sites are placed close to resource supply (e.g. mines, close to water plants), or as far away as rural or residential areas. Internet bandwidths were not a driver in the past for a factory site and therefore available internet bandwidth is often very limited and used for outbound business transaction workloads.

A Simple Example Calculation Can Help to Understand that Challenge.

Let’s assume, at a larger manufacturing site, one wants to collect and analyze data of 1000 sensors (1 data set per second with 10kB raw data) over a correlation time window of 1 month. Then one must deal with data speed and volume together defining the raw cloud ingress bandwidth for time series only, requiring:

  • Cloud uplink network bandwidth = 1000 x 8x10kB x 1/s = 80 Mbit/s
  • Data volume to compute/ day = 80 Mbit/s /8 x 3600 x 24 = 864 GB/day
  • 30-day storage capacity = 864 GB/day x 30 = 26 TB/month

The required uplink bandwidth could be a limiting factor for public cloud-based deployments (lack of network bandwidth or telco cost). IoT workloads have a 24/7 nature, so the IoT solution must be available as well on a 24/7 basis, which stresses the service management team and impacts cost. Hence a combination of a private cloud with a turnkey IoT solution continues to be a big desire across many industry verticals.

Furthermore, multiple industries require local private cloud solutions to meet regulatory requirements, such as what is typically found in Utilities, Government, and Defense verticals. Besides the technical hurdles, one also must cope with specific regulations and security to incorporate and certify. E.g. in the US regulatory compliance with ITAR or FEDRAMP is easier to achieve, or do not apply like FEDRAMP for full on-premise private cloud.

Through the advent of industrial IoT in the industry, manufacturers can now make use of commercially provided industrial IoT solutions. Siemens’ MindSphere is the leading industrial IoT as service solution that collects and analyzes real-time sensor data from products, plants, systems, and machines, enabling users to optimize products, production assets, and manufacturing processes along the entire value chain to build a real-time digital twin.

Siemens invests in industrial IoT and offers MindSphere to help customers on their journey. The Siemens customer experience shows that using pre-built IoT solutions has advantages compared to a build-your-own IoT solution from scratch:

  • 60% shorter time to value
  • 25% less OPEX
  • 40% less CAPEX
  • 90% risk reduction in the overall project

Siemens already offers a MindSphere SaaS-based industrial IoT offering at global scale:

  • Powerful applications and solutions giving customers access to direct value through MindSphere application and solutions covering all aspects of Smart Factory both for OEMs and equipment manufacturers. Some specific solutions include Remote Service and Condition Monitoring, Energy Management, and Preventive Maintenance.
  • Open interfaces for application development to help customers and partners build and integrate their own software applications and services, MindSphere delivers open application programming interfaces (APIs) and development tools. With Mendix and low-code, customers can deploy software applications in hours or days instead of weeks and months.
  • Secure communications with MindSphere. As the level of digitalization increases, so does the importance of comprehensive security concepts for applications. With defense-in-depth, Siemens provides a multi-layer concept on security, network security, and system integrity as recommended by ISA 99/IEC 62443 and IT Security oriented to industry-standard ISO 27001/BSI.

A new Siemens offering, the MindSphere Private Cloud solution for enterprise customers, comprises additional value propositions, besides the known SaaS-based IoT solution capabilities:

  • Time to value for local on-premise deployments
    • Shortest possible deployment and setup time
    • Immediate focus on IoT solution instead of IT project
  • Efficient long-term operations
    • Managed services guarantee availability of private cloud in the sync life cycle with SaaS offering including long-term delivery concepts
  • Total cost of ownership (TCO)
    • Transparency and predictability from the start for private cloud

The MindSphere Private Cloud solution is the result of a joint initiative among Siemens Digital Industries Software, IBM, and Red Hat. Siemens is bringing MindSphere as the industrial IoT and analytics solution, and IBM the hybrid cloud experience, built on Red Hat OpenShift, to extend the deployment flexibility of MindSphere. This will enable customers to run MindSphere on-premise, simplifying local, regional, and regulatory constraints, unlocking speed and agility in factory floor operations.

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