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At the recent Siemens Innovation Day held at its Munich, Germany headquarters, the company showcased MindSphere, its cloud-based, open operating system for the Industrial Internet of Things (IIoT). MindSphere is one of several industrial operating system platforms in the marketplace that end users and OEMs are evaluating looking for differentiated features and technologies to help their enterprises meet the challenges of increasing productivity and profitability while addressing growing global competitive pressures. Although technological advancements are important factors in the evaluation, end users and OEMs also seek solutions that provide an ecosystem that best leverages and optimizes their existing assets while increasing the integration of automation with other enterprise applications.
Siemens defines MindSphere as a scalable cloud platform as a service (PaaS) where apps and digital services can be developed and deployed, with data analytics and connectivity capabilities, tools for developers, and a wide range of applications and services. MindSphere is designed to help manufacturers improve the efficiency of plants by recording and analyzing large volumes of production data, and providing a foundation for applications and data-based services from Siemens and third-party providers in the areas of, for example, predictive maintenance, energy data management, and resource optimization. MindSphere also offers customers a development environment in which they can integrate with their own applications and services.
MindSphere is designed to collect large amounts of raw data, analyze that data through a range of apps, transform that data into knowledge and information, and leverage that newly created knowledge and information to continuously optimize a manufacturer’s production assets and business key performance indicators. This knowledge and information impacts decisions regarding resource usage, predictive maintenance, process and product design, and system performance and availability. This enables MindSphere users to create new data-driven services that can be also be provided to the users own customers, such as a machine OEM selling remote monitoring, maintenance and performance management services along with the machine.
The MindSphere ecosystem provides a range of applications for different purposes and usages, known as MindApps. These apps can be created by Siemens, OEMs, end users or by partners. MindApps are designed to provide asset transparency and analytical insights, such as predictive maintenance, and can follow a subscription based pricing model. This enables Siemens customers and partners to develop their own applications on the platform as well as use and operate them to facilitate new digital services focused on, for example, increasing machine availability, optimizing resource usage, and increasing productivity. The success of customer-owned apps is typically directly related to the success of the Application Programming Interfaces (API) for development. The MindApps API characteristics are optimized for industrial IoT app development with additional reusable supporting modules, such as analytics and visualization modules. An upcoming MindSphere App Store will provide ready to use applications.
Connecting machines, plants and systems to MindSphere is done via Siemens MindConnect, which provides secure and encrypted data communication to industrial assets. MindConnect offers plug and play connectivity to Siemens products, and leverages open standards, such as OPC UA, for connectivity to a wide number of non-Siemens automation products. MindConnect includes dedicated IoT Gateways, such as MindConnect Nano and MindConnect IoT 2000. MindConnect Nano is a pre-configured Industrial PC that supports transmission of data encrypted through a secured internet connection to MindSphere. Supporting protocols include Siemens S7 PLCs and OPC UA. The MindConnect IoT 2000 is an open platform for collecting, processing and transferring data in the production environment, acting as gateway between the cloud or the company IT level and production. It also transfers analyzed data from the cloud to the production control. This continuous data communication helps to close the control loop for optimization of production.
One of the many questions that end users and OEMs have regarding MindSphere is how does one practically get started. Siemens demonstrated that it takes just a few steps to get started with MindSphere to create new data-driven services. The first step to get connected is to set up a MindSphere user account, where the end user or OEM will receive and integrate a connector box into their machine or equipment. The next step is to configure the data acquisition, connectivity and visual analyzer via MindSphere. The final step is to run the service, monitoring, for example, the health status of all assets in MindSphere with its fleet manager app and drill into details using its visual analyzer tool.
Maybe the most important thing that predicts how well an operating system platform will be accepted in the marketplace is the size of its ecosystem. Siemens has created a partner network for MindSphere that includes companies, such as Microsoft, IBM, SAP, Accenture, Atos, and Evosoft. Examples of these partnerships include Siemens and IBM to bring Watson Analytics to MindSphere, which entails a planned integration of IBM's Watson analytics and other IBM analytics tools, with access to analytics through visualization and dashboards, and IBM's analytics technologies for data analysts via APIs. Also, Siemens plans to make MindSphere available on Microsoft's Azure cloud platform during 2017. As part of the collaboration, Siemens customers who develop and make available their apps in the public cloud will be able to choose between Microsoft datacenters in different locations around the world. With the Azure Stack, the customer can also utilize Azure services within their own datacenter. In addition to Java, JavaScript and Python, plans are in place for MindSphere to also support .NET applications in the future, which will allow .NET developers to leverage existing applications and expertise when developing new MindSphere apps.
Siemens Innovation Day clearly demonstrated how Siemens is evolving its product and solutions portfolio for the shift to Industrie 4.0. Siemens also left no doubt to attendees about its commitment to its digital transformation efforts and the MindSphere operating system platform. By leveraging advanced analytics, such as predictive, prescriptive and cognitive, end users and OEMs can utilize MindSphere to help increase operational performance and reduce downtime by bringing intelligence to production equipment to help predict anomalies and failure patterns and to initiate corrective measures. It also helps to improve product quality and yield using quality analytics that helps to detect the conditions that contribute to process failure and quality issue. These digitalization technologies will add tremendous value to electrification and automation, which is the basis of Siemens’ digital business. ARC left Innovation Day with the impression that Siemens is on the correct strategic path with MindSphere.
Siemens defines MindSphere as a scalable cloud platform as a service (PaaS) where apps and digital services can be developed and deployed, with data analytics and connectivity capabilities, tools for developers, and a wide range of applications and services. MindSphere is designed to help manufacturers improve the efficiency of plants by recording and analyzing large volumes of production data, and providing a foundation for applications and data-based services from Siemens and third-party providers in the areas of, for example, predictive maintenance, energy data management, and resource optimization. MindSphere also offers customers a development environment in which they can integrate with their own applications and services.
MindSphere is designed to collect large amounts of raw data, analyze that data through a range of apps, transform that data into knowledge and information, and leverage that newly created knowledge and information to continuously optimize a manufacturer’s production assets and business key performance indicators. This knowledge and information impacts decisions regarding resource usage, predictive maintenance, process and product design, and system performance and availability. This enables MindSphere users to create new data-driven services that can be also be provided to the users own customers, such as a machine OEM selling remote monitoring, maintenance and performance management services along with the machine.
The MindSphere ecosystem provides a range of applications for different purposes and usages, known as MindApps. These apps can be created by Siemens, OEMs, end users or by partners. MindApps are designed to provide asset transparency and analytical insights, such as predictive maintenance, and can follow a subscription based pricing model. This enables Siemens customers and partners to develop their own applications on the platform as well as use and operate them to facilitate new digital services focused on, for example, increasing machine availability, optimizing resource usage, and increasing productivity. The success of customer-owned apps is typically directly related to the success of the Application Programming Interfaces (API) for development. The MindApps API characteristics are optimized for industrial IoT app development with additional reusable supporting modules, such as analytics and visualization modules. An upcoming MindSphere App Store will provide ready to use applications.
Connecting machines, plants and systems to MindSphere is done via Siemens MindConnect, which provides secure and encrypted data communication to industrial assets. MindConnect offers plug and play connectivity to Siemens products, and leverages open standards, such as OPC UA, for connectivity to a wide number of non-Siemens automation products. MindConnect includes dedicated IoT Gateways, such as MindConnect Nano and MindConnect IoT 2000. MindConnect Nano is a pre-configured Industrial PC that supports transmission of data encrypted through a secured internet connection to MindSphere. Supporting protocols include Siemens S7 PLCs and OPC UA. The MindConnect IoT 2000 is an open platform for collecting, processing and transferring data in the production environment, acting as gateway between the cloud or the company IT level and production. It also transfers analyzed data from the cloud to the production control. This continuous data communication helps to close the control loop for optimization of production.
One of the many questions that end users and OEMs have regarding MindSphere is how does one practically get started. Siemens demonstrated that it takes just a few steps to get started with MindSphere to create new data-driven services. The first step to get connected is to set up a MindSphere user account, where the end user or OEM will receive and integrate a connector box into their machine or equipment. The next step is to configure the data acquisition, connectivity and visual analyzer via MindSphere. The final step is to run the service, monitoring, for example, the health status of all assets in MindSphere with its fleet manager app and drill into details using its visual analyzer tool.
Maybe the most important thing that predicts how well an operating system platform will be accepted in the marketplace is the size of its ecosystem. Siemens has created a partner network for MindSphere that includes companies, such as Microsoft, IBM, SAP, Accenture, Atos, and Evosoft. Examples of these partnerships include Siemens and IBM to bring Watson Analytics to MindSphere, which entails a planned integration of IBM's Watson analytics and other IBM analytics tools, with access to analytics through visualization and dashboards, and IBM's analytics technologies for data analysts via APIs. Also, Siemens plans to make MindSphere available on Microsoft's Azure cloud platform during 2017. As part of the collaboration, Siemens customers who develop and make available their apps in the public cloud will be able to choose between Microsoft datacenters in different locations around the world. With the Azure Stack, the customer can also utilize Azure services within their own datacenter. In addition to Java, JavaScript and Python, plans are in place for MindSphere to also support .NET applications in the future, which will allow .NET developers to leverage existing applications and expertise when developing new MindSphere apps.
Siemens Innovation Day clearly demonstrated how Siemens is evolving its product and solutions portfolio for the shift to Industrie 4.0. Siemens also left no doubt to attendees about its commitment to its digital transformation efforts and the MindSphere operating system platform. By leveraging advanced analytics, such as predictive, prescriptive and cognitive, end users and OEMs can utilize MindSphere to help increase operational performance and reduce downtime by bringing intelligence to production equipment to help predict anomalies and failure patterns and to initiate corrective measures. It also helps to improve product quality and yield using quality analytics that helps to detect the conditions that contribute to process failure and quality issue. These digitalization technologies will add tremendous value to electrification and automation, which is the basis of Siemens’ digital business. ARC left Innovation Day with the impression that Siemens is on the correct strategic path with MindSphere.