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MindSphere

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As an industrial IoT as a service solution, MindSphere collects and analyzes all kinds of sensor data in real time. This information can be used to optimize products, production assets and manufacturing processes along the entire value chain. MindSphere’s open application interfaces make it possible
147:). MindSphere stores operational data and makes it accessible through digital applications (“MindSphere applications”) to allow industrial customers to make decisions based on valuable factual information. The system is used in applications such as automated production and vehicle fleet management. 187:
MindSphere is based on the concept of closed feedback loops enabling the bi-directional data flow between production and development: Real-world plants, machines and equipment can be connected to MindSphere in order to extract operational data. Valuable information (i.e.,
192:” of machines) can then be extrapolated from the raw data through analytics and utilized to optimize products as well as production processes and environments in the next cycle of innovation. 180:
To help customers create their own software applications and services, MindSphere is equipped with open application programming interfaces (APIs) and development tools. This allows
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Dowling, Michael; Eberspächer, Jörg; Neuburger, Rahild; Noll, Elisabeth; Zisler, Kristina. (2016) Neue Produkte in der digitalen Welt. Books on Demand.
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Schmalz, Kurt; Winter, Albrecht. (2016) “Trends in Vacuum Technology and Pneumatics in the Context of Digitalization”. qucosa.de. Retrieved 2017-10-09.
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Assets can be securely connected to MindSphere with auxiliary MindSphere products that collect and transfer relevant machine and plant data.
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Weinländer, Markus. (2017) Industrielle Kommunikation: Basistechnologie für die Digitalisierung der Industrie. Beuth Verlag. pp. 59-60.
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Examples include real-time telemetric data from moving assets like cars, time series data and geographical data, which can be used for
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Weinländer, Markus. (2017) Industrielle Kommunikation: Basistechnologie für die Digitalisierung der Industrie. Beuth Verlag. pp. 56.
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Reinheimer, Stefan. (ed.) (2017) Industrie 4.0: Herausforderungen, Konzepte und Praxisbeispiele. Springer Verlag. p. 26.
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Naujoks, Stefanie. “MindSphere – Siemens cloud for industry: What is it all about?” pac-online.com. Retrieved 2016-05-09.
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Williamson, Jonny. (2017) “Mindsphere: the next step in digital factories”. themanufacturer.com. Retrieved 2017-09-04.
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to obtain data from machines, plants or entire fleets irrespective of the manufacturer. These interfaces include
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August 2017 – End of closed beta phase and release of MindSphere Version 2.0
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The Web at Graduation and Beyond: Business Impacts and Developments
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Dillon, Stuart; Schönthaler, Frank; Vossen, Gottfried. (2017)
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for applications in the context of the Internet of Things (
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January 2018 – Release of MindSphere Version 3.0 on
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June 2023 – Mindsphere is now known as Insights Hub
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Index

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promotional content
external links
neutral point of view
Learn how and when to remove this message
Original author(s)
Siemens
Developer(s)
Siemens
www.mindsphere.io
IoT
Siemens
IoT
predictive maintenance
OPC Foundation
OPC UA
OEMs
digital twins
AWS
Microsoft Azure
Alibaba Cloud
Internet of Things
Industry 4.0





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