Siemens and IBM Team Up to do What?

Siemens and IBM Team Up to do What?

It was just one of several announcement at Siemens’ Innovation Day in mid-December, but maybe the one with the greatest impact.  IBM and Siemens announced plans to include the capabilities of IBM’s Watson, an artificial intelligence service, in Mindsphere, Siemens’ platform for industry analytics.  While this looks like just another collaboration on the surface, it is actually a crucial one when we take into account future architectures of cloud-based software and services. 

In the near future, cloud-based eco-systems will run on platforms, such as MindSphere (Siemens), Predix (GE), Ecostruxure (Schneider Electric), Sentience (Honeywell), or Azure (Microsoft).  Looking at a representative sample of automation software, around 13 percent are already cloud-based, and we expect this portion to grow. 

In the more distant future, software functionality, such as FSM, GIS, PAM, PLM, ARS, SCP, TMS, HMI, and MES will be replaced by “micro services”. 

Micro services are an architectural pattern in IT, where complex application software are composed out of small programs / apps.  These small apps run in a cloud and are purchases as a service.  Micro services are:

• Small
• Decoupled from each other and independently deployable
• Communicate with each other
• use lightweight technology-agnostic protocols

   

   

This means that an end user can select software functionality on a best-of-breed basis, or by lowest cost micro services, all running on the same cloud platform.  For an end user, the result is a more tailored and streamlined solution.

Micro services will be offered primarily by automation suppliers, but they also open the door for OEMs and EPCs to serve the market, as they sometimes require deeper application know-how and experience.  Micro services leverage big data analysis and artificial intelligence, which is where IBM’s Watson comes into play.  Developer of apps and micro services use an application programming interface to access fundamental calculations for big data analysis, machine learning, and artificial intelligence.  Providers offering micro services do not require any special know-how.  Instead, they merely configure access to existing knowledge.  This simplicity is crucial for OEMs, which are often medium-sized companies with limited engineering resources.

The integration of IBM technologies will further ease the use of advanced analytics by providing visualization and dashboards for business customers and analytics tools via Application Programming Interface (APIs) for app-developers and data analysts,”

Currently IBM plans to offer three different analysis technologies: predictive analytics (“you will need to act in three weeks”), prescriptive analytics (“you need to change the oil in three weeks”), and cognitive analytics (“example of cognitive analytics here”).  Cognitive analytics is also context aware, so sticking with the examples above, the recommendation might be: “The weather is will stay warm for five weeks after next Thursday, so you should change the oil in your convertible now”. 

To make MindSphere more attractive, Siemens already announced that the platform will be used globally within the Siemens organization, which will expand coverage from industry to also include energy, building technologies and healthcare.  This increased scope should make the offering more attractive to partners, such as IBM, which offers the fundamental analysis for micro services. 

Keywords: Artificial Intelligence, Cloud-Based Software, Automation Software, Big Data Analysis, Advanced Analytics, ARC Advisory Group.