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Smart data: IoT analytics for manufacturing and process industries

The Open Cloud – Apps in the Cloud 

Smart Data

Based on my discussions at Messe Hannover , this blog explores the potential of applying Data Science to manufacturing and process control industries. In my new course at Oxford University (Data Science for IoT) and community (Data Science and Internet of Things ), I explore application of predictive algorithms to Internet of Things (IoT) datasets. 

The Internet of Things plays a key role here because sensors in machines and process control industries generate a lot of data. This data has real, actionable business value (Smart Data). The objective of Smart data is to improve productivity through digitization. I had a chance to speak to Siemens management and engineers about how this vision of Smart Data is translated into reality

 

When I discussed the idea of Smart Data with Siegfried Russwurm, Prof. Dr.-Ing. - Member of the Managing Board o... ,  he spoke of key use cases that involve transforming big data into business value by providing context, increasing efficiency  and addressing large, complex problems. These include applications for Oil rigs, wind turbines and process control industries etc. In these industries, the smallest productivity increase translates to huge commercial gains.  

This blog is my view on how this vision (Smart data) could translate into reality within the context Data Science and IoT.


Data: the main driver for Industrie 4.0 ecosystem

 At Messe  Hannover, it was hard to escape the term ‘Industry 4.0’ (in German – Industrie 4.0). Broadly, Industry 4.0 refers to the use of electronics and IT to automate production and to create intelligent networks along the entire value chain that can control each other autonomously. Machines generate a lot of Data. In many cases, if you consider the large installation such as an Oil Rig, this data is bigger than the traditional ‘Big Data’.  Its use case is also slightly different i.e. the value does not like in capturing a lot of data from outside the enterprise – but rather in capturing (and making innovative uses of) a large volume of data generated within the enterprise.  The ‘smart’ in smart data is predictive and algorithmic. Thus, Data is the main driver of Industry 4.0 and it’s important to understand the flow of Data before it can be optimized

The flow of Data in the Digital Enterprise

The ‘Digital factory’ is already a reality. For instance,  Industrial Ethernet standards like Profinet, PLM(Product lifecycle management) software like Teamcenter  and Data models for lifecycle engineering and plan management such as Comos. To extend the Digital factory  to achieve end-to-end interconnection and autonomous operation across the value chain (as is the vision of Industry 4.0), we need a component  in the architecture.  

The Open Cloud: Paving the way for Smart Data analytics

In that context,  the cooperation of Siemens with SAP to create open cloud platform. Is very interesting. The Open Cloud enables ‘apps in the cloud’  based on the intelligent use of large quantities of data. The SAP Hana architecture based on in-memory, columnar database provides analytics services in the Cloud. For instance, the "Asset Analytics"(to increase the availability of machines through online monitoring, pattern recognition, simulation,  prediction of issues) and  “Energy Analytics" ( revealing hidden energy savings potential)

Conclusions

While it is early days, based on the above, the manufacturing domain offers real value and tangible benefits to customers. Even now, we see the customers  who harness value from large quantities of Data through predictive analytics stand to gain significantly. I will cover this subject in more detail as it evolves. 

About the author

Ajit''s work spans research, entrepreneurship and academia relating to IoT, predictive analytics and Mobility. His current research focus is on applying data science algorithms to IoT applications. This includes Time series, sensor fusion and deep learning.  This research underpins his teaching at Oxford University (Big Data and Telecoms) and the City sciences program at the Technical University of Madrid (UPM). Ajit also runs a community/learning program through his company - futuretext for Data Science and IoT

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