Presented by, Timo Klingenmeier, General Manager, inmation GmbH & Co. KG
Industry 4.0 and the Internet of Things translate to new opportunities and new challenges for manufacturing corporations. The informed workforce requires access to vast amounts of data. Handling floods of data from the production floor across the organisation and in exchange with selected business partners is not a simple task, but when achieved it turns into a major competitive advantage. MongoDB’s strategic partner inmation has developed a middleware solution which combines intelligent industrial real-time connectivity with unlimited scalability and one uniform storage layer for all kinds of data structures – MongoDB.
Developer Data Modeling Mistakes: From Postgres to NoSQL
Mongo db iot_london_v0.1
1. IoT City Tour
Realtime Data – The Source of
Corporate Intelligence and Agility
Presentation
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30 Minutes to Cover
1. Some thoughts on Industry 4.0
2. Internet of Things vs. Industrial Control (and
practices)
3. The OPC specification in brief
4. Short round-trip through „Industrial Data“
5. Benefits of MongoDB being an universal data store
6. IoT City Tour
Industry
3.
x
Material
Flows
Source: https://chemicalparks.eu/system/files/attachments/file/14/European_Pipeline_Infrastructure__Networks.pdf
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Goal is the
“Smart Factory”
Further Computerization
of
Traditional Industries
The Internet of Things
Is Technological Foundation
Industry
4.0
Drivers
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Industry
4.0
Effects
End of Data Boundaries
for Individual Factories
Data Interconnectability
Between Sites Without
Geographical Restrictions
Enourmous Growth
of Production and
Supplier Networks
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Common Data Sources
SQL
Text/XML
NoSQL/Schema-flexible/BSON
OPC
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OPC: OLE for Process Control
OPC Data Access (DA) specification established
OPC Alarms and Events (A&E) specification established
OPC Historical Data Access (HDA) specification established
OPC Unified Architecture (UA) created
OPC UA 1.0 becomes available
First products based on OPC UA
OPC UA 1.01 becomes available
OPC UA 1.02
becomes available
1996 1998 2001 2003 2006 2007 2009 2013
Source: www.opcfoundation.org
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Teach yourself…
…and visit
www.opcfoundation.org
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Advantages
Data Type Flexibility
“Intrinsic” variants
“Intrinsic” arrays
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Sample Storage: Each (sub-second accurate)
measurement is stored as a “Micro-Document”
o
ObjectId points into another
collection which stores the
context information for this item
(e.g. measurement).
c
This is the distinct counter
relative to the value updates
which were received from the
external data source.
v
A value submitted by an external
(OPC) server, in whatever format.
q
The external quality (bit mask).
t
The original timestamp taken from
the external server.
h
The timestamp of the historization
process (and machine).
Advantages
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Sample Storage: Different data types can be stored in the same
Advantages “value” field:
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Summary
MongoDB is the perfect fit for Industrial Big Data
• It has the performance and the scalability options
required to store hi-freq data in huge amounts
• Timestamp accuracy is sufficient
• Schema (-less) flexibility fits the variant data structures,
originated in (OPC) source systems
• BSON is not only about storage, but also transport
• Unbeatable value offer (both software and hardware
utilization)
• It exposes ‘natural’ data structures which simplify any
kind of further analysis
• Choose between private and public cloud storage
(Slide) Industries – Is that familiar to you?
Based on some ‘polaroids’ pitching up on the screen showing diverse types of typical process industries, we will set the context for the applications between Control and Enterprise Management, which are then discussed throughout the talk.
[Quiz: How many distinct information items are available from a single, 6MW wind turbine each second?]