2012 saw the rise in what I call “Industrial Information
Systems, Projects”. You may say “rubbish”, the whole historian, and information
business has been around for years, and the answer is true. Today these
projects are different dealing with a “lake of data”, delivering to more
people, of different roles typically not even aware of what an historian is drawing
data from many different sources including historians, xml files, transactional
data sources such as MES and Batch systems, alarm, event systems, MS Excel and
customer odd databases, as well real-time data. There is no one supplier, one source,
or structure to this data. The challenge is when the context and knowledge of
the data is retiring from the companies, but the size of internal community of
roles and workers requiring access is increasing. How often I have been asked
and discussed the issue of data validation and data awareness, vs architecture,
and technologies at tossed into conversation hoping for a “silver bullet”, but
I believe the solution comes with new capabilities like “Big Data” but also evolutions
in existing industrial implementations, with a more holistic design!
I believe the growth will accelerate in “Industrial
Information Systems, Projects” during 2013, and beyond, but this is not about
delivering reports and information, it is about “empowering” the increased community
in business in making real-time decisions, based on real-time trustworthy, effective
industrial information, no matter their location. I continue to get surprised
by the notion that the solution is an Enterprise Historian on top of the existing
system, acting as a data warehouse. I ‘Scratch my head” and usually “ask how to
you know the data is valid, in context, and comparable. Too often it is a blank
look they were lead to believe the data in or supplied from their SCADA, lower
level historians, etc. is the only thing they need to access. Key to
understanding is the ability to detect patterns, across data, but there needs
to be enough context to allow the evolving big data tools to enable detection
of patterns.
Last week this blog discussed exception based “self aware” models
required in today’s proactive operational/ supervisory systems, especially as
devices grow in intelligence capability. This model is also key to putting
things in context enough to enable this analysis and patterns to be seen way
further than process analysis. Big data concepts of pattern analysis, save that
pattern, and now have it as auto detect on a similar pattern happening again,
triggering an operational process that will continue a proven procedure to
resolution, guiding the workers involved interacting in a consistent and pro
active manner with the objective for early detection and fast resolution. This automatic
pattern recognition, detection, and embedded procedure are one key aspect of
the modern situational awareness concept. Building on last week’s blog concepts
of the “self aware” model, if these smart devices and processes include a
pattern recognition capability as part of the “self” intelligence, the shift is
a response from the “as is” status to the ‘to be”. The diagram below shows a significant
opportunity for improvement with the two “value of early corrective action” lines effectively illustrating the value gain in
early detection and pro active correct action.
The diagram illustrates how a condition over time “x axis”
changes in cost/ value through time, and how the traditional alarm systems are
in the “as is” state, and the whole objective to “SITUATIONAL AWARENESS” is to
shift to the “to be “ state.
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