“Gather all the plant data and analyze afterwards” are common words you hear about the market, but when the discussion happens this approach a “putting head in the sand” approach, with limited bigger picture consideration. Today the key to agility is empowerment of decisions and actions in the NOW. This does not require data it requires trustworthy, in context information. The last couple of weeks has enabled some fascinating and productive engagements. In a discussion, last week at a Mining Thought leadership on the future a sizable group of interested people attended and took part in discussions.
A
key concept of “mine of the future” and actually for most industries oil and
gas, power, food etc. is the agility to take more holistic operational view of
the system and day to day operations. This requires alignment at 3 loops (the
diagram illustrates these loops) of operations with the alignment in decision
and actions. Foundational to this is the information that decisions are based
on, requires not HISTORIANS but Plant/ Operational Information Systems, that
align information and actions for effective use my different operational roles.
Companies that make this foundational move will have a system where data
structure, validation is “managed” not coded, that the system is trust worthy
so people will depend on and use the system.
To many times the discussion with mining and process end users
who are implementing an information system for increased decisions support,
that they require a re look at the data sources and how to put it in context,
and validated. An example of this was a coal company in South Africa they had
spent significant time working on an information system and the historians and
data warehouses, but lost effectiveness through:
- Data alignment across
sources, E.g.| Finding different data streams that effected the same asset
calculation for say energy.
- Data validation
- Data structure
The conversation remarkably quickly ended up going back to
redo of the structure of data coming into the historians, and getting this data
structured, validated before it went into historian. They had two choices
either going to source in this case PLCs and adjusting the running code (not a smart
idea), or put a structuring layer in which would structure the data, validate
the data, and provide high availability and single names space to manage over
the distributed historians.
This is a departure from the story he was told that just put
a historian in and capture the data worry about analysis afterwards, that is
old and in effective saying. As discussed in the “mine of the future”
discussions the challenge is to “federate”
the existing data sources on a plant, E.g.| Historians, alarm event data logs,
operator logs, and delay, downtime data bases, E.g.| The alignment of the data sources
into effective information that actions can be taken. The concept of “self service”
becomes necessary, as there was a lot of comment around of trying to minimize
the process analysis phase and role in the data, and try to get effective
information to operational people quickly. Another example is an oil and gas
plant’s decision system that is effectively been run 24 hours out of phase with
the plant, by only have decision able reports/ dashboards from the past 24
hours at 2 to 3 in the afternoon so. Again this delay was due to data
gathering, data alignment, validation, in MS Excel manually done by 3 people,
the company was exploring ways to eliminate this manual creation, so the whole
process is “near real time”.
A
clear message from the last couple of weeks is we need to step back, align the
existing systems, to provide that key foundation for operational empowerment, absorb
significant milestones such as advancement in the communication infrastructures;
Example putting 4G communications in the Pilbra mining area (remote north
western Australia), providing significant data capability. (A topic for next
week). This need to absorbed into the industrial / operational Architecture,
internet will be a natural part of the backbone, leveraging computing power
remotely for functions, such as storage, analysis, model running, help accelerate
the decision support. 
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