Smart XXXX: What does it mean!!!

So often today you hear the word “smart” put on the front of a segment describing the transformational program encompassing many of the Internet of Things concepts.

Smart Cities, Smart Farms/ Agriculture, Smart Airports, Smart Plants, Smart Fields etc.

Are they different or do they all come down to a basic set of concepts, transformations that are applied to that industry to significantly shift the needle in operational efficiency?

 Fair question, and so often lately I am being asked what is the difference between IT/OT, IOT, and Smart xxx? So I thought it was worth a discussion, as I suspect there different interactions.

To me the discussion of “smart/intelligent” industrial it is all about achieving “operational Optimization/ Excellence”, to suite the required production at the most effective time, cost. This is a shift from time based production and managing the process to managing the production of product/service. Driving the optimized execution of work / actions on operational processes for that product/service delivery.

At the core it is about changing the way in which we manage and execute work tasks, either automated or actions with human intervention so that only required work is performed at the correct time.  

“Smart Strategies” are fundamentally different from current IoT, Big Data etc. thinking:

• The IoT, Big Data etc. Initiatives/trends can be characterized as offering the 5 “any’s” – any information, in any context, at any time, to any user, for any action
• “Smart” products and operations can be characterized as offering the 5 “right’s” – the right information, in the right context (operations situation), at the right time (which is often earlier than “real-time”), to the right users for the right actions (which are often preventative and at best prescriptive).

All fundamental on the journey towards “operational excellence.”

That said “Smart Strategies” will employ the services of IOT, and big data, but the key is “Smart” is about tightening the execution of an operation process relative to the current product delivery expectations. A key concept is that the Operational Process, (no matter if it is in a city, airport, or production line) understands:

•        What it is expected to deliver in characteristics of product or service, and when
•        It is “self-aware” of it’s condition and ability to deliver that product/ service, due to capability, materials and the situation it is in.
•        It is able to then request and interact with other process, applications, assets and people to gain the required actions needed to succeed and when. 

This is a transformation from just understanding it is taking control of the process, as opposed to time schedule actions.

Real time information Platform vs. traditional historian, Why it is Key to Pushing “Actionable Decisions”, foundational to the “Industrial Internet of Things” and Empowering the Teams.

Again last week I was presenting to a set industrial companies in water, food, and mining, and the topic of a "real time information platform" many questions.

My immediate answer is “what are you trying to do? " " who are the users targeted to interact with the system, and what decisions and actions are they expected to take?". These last two questions usually leave a complex blank expression on people's faces.

Many are engineers who have been asked to investigate, and they centered on the traditional approach of a "data centric" historian centered  world, leading with a technology strategy. The question of what people will use the data for, what roles and actions to be taken are secondary in their minds! 

Why is this when if someone had wanted a "historian" they would have asked for it. So why a platform, what does real time mean, and key is information.

It all comes back to one of the quadrants we talk about in the "operational transformation" around networking a series of assets, plants into a a "trusted" information system. That "actionable decisions" can be taken by a ever increasing community of operational people across the operational landscape.

To me it is understanding this community of consumers and what their requirements, uses are is key:

1. What activities, decisions, and actions they are expected to take?
2.  Their roles, skills, and approach is their time frame, location relative to the data
3. Their context and understanding of the plant, asset or process in question, as their is a growing trend of highly educated skilled people on assets, process. With little or no practical experience on the asset, and more than likely will not have visited site.

On investigations you find you have the traditional process engineers, who need the trend analysis and discovery of potential improvements. 

However, there is a growing tribe of people who need to make actionable operational decisions. They will not monitor the system must best "self-aware, and living" (exception based) capture the data, transformation  it into information.  Apply experience and knowledge, clear understanding of the situation, and what are typical actions with "best operational process" provided to take action.

This is very different to everything getting data stored and then extracted, yes in this new world there is history as it provides the history for reliable knowledge and basis for wisdom or " application knowledge".

The real key is the change in approach from “predictive to prescriptive” which embeds the “actionable decisions into the model. Empowering the operational team, no matter the location or experience with decisions and associated actions.

Understanding this maturity curve and evolution is what we see as foundational to the success of “industrial Internet of Things”. Through the embedded practices provides a basis for the changing workforce to act and make decisions in a timely manner.

However, these two communities in the industrial landscape are interlocked for success. The two communities are:

• Community 1: Process, performance, optimization team that accesses the data with trending, analysis, and predictive tools. Identifying the trends, conditions by applying their experience combined with “big data” techniques allows these conditions, to be seen in the “to be state”. If captured in a managed configuration framework, that will allow roll-out over sites and sustainable evolution. These become embedded into the system, for adoption by the operational team.

• Community 2: Operational Team: This is the dynamic team, from roaming people on the plant to central operational teams, to virtual expert teams, collaborating together in real time to enable “actionable decisions” no matter role, location, and experience.

The diagram below shows the this maturity of capturing this “applied knowledge” as Managed “Actionable Discussions” that interact with people, assets and process as key, very different a traditional historian approach.

The “Real Time Information Platform” provides a real-time "living" model that is self-aware that captures validates the data with rules aware of it is current state. Storing this data in context and rules and calculations in that provide motivation, embedded operational process, and awareness to correct people. Fundamental is the "trust" worthiness of the information, without impacting current automation systems. The ability to have sustainable evolution and scalability, through managed components that represent the assets and processes (actionable decisions) to the model is available on storage side in history and real-time.

You cannot do this with Historian (data centric) architecture and solution. Make sure you looked at who the communities of users you are satisfying now and in the immediate future?