Operational Manufacturing Interface (OMI) vs Human Man Interface(HMI) or SCADA

Over the last year, I have visited many sites, discussed with many peers the evolution of the Operational Experience in the Industrial Landscape. But over and over again I find myself in the much debate on the role and capability, as usual this is not anybody being incorrect it is a miss communication more often than not.

The traditional industrial user experience which has been owned by the Human Man Interface (HMI) or DCS workstation, where people control, monitor and interact with the process in a focused way. So in these discussions people use the HMI, but I find myself questioning what experience are they targeting or describing. More than often I pull up the diagram below to provide a reference for Industrial Operational Experience of today.

 An HMI for a process cell with a narrow focus is very different to the Operational Interface used in an Integrated Operational Center, and very quickly people see the different.

This does not mean the Time of the HMI is over, I fundamentally think it does it's job well, at the focused point at which a process cell and the human come together in a simple, clear and concise experience at a reasonable process to set up and sustain.

But as you move to the right of this diagram, increasing reason-ability, increased scope of control, increased value in decisions. No longer can you monitor the system, the system be an exception based bring to attention the critical items. The focus is on Operational Continuity, which goes beyond control to Optimization and performance, and effective alignment of the operational team. Understanding the operating boundaries set up by safety to humans and environment, and maintaining maximum operational/energy performance.

To achieve this, the user is looking at operational view/dashboard of the high level process with the ability to investigate situations onto surrounding operational view real estate for deeper focus, without losing the overall screen. This avoids missing situations, as this Center view is an exception based.   The ability to investigate and then share with others in the team, easily, and for dynamic live collaboration to exist between the site field staff and operational experts, production, maintenance etc no matter where they are.

The information, types of content used in these investigations are not standard process graphics of traditional HMI, they are to name a few:

Video, alarms, alarm event analysis, forms for data entry, and searching. Reports, documents, live collaboration tools, such as chat, video conference, and operational analysis tools to put events, data in the context of now, past and future for " what if" etc.

Key is the interaction between this content, with ability focus on the main screen and situation, then automatic relations across other content for rapid investigation and understanding is achieved for fast decisions.

This is NOT and HMI in the traditional sense and has caused us to term this new interactive, multi content environment in a new type of operational experience the " Operational Management Interface". This multi content environment will go across the operational control room to roaming expert maybe on a tablet, but different layout experience, and to the site.

The key is the interactive, collaboration experience across multiple content types to enable rapid decisions.

As you design for 2020 and operational workspace required over the next few years and for the next 20 years, ask yourself what is required by role, and activity.

Information Driven Operational/Process Excellence Set Drive Next Wave in Mining but with a Twist

As I toured a number of the leading mining companies this week, the conversation showed a significant shift from last year from "greenfield" to “brownfield" discussions. Shifting from new plant implementation and speed to full production to how they draw the most efficiency from existing assets. The interesting twist was that the discussion of what was an existing asset:

1/ Fixed assets such as equipment

2/ plant ore assets

3/ mobile assets like trucks, digging equipment

4/ human assets, operators, maintenance and experts

So the strategy was how to tap existing information more than often locked within SCADA trend systems, and other data stores, it was key to extract this data and align these records into effective information. The driving forces are :

1/ minimal impact on the existing systems

2/ speed of delivery of the value

3/ expertise to understand and interpret the value

4/ predictive awareness, pattern recognition

The diagram below again resounded in the discussions.

The key for Industrial Analytic s is the trusted data, and just a historian will not achieve this, the model and validation must be done as close to the source.

The information needs delivery in many cases outside the automation landscape, often in the corporate networks. The key is to use the not APIs but make the connection through an SOA architecture. The service sits on the data source, with configuration, and data delivery built in, but key is low impact and effort.

This is not new, as the enterprise historian has been around for years, but the real difference is the need not just gather data, but to capture the data in a structure,  context, and validation of data that makes sure all stored data through resulting information is in trusted.

You are probably sitting there and saying nothing new! Fair, but the key was how are they going get this structured trusted data, that the concept was to do this as close to the source as possible, and then send through. This means the underlying systems do not change, minimize risk, maximize Lifecycle managed to enable evolution which will happen. Why is this not an IOT service, local and pushing vs polling, “self configuring” ?

Remembering the performance team of experts can be anywhere, and will probably virtual, where sharing, analysis and Modeling is done in offline mode looking for patterns.

As the discussions evolved the architecture evolved, and again the "cloud" came into play, why because the data size will grow, the users are everywhere, and the infrastructure of delivering is now there.

Why not?

The collaborative information, industrial analytics, is going to be foundational for the future of Gen Y teams of analysts experts from different locations and outside the companies.

Standby, as we see some of the optimization learnings from Oil and Gas come over into mining.

Industrial Ethernet/ “Internet of Things” Is it About putting Data in the Cloud? Or Interactivity?

Sorry for missing last week, time seems short when on the road with short flights.

As I fly the final leg home after a month on the road many brainstorming multi day workshops around different strategic thinking, but without a doubt the “Internet of Things’ applied in industrial/ manufacturing space brought up many ideas and many questions.

Certainly the discussion of “Cloud” vs “Internet of things” is it about getting to data from all types of devices and making that more available? Certainly that is one case, but certainly it is not a compelling case.

The “Internet of things” is about self-configuring devices, these could instruments, motors trucks, and mobile devices, fixed and roaming devices. Too many of you the IOT definition I believed was clear, but the workshops showed the confusion between taking and existing industrial application to the “Cloud” connecting through safe but tradition device integration paradigms, vs an interactive “self-configuring” environment of devices and systems, that is a new device integration, management paradigm.

Also, it is important to note it is not just about gathering data from devices to the cloud, and exposing it, the real opportunity comes in the interaction between devices, that the environment make the devices “self-aware” and able to interact. A natural example is that mobile devices of a roaming user is interacting with the other devices in the immediate area. Enabling interacting, and constant awareness and warnings of the current environment state, relative to a stability, and safety. Combine this with ever increasing transformation to managing Operational work vs monitoring, where the “work” or “activity” includes the information, action in the context of “activity”.

The fact that a device is now “self-configuring”, so you can from an IOT system “discover” the devices out there and configure the co-ordination system in the cloud, making other systems aware of them. This is a clear case for segments that are physically distributed such as cities, airports, upstream gas fields, mining, pipelines etc. Where the cost of aligning the devices has been too expensive, now with wireless but even more 4G networks like we seeing in the remote “Pilbara” region on Western Australia, the opportunity for plug and play devices that are “edge/ GPRS” enabled, and IOT enabled can be discovered, configured and aligned. As devices are swapped in and out no matter site the size, the configuration moves from an instrumentation job to anyone. This frictionless experience is key in configuration/ and sustaining. The increased speed of systems, decisions and agility required drives up complexity of systems, but this cannot drive up lifecycle cost, and this can only go away through Self Configuration, enablement of anyone to enable the system to run, this become clear as the key requirement of the IOT.

The chart below shows the expected industry segments to adopt, many are well engaged.

But why is there a slow take up, mainly I believe to unawareness, lack of understanding, and readiness? But this is changing, the IOT platforms are coming on to the market that will drive down the cost of achieving IOT, but it will still be a journey. The diagram below shows from one of the workshops the key challenges in adoption, I expect these to fall away fast over the next 2 to 3 years. I cannot see how we going achieve the agility, with the dynamic market, operational workforce at a sustainable cost that is reasonable without this paradigm shift, to IOT as interactive landscape. In the many sessions I held with end users, engineers and people across the company and industry, the real initial opportunity is not in the big plants it is in the “collaborative Industrial Landscape” of small plants and assets aligning with people and processes.

 Certainly the interest, like cloud is growing, and the infrastructure is maturing that this will be reality in helping to addressing the modern industrial landscape challengers in a very different landscape than we had in 90s, 2000s, and 2010s, I will discuss more on this fundamental event next week.