Achieving Consistent and Right Results in an Agile World

As Sunday draws to a close, I sit out looking over to pacific the waves crash, and birds fly, it is my time of reflection.

Last week I talked about some of the observations from the last month on the road. But this week I debated with a number of thought leaders and we all aligned on the challenge of a dynamic workforce, and dynamic operational/ business environment, means that chance of “Lights out Manufacturing “ are slim.

One company I was engaged with last week their thought pattern was still about replacing the personal on the plant, going to total automation. While I agree with automation, it is required for consistently and velocity of production. But I struggle with agility.

Two days latter I was at another company and they were all about empowerment of people, they wanted to automate process, and operations to free up people to add complimentary agility and “out of the box” thinking.  As one C level said to me, our market is changing as fast as we ever seen, and

Stepping back and looking at both these companies the second company was more automated than the first and the second was investing in automation more than the first. But their attitude was to gain consistently and free up people from repeatable tasks, and increase the responsibility of people, and empower people to make decisions fast.  

The diagram below really depicts what I started to introduce last week, and what this second company believed in.

That they needed to design their systems and people to play “natively in the dynamic world”, and they have realized that “embedded Intelligence and knowledge” will be key and must grow proportionally with increasing data. They also realized that with agility comes the changing operational environment and situations which will require “augmented intelligence” with the human brain can work out. The key thinkers in the industry are not looking to dependency on 1 to 2 people, they are leveraging the concept of “crowd sourcing” thru a active community of people. As we look at the operational/ automation world of the future the key pillars will be:

•     Ability to capture knowledge and intelligence into the system to automate process, and operations. Key is this is not just traditional automation in PLCs/ DCS etc, it is capturing repeatable knowledge and decisions. So the system must bread a culture of contribution and use natively.
•    Ability to have a community of workers who can share collaborated “naturally” with ease, no matter the location of the users and state. Foundational to this is  the ability trust the information, the measures so a common understanding of the situation, and basis for decision can be made.

Leading to natural decisions, and action paradigm across the team as seen below. I will expand on this more next week.

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.