How do you Achieve Orchestration in Industrial Internet of Things without Managed Configurations and Standards?

Last week I was at mining conference and had a rare chance to sit back and listen to people’s thoughts on innovation, and the future. It was good to hear the topics of partnership are key to innovation, (relating to my blog of a month “Participation architecture and culture key to Innovation”).

As expected the “internet of things” came up a lot, in many contexts, like it did at the Dairy conference the week before. With this cam the usual many definitions of IOT and the impact it will have on the mining industry. I just wondered how many people really comprehend the value, and complexity that it brings?

One evening I was on call with France with a partner discussing smart cities and IOT and he made the interesting comment:

“The Internet of Things has moved beyond big data and analysis to how will we align the devices and people into an orchestrated operational strategy that achieves a repeatable agile outcomes.”

I sat back with a big smile as he had articulated the change I had been seeing. As decisions and data is nice but it must go from data, information, knowledge to wisdom where actions can be taken, no matter if that action is taken by a device, or human.

Then I saw this categories of maturity in the internet of things, I had seen something similar but in a week of much discussion on this topic I thought this one would do. It shows devices going from a data sources with intelligent data / I hope actually Information. Evolving to control of devices in orchestrated way, no matter if the control is in the thing or in cloud the things know how to work together in a coordinated strategy. Once you have all the things working together you can move to tuning their operational behavior and effectiveness. This seems simple but things require access to control strategies, and orchestrations that guide these things, now we talking 100s to 1000s of things in this coordinated community. Eventually you end up autonomy or semi autonomy “managed by exception”.

In another discussion with a large network hardware supplier we were discussing a mining extraction alignment solution that could be enabled by IOT unlike today. So we took a practical look at the application, and saw 10s of like machines and a few classes of machines. Then you look at the operational processes they executing and again see repetition, but we are now talking 1000s look at devices.  Yet we had a customer wanting achieve level 3 in the above model “Optimization”. I thought back to many industrial sites I have been on in the last few years where there are 10s of PLCs programmed with larger control strategies but programmed at different times and by different people (even if from the same vendor) and how customers were having a significant cost of ownership in evolving these strategies. This why organizations like OMAC and PACKML have come about defining standard control strategies for operations/ devices that could span vendors.

So I ended back at my conflict, as we move to landscape where we will have 1000s of devices often smaller than traditional PLCs but each with their own monitoring, or control strategies, and then high level strategies that enable the orchestration of these devices/ things into a an effective operational strategy.

I asked how are we going sustain and evolve these strategies without having an “Enterprise Standards Management Framework” that enable standards to built for an operation? These are then deployed over 100s of similar operations on different devices. Now we shifted to managed, agile and sustainable solution.  

The thought of 100s of people programming 1000s of devices and then trying tune and evolve these seems un practical, plus if we enable standards management the reuse of IP and rapid rollout is achieved, while leveraging the revolution to smart devices and lower cost devices that execute these strategies.

A food for thought!!!!!

Cyber Physical and Operational Management Evolution

In recent months Stan DeVries and I as part of Common Architecture Team, and also investigating large opportunities have spent many hours discussing the internet of things, Industrie 4.0, and shift to Cyber Physical architectures. It is fundamental for the rapid innovation businesses will need in order to stay competitive, both delivering products, but evolving efficiency and leveraging an effective "operational team", Stan submitted this blog on the subject.

Recently the academic phrase “cyber-physical systems” has appeared in presentations and articles on smart manufacturing and Industry 4.0.  Much of the emphasis has been on the “cyber” element, with frequent example of automation.  This may imply “lights out” operations, which might be achievable and desirable in some operations, but unnecessary, in-feasible and undesirable in most.  It should be helpful to consider one of the models of cyber-physical systems, which is called the Boyd OODA Loop, as shown in the following diagram:

Colonel Boyd was an excellent fighter pilot and military strategist.  The key elements of his decision model are:

• Observation: the collection of data by means of the senses
• Orientation: the analysis and synthesis of data to form one's current mental perspective
• Decision: the determination of a course of action based on one's current mental perspective
• Action: the physical playing-out of decisions

Using this model, automation improves the Observation and Orientation so that users engage with only the “right” information, at the “right” time (often earlier than real-time) in the”right” context – for the “right” results.

While the Boyd decision model is excellent for one or a few workers, another model is necessary for considering an entire operation, such as a manufacturing plant, a power generation station, petroleum refinery, oilfield etc.

If we accept that the main value of the automation is to improve the Observation and Orientation, then the above diagram implements these 2 important steps in what can be called the Smart Solution Center, which is a combination of a technology/data center and specialists who are providing support, improvement and instruction to other workers.  One of the key outputs of the Smart Solution Center, so that most of the work performed by knowledge workers within that Center and other workers spend the majority of their time on planned work, instead of being consumed with reactive work.

But automation of Observation and Orientation must be extremely accurate and trustworthy.  To achieve and sustain these attributes, we recommend a “Virtual Smart Plant” which is used to design, modify, test and train workers.  This is also key to sustaining behavior change and if possible, culture change.  Best practices have shown that workers change their performance in lasting ways if they experience the change for themselves, and especially if they can experience new learning in a “safe” environment.

In the above diagram, the “work orders” are more than task lists, but a combination of recipes, KPI targets, instructions, handover/turnover actions etc.  The black rectangle at the center bottom of the diagram is focused on people, who are doing what humans do best: dealing with new knowledge, managing complexity, and navigating change.

So the key to applying “cyber-physical systems” is optimizing the use of the workers, not eliminating them, and this optimization requires using technology in a “smart” manner, such as focusing on Observation and Orientation.

An increasing amount of leading companies are developing the "Smart Solution Centers" (often reference to as Centers of Excellence) where they can physical one location or a "virtual smart center" maximizing the leverage of key thought leaders in the analysis and development of operational/ process innovations. A good example of this is Rio Tinto's Process Excellence Center for mining in Brisbane (plenty of write up on this) where data is analysed converted into effective knowledge through simulation, analysis models, to improve operational running of mine process. 

  

Increased Automation of Tasks/ Decisions over the next 10 Years is Foundational, but that does not mean “Lights out Manufacturing”.

In order to deal the increased complexity of the operational opportunity of today, the flat world of competition from around the globe, and the complexity of the Operational System, the production increase dramatically. Requiring higher qualified people, or take the approach that we must constantly simplify the operational experience, so the required skill level does not increase with the complexity of the Operational Scenarios the system is applied.

The diagram below shows the critical drive to sustain productivity margins, by increasing the productivity, while flattening the hourly rate for that productivity. This can only happen through increased effectiveness of the systems, and use of people, without adding more people, or requiring highly skilled people.

So many of the programs have this drive to increase automation of tasks, with some people jumping to the conclusion that means we moving to “lights out manufacturing” an old concept. That is not the case, we need the human brain to deal with the exception and edge decisions and actions where the model has not been created. With agility increasing velocity of products through the supply chain, while increasing the volume of new product introductions, combined with the complete value supply chain managed as one, the role of workers is key.

The table below shows one version of the 6 levels of automation. The key is as a decision and action become predictable and well known, then it must be rolled into the system as “knowledge “and “Wisdom”.

The goal is to get to “Manage by Exception” (level 5) vs all decisions, this is what is done in a aeronautical industry with pilot/ plane control, and is why it is key to take on principles like “situational awareness” so a worker is able to see the ever growing scope of responsibility, in an insistent.

Where does you design principles apply in this landscape?

A Different Approach to Design Operational Systems is Needed!!!

I have had the opportunity to review some new strategies of some companies are taking to designing their systems for operations in 2020 to 2030, and I am pleased to see they have taken not just a technology approach. But really turn around and looked at “who they will execute work across their value supply chain” focusing on how they will have operate in this period then how they will be executing their work to achieve this.

Now technology is key as it will enable vision to be achieved in “agile “ world, while making it a sustainable evolution.

The diagram below illustrates our current summary of change in thinking needed in approach the bigger picture programs.