The Smart Plant Culture, What is it?

The concepts of an agile / smart plant, facility are not just in the assets, equipment, and systems, the key to the modern world is the efficiency in the work, and how people and expertise is used across the given tribes of people working and contributing to the business success. This article by Stan captures what is core to that culture.

 The Smart Plant is characterized by its behavior, which is a combination of technology enablers and the culture of the organization.  If the people don’t effectively use the technology, then the plant won’t behave in a “smart” way.

One of the most effective analyses of culture and culture change comes from Roger Connors and Tom Smith, who have written a book called Change the Culture, Change the Game.  They assert that actions and results only change when beliefs and experiences are changed.  When management attempt to change the results without changing beliefs and experiences, the organization doesn’t produce lasting change, and the amount of “disengagement” and rebellion increases.  These authors have also analyzed a key aspect of culture that they call “accountability”.  In this analysis, they recommend shifting an organization’s behaviors from what they call the “blame game” to a behavior of openness, ownership, teamwork and collective actions to solve the problems.

Dr. Stephen Covey has embraced these and he has written a book called Principle-Centered Leadership, which recommends a combination of changing the goals and measures, combined with a different approach to managing performance.

In the above diagram, the most important goals are called Wildly Important, and these are made clear and prominent.  The second step is to shift from the traditional “lagging” measures to “leading” measures, so that organizations can continually prevent problems and take full advantage of opportunities.  The third step is a “compelling” scoreboard, which requires all workers to have information with sufficient frequency and detail that affects their jobs.  This often requires hourly information focused on manufacturing or processing “cells” or “units”.  And the fourth step is a supervisor “cadence” or regular review and adjustment of targets.  In many industrial facilities, this might occur daily.

The Smart Plant culture reaches across organization silos, reaches across locations and reaches across time to share ownership of challenges and solve problems together.  The “blame game” is minimized and new employees are oriented into the shared beliefs and experience of problem-solving and sharing information, both good news and bad news.  Training shifts from isolated prevention of blame to team training which share performance.

Article authored by Stan DeVries Snr SOlution Architect at Schneider - Electric

The Re Think on the Role and Use of the Experts in Industrial Operations/ Automation!

For a while now I have spoken about the trends in the operational workforce, and people have been talking about the aging workforce (expect major impact over the next 7 years), but the talk has only been in one dimension.

Over the last week as we did analysis across a couple of industries an “aligning of the planets” into a major market disruptive event has become clear not just from the “aging” workforce retiring , but from two additional dimensions.

The diagram below tries to show the 3 converging dimensions that became clear where speaking with 2 customers and then listening to a few others.

Looking at this diagram you have 3 clear dimensions, driving different aspects of the new strategies we seeing in “Smart Facilities/ Plants” etc., but they all effect each other, and will cause a significant shift in how we handle experts.

Experts can be in the Operational Process, Production, IT, Automation, Asset etc.

1/ Reducing Expertise Capacity (Aging workforce): Nothing new here except the impact of GFC (global financial crisis) has pushed out the retirement of many people. But as predicted in Europe that in 2030 there will be an 8.3 million deficit in people entering the workforce vs retiring or leaving. Other charts show the next 7 to 10 years will see the acceleration of retirements in industry.

Two big feedbacks in this area:

•         People are predicting that the workforce of 2020 will have 30% of experience of the current workforce, does not mean they less qualified, but their first hand experience in a role or location will be down. That tacit knowledge vs the explicit knowledge you can learn from text books.
•          Two companies just talked about even the shortage of people hiring into positions even from Gen Y.

One comment from the mining field “I've been told by engineers on more than one mine site that they just don't run the existing equipment as well as they used to in the early 1990s. Particularly the big plant and equipment. This seems to be more an issue of availability of expertise and training!”    

2/ New Digitally Native/ Dynamic workforce: This I have talked about at length, but it is still an eye opener for many people that the above “ageing workforce” retiring is not just about the loss of experience (which significant), but the transition. The new workforce is not the same as the old, and the interfaces, procedures, approaches will not work, or keep the experts.

•         They are digitally native they expect to collaborate, share, and in the NOW
•          They will evolve in roles, careers, and locations many times to the point that they will not stay in a role/ location for longer than 2 years. We already seeing this in some parts the world.  
•          There ability to use tools to execute exceeds to two pervouse generations, but their tolerance and ability to solve, investigate work determining execution is reduced. The system should provide the information and action.

3/ Personnel Efficiency Reduction: This was brought to me 2 weeks ago and I was surprised as I know in my own work that I do far more than I did 10 years ago, and effect all parts of the globe so my reach is more effective.

But in Solomon Benchmarking for refining, which is really the Refining industry benchmarks by which companies in that industry judge their performance. Indicated from 1994 to 2012 the Personal Cost Index is dropping. PCI (Personal Cost Index) is equal to “Personal Cost/ Equipment/ Asset Capacity to Produce “. Over the last 18 years the trend has been that Asset/ Plant capacity increase has not kept pace with the increase in Human Overhead cost. Example in 2010 = 23.5 2012= 25.7. Driving strategies to use fewer experts across wider influence over the total industrial supply chain, increasing the effective output.

Is this surprising initially probably yes, but when I went back and looked again, in my role I have increased my efficiency and output, by leveraging new technologies built into the latest office, communication, and task execution tools.

But has that same dramatic increase in tools capability to empower operators and experts to increase their effectiveness happened in the industrial world, ASM (Abnormal Situational Management Consortium) and others indicate that we have not increased the empowerment of industrial worker. We have done integration, we have looked asset performance, process performance, but in most cases until recently we have not changed the personal experience significantly to performance tasks.

With the true application of the ASM concepts, going to Integrated Operational Centers, going to exception based awareness, vs monitoring. Truly not just making the equipment smart, but leveraging the smart “self aware” equipment to empower a new level of operational efficiency and increased output relative to the amount of experts and operational staff.

Also during the same period the both the “mechanical and operational availability” in refining has dropped.

This is all food for thought, but in so many of conversations I am having today with leading thought leaders in industrial companies, the need for innovative ways to effectively use their workers and experience across their industrial supply chain is “top of mind.”

A foundational pillar in an Effective Operational Excellence Strategy, is the strategy around using experts differently, leading companies towards the “Virtual Expert Teams” that collaborate on trusted information with the local teams. Indications are that the operational work-space of 2020/ 25 will have a significant 40% less operational experts across a companies industrial supply chain, with the systems housing the required knowledge to be agile.

Clear KPIs for Measuring “Smart Plant/ Factory” Success is Key, Again Operations, Humans are Difference in this 4th Industrial Revolution

I seem to have been involved in Smart Fields, Smart Facilities, etc for years, and a lot of the discussion and thought leadership was around information, and more intelligent devices. But many have had limited success, until now, why is because many “smart” strategies did not cover all the bases.

During last week a colleague and I had a number of workshop sessions around forward strategy, reviewing specifically what is different this time round with smart, looking at the “Operational Transformation” event we seeing unfold, what is different and core this time! It was very clear, but so was the significant discontinuity in the market.

When we talk Smart concepts too often, the discussions goes quickly to the “smart/ intelligent” devices, and data and information, with the hype around the “Internet of Things” this continues. But when you really get down to what people are trying to achieve is decisions faster, and flexibility / agility through awareness and operational transparency.  

Yes the real impact here of this Operational Transformation is not just that devices are becoming smarter, “self aware” but the need to gain consistency in operations, and reduce errors. There is significant discontinuity happen in the market, as the logical way to eliminate the errors is through experienced workforce. As we all know that actually the workforce in 5 years will dramatically be less experienced than the workforce of yesterday or today.

The diagram below shows the experienced workforce  today is responsible for most of the unscheduled shutdowns.

So the outlook in the next 5 years is grim as we move to the in experienced workforce, unless our systems and operational processes change that is why “smart xxx” is real.

The major outcomes of the drive towards “smart factories, airports, fields etc” is to embed the operational experience, and self awareness in the Smart Devices” and “Smart Processes” .

Too often we do not have clear goals, but it was interesting to see a leading coming define very clear goals constantly to monitor the direction, and success of this "journey". 

Below is their goals:

Key drive is for zero human, equipment and process shutdowns and errors; this drives towards a significant embedding of process and automation on process and analysis to predict situations so that planned / controlled actions can take place limiting unnecessary shutdowns.

Key is the recognition that number of experts that are going to be available due to new generational work-space is going to be limited, and it is key to dramatically reduce the dependency on these experts by 90%. Another shift is to Global centers of excellence that must have access to timely information in context and trusted to interact with the local teams.

100% optimization of Feed/ Energy/ and Product usually plant have 1 maybe two of these tuned , but not 100% optimized, but this is not as simple as it looks when Feed stocks vary, Products instruction is increasing and Energy is totally variable, but the company has recognized to minimize impact of variability is optimization.   Also the knowledge of the system must be embedded, so the system is intuitive and self aware, enabling operational workers to rotate while maintaining consistency in operations and process.

Intelligent Alarms, and awareness will have to natural, so state / condition pattern analysis the move to the “to be” state is key. Many companies have significant programs in play now for transforming their current alarm structure to enable rapid, intuitive awareness of where that “pin” is in the haystack of alarms, and events.

As the plant becomes more intelligent and able to operate, key decisions and follow through actions in a timely manner are fundamental. This will not be one person; it will be a set of actions, and decisions across a team. So the operational system will be designed with collaboration in mind, the natural ability to guide, have built in operational process, natural documentation of actions, and passing of actions to the next person. Key will be the ability to “Resolve Operational Tasks” through tracking and an operational work system within the system, optimizing the human assets as much as the physical assets and processes.   

Asset Management / Optimization Stands to Take Significant Leaps of Value with the Internet of Things

Last week I talked about the “smart plant”, one of the key areas that is changing and opportunity for a step level of output value is in the “Asset Reliability” / “Operational Continuity”.

The real opportunity in is increasing capacity of through :

• Increased flexibility in the existing assets to run more products, and we understand asset condition through pattern recognition
•  Improved preventive, and “awareness” of asset condition and capability of performing at optimum. The devices / assets are “self aware” and self learning on improvement and conditions so early detection of conditions are seen and corrected in a timely manner.
•  Improved planning and asset utilization through transparency across assets on a site and across sites,

There is a lot of talk around the internet of things (IoT) in the general world but in the industrial world there is huge opportunity just due to the significant number of devices.
Industry pundits predict that by 2020 over 50 billion everyday objects will be connected to the Internet. This does not even include the Industrial IoT and the entire M2M environment, much of which is already in place in our factories, plants, and infrastructure.The initial trend will be to establish one-way communication, ultimately migrating to "many-to-many" communications as more physical objects be-come connected. Connecting all the assets and devices in communities of active tuning, decisions and optimization, requiring a significant rethink and change to current operational management/ supervisory systems and information systems to take advantage, but it aligns with the workforce operational transformation.So if we look at the clear steps that can happen in Asset Efficiency:

1/ Increased information, data in a one way capture of asset information.
This step is the first one and is well under way where increased intelligent devices are monitoring / calculating their performance and the information is logged to an historian. As stated in past blogs we seeing the I/O count between control systems and historians increasing by over a factor of 10. (example a pump use to be 5 to 10 variables, now is 120 to 200, a well head was planned to 50 points now logging 690 points).
Once you have this data companies like Pattern Discovery Technologies (http://www.patterndiscovery.com/) produce solutions that used defined events to investigate through Big Data Techniques asset condition patterns, from this vast historical data, so that better prediction is possible of conditions earlier.

2/ Is by direction, and communities of devices “learning” together and tuning their performance.

So instead of a device/ asset just learning on it’s own, imagine a community or similar type devices learning and sharing their learnings between them. This is not a linear learning of optimization but an exponential learning. So the conditions for a type can be immediately picked up and used by a new device / asset of the same type. Machine learning and community “hub” learning is a powerful predictive capability coming into the market.

Companies like MTELL (http://www.mtell.com/) have introduced some powerful “Machine Learning” capabilities, that combine with their “Transfer Learning” capability. Key is this does not have to wait to new devices/ assets on the plant it can be applied to existing assets, and the “learning” will begin.

The concept of going to “Smart Machines/ assets” that are:

• Self-Aware”
•  Self and Tribal Learning, so improving in predictive understanding of behavior

  Notification and increased analysis capability through powerful tools for asset analysis from the dramatic increase in data available.Now that devices can be connected through wireless to internet, and therefore a “cloud historian that is managed” and these analysis tools can executed centrally, or devices discover each other and learn together provides the breakthrough in the Asset world from predictive to prescriptive.

Smart Plant a Realistic / Holistic View

Smart Cities, Smart Airports, Smart Farms, Smart Upstream Fields are all the talk, but when you get down to interviews with companies, cities etc, the definitions change from city to city, from major oil company to another, so if you looking for a clean definition it not to be found. But there are underlying trends you see across all of them:

Trends/ Objectives:

·         Faster decisions and less people monitoring / responsible for more. Leading to the Integrated Operational (control) centers.

·         Increased agility and efficiency through transparency across the whole landscape, so better alignment to plans

·         Increased Operational Continuity

·         Lowering of cost through increased understanding of operations, and operational efficiency of assets. Energy management and material management.

·         The Operational Workforce transition of experience and to a dynamic, digital workforce.

·         Environmental/ Safety and regulation control, limiting exposure and cost

·         Change of equipment/ instruments to “smart equipment” which have increased intelligence and “self monitoring” , a dramatic increase in data that needs to be understood, and used for more predictive awareness

Yes this is all a part of the Operational Transition I have been talking about, and believe will transform the industrial sector over the next 5 to 10 years, as part of the 3^rd industrial revolution.

But in the last couple of weeks we have worked with a company in Asia who has a really good grasp of “smart plant” and the overall concepts that need to addressed in their journey.

They are really looking at the 4 main themes with their unique names, but they also looking across these and how they interact, as well not just a plant but across assets.

This is built on their belief that Operational Workspace is changing and not in one area but multiple dimensions, with workforce change, but also ICT changes like “cloud," “Bandwidth," IOT (Internet of Things), Smart / intelligent devices, and the move to naturally using simulation.

The diagram below shows the two big axis they see changing, not too different to People and Asset changes we have seen before.

An interesting observation is the shift to “larger, more complex process” this is true in all industries, as the problem we are being asked to solve is significant compared with the traditional control, but the opportunity for return is significant as well. But with the use of centralized computing, and shared learning, the cost, and ability to solve these today over all size plants is possible.

In reality the fact that this company has engaged on journey and understands it is journey is important, understands the goals, and direction, the shift to manage “work” and transition their architecture to embrace “intelligent devices” so they can leverage the IoT developments and Big Data, Industrial Analytics. Probably means they will lead the transition and be positioned well in the new world beyond 2020, but we all entering this world!