Forecasting and Predicting, Must be a Cornerstone of the Modern Operational System

For the last couple of weeks Stan and I have been working with a number of leading companies in Oil and Gas, Mining, and F & B around their Operational Landscape or experience of the future.

Too often the conversations start off from a technology point, and we spend the initial couple of days trying to swing the conversation to the way in which they need to operate in the future and what their plans are around operations.

It becomes clear very quickly that there is allot of good intent, but real thought into how they need to operate in order to meet production expectations both in products and margin has not been worked through.

Over and over again we see the need for faster decisions, in a changing agile world, and this requires an "understanding of the future" this maybe only 1/2 hour. The time span of future required for decisions depends on role, (same as history) but it is clear that modeling of future is not just something for the planner, it is will become a native part of all operational systems.

This blog from Stan captures some of the necessary concepts.

  

Operations management systems must deliver better orientation than traditional reporting or decision support systems.  One important aspect of operations is the dynamic nature – there will be a journey of changing schedules, changing raw material capabilities, changing product requirements and changing equipment or process capabilities.

It might be helpful to consider desired and undesired conditions, using the analogy of driving a car on a long trip.  The planned route has turns, and it may involve traffic jams, detours, poor visibility due to heavy rain or fog; the driver and the car must stop periodically; and the driver may receive a telephone call to modify the route.  The following diagram is a sketch which displays how an integrated view might appear:

In the above example, the actual performance is at the upper limit for the target, and the scheduled target and constraints will shift upward in the near future.  The constraint is currently much higher than the scheduled target limits, but it is forecast-ed to change so that in some conditions in the future, the constraint will not allow some ranges of targets and limits.  This simple view shows a single operations measure with its associated constraints and target.

• At this stage, we propose a definition of “forecasting”: a future trend which is a series of pairs of information, where the pairs include a value and a time.  The accuracy of the values will be poorer as the time increases, but the direction of the trend (trending down or up, or cycling) and the values in the near future are sufficiently useful.
• In contrast, “predicting” is an estimate that a recognized event will likely happen in the future, but the timing is uncertain.  This is useful for understanding “imminent” failures.

The following diagram shows an example of estimating the probabilities of 5 failure categories, where the first (rotor thermal expansion) is the most likely.

Given these two definitions, it is helpful to consider industrial equipment behaviors.

• Several types of equipment, especially fixed equipment such as heat exchangers, chillers, fired heaters etc. exhibit a gradual reduction in efficiency or capacity, or exhibit varying capability depending upon ambient temperature and the temperature of the heat transfer fluid (e.g. steam, hot oil, chilled water).  While the performance is changing, the equipment hasn’t failed, although its performance might reach a level which justifies an overhaul.  In extreme cases, sudden failures can occur, such as tube rupture or complete blockage.  These benefit from “forecasting”.
• Other types of equipment, such as agitators, pumps, turbines, compressors etc. exhibit sudden failures.  These benefit from “predicting”.

One analogy of incorporating both “forecasting” and “predicting” is that it is like driving a car without looking forward through the windshield/windscreen, such as shown in the following sketch:

In the above sketch, the road behind the car is clear, but ahead, a potential collision will occur.  High-performance operations requires that teams prevent unplanned shutdowns or other events.

The Workforce Crisis of 2030!! And how to start solving it now

“People, workforce planning will become more important than financial planning.” Rainer Strack

This is a statement from good TED talk by Rainer on his interpretation of the workforce challenge of 2030. Supporting much of what this blog has been looking at this past year, but bringing another angle. The key we both trying to get over it is not about the changing workforce it is about the operational workforce transformation to a new workforce landscape of skill shortage, labor shortage and cultural and people change.

You can go to Ted talk with the following link.

http://www.ted.com/talks/rainer_strack_the_surprising_workforce_crisis_of_2030_and_how_to_start_solving_it_now

A couple of extractions:

The investigation and determination of a significant workforce shortage by 2030, but starting now:

The required strategies that will dominate much the thinking

Rainer is talking general workforce, if you take this and bring it into manufacturing, industrial world, the shortages will be all more acute. As pointed out in other surveys from Accenture and others.

This shows in US survey results on filling skilled and highly skilled roles, below is worked example of mid sized company in mid west.  

This is why the move from knowledge to wisdom is key, and emedding of knowledge and wisdom , actionable decisions into the systems is key to accommodate the transformation to dramatically reduced dependency on skilled people. From Rainer’s and other investigations that Operational Systems of the future in the industrial market have 50% + reduction in dependency in skilled and highly skilled workforce.This Ted talk supports this will be the biggest issue in the next 10 years to sustain competitive agility. Like we have seen in 2014, I believe 2015 this acknowledgment and strategies building around workforce change will intensify.    

Big Data Requires a Big, New Architecture

“The potential of “big data,” the massive explosion of sources of information from sensors, smart devices, and all other devices connected to the Internet, is probably under-appreciated in terms of its eventual business impact. However, to take maximum advantage of big data, IT is going to have to press the re-start button on its architecture for acquiring and understanding information. IT will need to construct a new way of capturing, organizing and analyzing data, because big data stands no chance of being useful if people attempt to process it using the traditional mechanisms of business intelligence, such as a data warehouses and traditional data-analysis techniques.” Dan Woods; Forbes

So does this apply to Industrial Area, I was heading through Terminal 5 in Heathrow this week, and articles banners around Big Data were all around me, and yes it is the latest “train” for people to board, but is it real in the Industrial Space? As I boarded a train, sat doing a mind thinking moment looking at the industrial operations/ automation landscape I realized why there is confusion is that in the industrial space,  we talk about Enterprise Historians, and one person said to me that is big data! I do not think so, it is just one aspect of the growing industrial information dilemma facing all us over the next 5 years.

When I look at the predictions of Big Data by Industry from Gartner:

The column for “Manufacturing and Natural Resources” which has every row in “Hot” or greater and points to “Volume of data”, “Velocity of data” and especially “Underutilized Dark Data” as Very Hot. This is should not be a surprise to anyone with the historians out there with 10000s of tags soaking up the data at second intervals. In the last 7 years,  Invensys Wonderware has installed 128 million I/O in historian points. Another point not brought out here is the need to make the data “trust worthy” and auditable so business decisions can depend upon it, much of the industrial data is just captured today, not validated against the current state of the process etc.

Now lets understand the “Jobs People want to do today” has there been a change? Yes there has been around the responsibility scope increase. This is both in making decisions and more business impactive decisions, as well as the increase in breadth e.g. Area that a person has to manage.

Initially this seems okay, but  now consider  the devices in the field today, and the amount of data coming from a device that traditionally would have 2 to 3 points, can have 400 points. Is this exaggeration, lets look at an example of a pump.

In the old days,  a pump would have:

• Speed
• Pressure

 Today:

• Speed
• Temperature
• Pressure on incoming and outgoing
• Vibration
• Energy calculations (many variables)
• Number of starts
• Volume
• On goes the list

The reason is that today devices are much smarter this to improve performance, efficiency, maintenance lifetime, and energy consumption management as well as predicting the operational reliability of  the pump. Compared with the old requirement of turning it on and making sure it is pumping to make sure it does not run dry.

Now take one device and put it in a plant context where it is one of 1000s, we have effectively increased the volume of data by 100000s and it will not stop growing. So the ability to capture this data as close to local data source, validating the data, but accessing the data, understanding events, patterns, and relationships across devices, plants, and device types etc required for this ever increasing drive to lower the OPEX costs, through increased efficiency and lower maintenance lower energy consumption  etc.  Again review this data historised for  a pump, the data falls under multiple categories:

·         Operational

·         Energy

·         Maintenance

·         Efficiency

Different roles within the “day to day” running of the industrial operations will analysis the data in different ways, to draw different conclusions. Examples are some people will want to look across multiple pumps and compare efficiency, energy etc vs the Operator who is just look at the current status and availability.

Will the traditional industrial tools be good enough?  I do not think so as all data is not in one form, one data source, take the above time series historian data, combine this alarming, events, and operational data. The introduction of new architectures, “Information Models” and analysis tools which will enable a view across large amounts of data, put this data in the context (this does not mean a data warehouse) and analysis tools quickly bring out trends/ relationships between data from different sources over large areas. All with the simple objective of enable more “real time decisions support”. An example of this is in the latest Wonderware Information Server 2012 R2 (released this month) with a new operational analysis capability. Seen below this capability is out of the box across, MES, Batch, Time series historian data and alarms data sources, providing an immediate view into a trend with a “halo” to show the shift, or batch or phase of operations the process was in, and associated alarm data, all at the operators finger tips.

This is the first step as Invensys will be expanding this capability through the next few years across the Enterprise Control Solution. I will expand on this Big Data in Industry and Decision Support concepts over the next couple of weeks.     

It is the End of the Year, what is on people minds this year vs. Last year?

Sitting a coffee table in Convent Garden in London, the chilling winter wind blowing through me, but the dazzling lights of Christmas and the holiday season dance about me. I have the opportunity to absorb the discussions of the last week discussing with teams from around the world what is driving operational thought leaders in mining, transport, and infra-structure. Now I look up at dazzling lights my mind shifts to the thought of;”is there a difference in operational priorities this year vs. last year and the answer is YES!!!”

The economic outlook is “soft” and nervous; certainly infra-structure projects from governments are under increased scrutiny. Last year there was some optimism as things were turning, today for many they walking carefully, we are seeing commodity prices causing pull back in major/ mega projects. Also, we are another year into this final run on the experience of “Baby Boomer” and Early Gen X (born 1960 to 1970) moving on, and that experience going out the door.

Reflecting on the key themes underlying discussions in Operations Strategy as we end 2012:

·         How to increase the effectiveness of roles, so they are able to make more decisions. This is leading to active discussions around “decision support systems” more than reports, but an experience that will enable a holistic view on information in context and actions to be taken in a timely manner.

·       Opex cost tightening, that strategies are around reducing operations costs, through increased efficiency, the discussion is not on people reduction, but is around “energy” reduction. This is causing discussions on energy around how to align plant, equipment usage to low energy rate periods and bring this into the plant operational planning.

·         The Aging worker discussion has shifted or started to shift to how deal with people in roles for short periods causing limited experience. There is recognition that this is not just an age issue, but the nature of operational business and HR that people are moving locations, roles at an increased frequency compared with 5 to 10 years. Note that this has only started to be recognized but with recognition.  

·         Having people more aligned into effective work. This is an intriguing one, but there is a lot of discussion on what workers are doing in their 8 hours and how much of it is effective. This aligns with the shift towards focusing on “planned work” vs. “ad hoc, unplanned” work. This immediately provides benefit in safety levels, and efficiency.

·         The discussion of how to execute solutions of the complexity required, unifying many sites and systems, how to build and sustain standards, how to execute in a timely fashion at minimal risk when shareholders are constraining capital budgets. Yet everyone realizes the programs must go on, so a healthy discussion around how execute, modularization of the program into “bite size chunks” using multiple engineering teams. This discussion will grow in momentum in 2013.

·         With the drive down on Opex and Capex, there is an increasing review of the custom, unsustainable solutions running in the operations, especially MES, which traditionally had a significant customization. Companies are investigating programs to shift the cost or growing and sustaining the systems away, either by new solutions based upon off the shelf products, or outsourcing the sustaining of the system.

There are many other side conversations around information in the context, the unifying of data, potential to use “Big Data” concepts (see blog coming up in the coming weeks). There is  realization in the holistic view across the Enterprise Landscape, and the changing Operational Worker, I believe there will be a resetting of role definitions across the plants, as the “day in the life “ of Operational Worker (no matter the role) is changing significantly with the freedom mobility brings.

I am sure I have missed some points, but the key is the “outlook” is different, and the leading companies are considering different factors on when, what and how they will evolve their operational systems in order to achieve Operation Effectiveness.

All good food for thought over these upcoming holiday period.