Manufacturing Reflections

Quality control and management in the dairy industry has technical challenges generally not seen in other industries – on process quality measurement can be problematic. Therefore, we rely on the QC lab to give feedback. It’s accurate and repeatable for the most part, but nobody will argue it’s timely.  When we consider samples are typically taken hourly, and allowing for time for the lab to process the sample, it could be as long as 90 minutes to verify any control actions we made worked.

If we think about this, it’s the equivalent of driving a car by looking through the rear-view mirror to confirm nothing got run over. It’ll work up to the point we encounter a pothole – or even a curve.

Many dairy plants work around this limitation by operating conservatively with respect to process targets. Knowing the variation inherent in the process (borne out by years of lab tests), we set the operating targets far enough away from the upper (or lower) control limits to make a quality limit violation highly unlikely. To use the car analogy again, we’ll drive as far away from the ditch as we have to, to keep it on the road.

When we do this, we maintain product quality, but what happens to profitability? Are we giving away product by operating away from limits? Are we consuming energy unnecessarily?

What if we could use the information base contained in the plant to predict quality in real time?

Pavilion and myself have been living in a world biased to MPC (model-predictive control) for an extensive period of time.  MPC provides an explicit dynamic model including an ability to manage with complex dynamics, almost unlimited multivariate control capabilities, abilities to incorporate direct quality control and advanced features like nonlinear economic optimization or control among others. But since our acquisition by Rockwell Automation, we have added to our toolbox to include capabilities in advanced regulatory control like Smith Predictors for simple disturbance rejection, decouplers to handle limited multivariate control problems and fuzzy features to manage limited nonlinear control challenges (like pH control).

These features, while limited are simpler and easier to use than MPC for size appropriate control problems.  So sometimes a control problem needs a bigger, more capable tool (MPC) and other times a simpler, straightforward tool is appropriate.  We’ll call this advanced regulatory control (ARC) to cover anything from ratio controls to any of the more limited advanced control capabilities and looking at them together there are a lot of appropriate control challenges that are best solved with an ARC toolset.  I’ll take as a guiding principle the quote attributed to Einstein, “keep it as simple as possible, but no simpler”.

If a control problem is solved exclusively with capabilities available in MPC then MPC is the solution. If a control problem is solved with one or a straight-forward implementation of ARC tools, then ARC is the solution.  Where a debate and engineering judgment comes into play is when you are tempted to stretch ARC to the point where it becomes a maintenance challenge (Smith-Predictors, tied to decouplers or multivariate controllers; or fuzzy controllers tied to multivariate controllers with two or three variables).  I would propose that you need to look at the various block-diagrams of your controller and decide how simple it is going to be to train someone new how to update model parameters and tune them.  If it really is easy to tune then you can build a more complex ARC, but avoid the spaghetti code of over-complexity in any case.  Before this becomes a threat, migrate an application to MPC.

Finally, we have observed opportunities to cascade MPC at a higher level to lower level ARC.  This can have significant advantages and one disadvantage.

Advantages:

1. More of the advanced control benefits are DCS/SCADA/PLC resident so that their availability is almost 100%.  Benefits increase and certainly any essential or critical safety function should be resident on the control system.
2. The MPC solution is simplified so that some complexity is removed from the MPC or optimization models by segmenting regulatory functions from closed loop, but supervisory MPC functions.

Disadvantage

1. You require two independent advanced control functions resident on two different computing platforms, which can increase training, maintenance and TCO (total ownership cost) of an application.

My opinion is that this is handled on a case-by-case basis.  Sometimes both, sometimes everything in MPC.  What do you think?

Michael Gay (no relative) is constantly active in the Food and Beverage industry and since I’m never late for dinner – I’m always interested to hear how processing data is used in completely different ways than developing optimization models. It reminds me of the neural models used by my credit card company to call me and check that I haven’t lost my card.

Mike Tay

Basically Washington is looking to increase the pressure on Food & Beverage manufacturers to provide full accountability back to food suppliers on the genealogy of the food they supply, and it’s looking more and more like this will be in the form of electronic genealogy.

Current practices: a paper based system that creates tons of paper daily. That challenges anyone’s ability to recall any product: the task is simply too daunting. As a result, the scope of the recall is huge just to be sure all problem products are captured, which in turn increases the costs and the breadth of the recall. It can cripple a company.

Track & Trace

Ideally, product genealogy starts back at the farm, and then tracks the path all the way up to the shelf where the product is ultimately sold. However, focusing on the manufacturing process is a big step in keeping track of what’s inside. 

Elements of a track & trace solution include identifying the “M’s” of manufacturing, including:

• Materials – Understand the supplied ingredients and their origin and usage in the product
• Machinery – Collect and track the machinery that touched the product while processing
• Manpower – track the operations staff that came in contact with the goods in question
• Methods – Capture the recipe of the finished good.

Track & Trace solutions can provide manufacturing records to upper level systems that track where those suspect products ended up on the store shelf.

All this tracking and tracing provides operational benefits (If providing safe food isn’t enough justification) but, if you need to know…Track and Trace solutions provide the added benefit of:

• Providing an accurate accounting of products consumed in processing so yields, wastes, and rework streams can be clearly identified and improved
  • Reductions in safety stocks due to increased understanding of day-to-day inventory needs
  • Improved delivery of orders since machine efficiencies are better known
  • Efficiency improvements due to increased understanding of interactions of the four “M’s”

An electronic Track & Trace solution will also satisfy the inspectors at the federal, state or local regulatory agency by providing the documentation necessary as part of a mock or real recall event.  

Supplying accurate information quickly to the public not only ensures a safe food supply, it also provides piece of mind to Food & Beverage manufactures that the products supplied are something you can put your name on.

Mike G.

Three cultural trends are converging in plants and control rooms particularly in the Western economies, and throughout all process industries to create a perfect storm for operations:

1. The ‘Gray Wave’ of Baby Boomers, where a significant amount of practical experience and knowledge is about to walk past the plants’ gates and into retirement;
2. A replacement workforce that has grown up in the video game generation, accustomed to acquiring and processing  information and knowledge visually and at high rates; and
3. A dwindling graduation rates in the technical fields required to drive innovation and resolution within the day-to-day activities of manufacturing plants.

This convergence is the engine behind the recent focus on Operations Management/Enterprise Manufacturing Intelligence (EMI) solutions in the market.  Clearly, the way forward demands that a different set of application be given access to the next generations of operator.  The operator of tomorrow will be expected to make a broader set of decisions that go beyond the traditional boundaries of process control.  The drive to the top is fueling the need to ensure that minute-by-minute decisions in the control room are aligned with the corporate business strategy.  This was crisply highlighted in an Industry Week article focused on smarter manufacturing by Dave Miller, Global Industrial Sector Leader for IBM Global Services, where he highlights the fact that Manufacturing Intelligence must become prevalent for those companies that want to thrive in the future.

Unfortunately, software suppliers to the process industries have clouded the situation by confusing Manufacturing Awareness with Manufacturing Intelligence.  Elaborate dashboards displaying performance metrics tied to historical information can only provide retrospective insight, which is helpful if trying to understand what has happened.  However, Model-based Predictive Intelligence solutions have the capability to present events that are about to happen, and provide the functionality to test scenarios so operators can arrive at the optimal decision before events occur.

Predictive-EMI solutions provide predictive insight into the business impact of operating decisions by leveraging process models used in predictive control in combination with financial information from ERP systems.   The information is then presented to the control room on a role-based dashboard depicting the current state of operations (where you are), the opportunity (where you could be), and the recommended steps to capture the opportunity (how to get there).  This is the true essence of actionable intelligence.

Steve McGarel our resident cement expert is writing from the Middle East, while at the Cemtech show in Dubai.  Steve’s fairly pessimistic prognosis matches many fears about broader domestic, US manufacturing.  To my (overly) optimistic bent, the key always remains – do something better, focus on strengths and if the US processing market cannot leverage or invent technology that enables a domestic business, and take advantage of our logistical advantages – shame on us.  Do better!

Cement is the second most consumed substance in the world after water and changing trends in population growth and environmental pressures are introducing new dynamics to the industry.

U.S. consumption is down 25% in the current recession and the prospect of stricter environmental regulations means there is a distinct possibility cement production may move permanently offshore.

If this does happen, a shortfall in supply will occur as the world’s largest economy recovers and this demand will have to be imported from other countries.

World population growth trends are supporting this trend. Cement production and demand growth is highest in China, India, N. Africa, Middle East and Latin America.

World cement consumption will reach 3 Billion tons in 2010 for the first time ever. This will be driven by modern, energy efficient, waste burning cement plants, preferably with efficient access to seaport facilities to facilitate global shipping.

In the end it seems these mega trends will transfer production and economic wealth from “first world” economies to emerging markets.

Does this make complete sense? While it certainly assigns new capacity to uplifting new markets, does it result in a net benefit to the environment, since production is simply transferred to countries where environment regulations are less onerous?  Will importers levy a carbon tax to level the playing field and compensate for their environmental compliance costs?

The expanding producer countries are less likely to be involved in the burning of waste materials in cement kilns and will need to investigate new ways to reduce CO2 emissions from their process.

Will they become involved in growing and consuming biomass to replace other fossil fuels?

Will they introduce new raw materials and new cements to reduce the inherent CO2 component in their product?

Let’s track their moves and see. 

Pavilion has done a lot of work in the fuel alcohol industry.  The industry is challenged by influential commercial alternatives, but has delivered heroically throughout boom and  bust economic cycles.  If you haven’t looked into the history of this industry – you should.

Corn to ethanol remains predominantly an industry organized by growers cooperatives.  This has been essential in both farmers experience in dealing with boom and bust economic conditions, in supplying feedstock and in having alternative outlays to tide entities through challenging times.  The industry has been early adopters of technology solutions and invested in new research (like cellulosic ethanol) beyond what is common in other more traditional industries.

What is amazing to see is the benefit this industry has supplied to rural areas, the effort and motivation evident in most plant operations and the industries ability to solve problems as they come along.  The WSJ and several commercial voices are betting against fuel ethanol and it’s hard to judge why, but while the industry will continue to evolve – I’ve been to 70% of the plants in the US and 25% of the plants in Brazil.  I wouldn’t bet against this industry.

Today the industry appears living in good margins with inexpensive corn pricing and reasonably high ethanol (related to gasoline) pricing.  Last year was a tough economic time for most industries including fuel ethanol, but like many other industries fuel alcohol is cautiously optimistic about the near future.

If you haven’t read The Drunkards Walk take a look at this excellent book on Probability Theory in real life.  Another book related to this topic is Supercrunchers – which is another recommendation on using data to build understanding.

But in the real world data has both noise, drift and inconsistency.  One major question relates to using data intelligently, sorting through the haystack to find the useful information.  A couple of opportunities are critical:

• Empirical models (including unusual event detection) care more about consistency than accuracy; while fundamental models (including material balance) care more about accuracy.
• Like, “the solution to pollution is dilution” the solution to noisy measurements is redundancy in both redundant measurements, but also repeated sampling (a longer history of performance) to overcome and deal with noisy data.
• There are classical mathematical tools to solve inconsistency – to apply uncertainty to inputs and use optimization based error balancing in data reconciliation to assign likely error sources.  There are also engineering techniques to judge uncertainty or measurement accuracy based on methods.

You can live with bad data and still operate better with intelligent support than without it.  Better data is always preferable and measurement systems tend to evolve and improve with time.  Using available data (as in Supercrunchers) and being aware of data limitations (as described in The Drunkards Walk) remain essential in an uncertain world.

We’ve all been reading about upcoming refinery downsizing worldwide.  This includes major refiners as well as independents.  What that will mean for the refinery units that continue to operate will be “How do I make more with less?”

Most refiners have applied Model Predictive Control (MPC) to the “major” refinery units – FCC, CDU, reformer, etc. with optimization in some cases.  The benefits come from determining and controlling the optimal properties and relative sizes of the various product streams.  These applications have provided refiners substantial benefits for years

What do we do next?  Where can refiners achieve even greater benefits?

• Moving beyond these traditional applications are more complex systems such as blend optimization.  These are highly non-linear in nature, which has led to mixed results when attempted with linear methods.  There can be very large benefits in making blend quality control better by reducing blend give-away or by responding in real-time to blend component shifts as the blend component units shift in real-time.

• Another complex application is to control the CDU actively during crude switches.  These are also nonlinear and include challenging dynamics, but the value of success can be quite high.

• We are seeing a lot of interest in site-wide energy optimization, where for example, steam generated by the FCCU and other units is balanced against the value of steam generated in the utilities plant.  The “make vs. buy” decision is continuously updated as economics change. These optimization systems can provide even more value when environmental cap values are integrated into the constrained economic objective function.

We believe that the total MPC value proposition can be greatly expanded by going beyond the traditional applications and would like to hear feedback from refinery MPC users, both positive and negative.  It would also be interesting to get others’ perspectives on keys to MPC success in refineries.  In any case the key remains controlling quality tighter to specification, maximizing crude yields and reducing your energy input and leaving more in the product barrel.

Model predictive control (MPC) is using a process model to control a system on target or at process constraints.  Because it can control complex systems tightly, actively enforce, but run closer to process limits at your highest efficiency, MPC is generally accepted to increase production from the same equipment, yields from the same feedstock or reduce energy costs at the same rates.  So the question behind the question is – what do I need to do to actually get this money?  What are best practices in managing or delivering a MPC solution?

We believe the following based on hundreds of projects:

• Verify and agree on objectives as clearly as possible including project baseline and how improvements will be measured.  Make sure you can measure when an X% improvement is achieved and that it actually improves the bottom line.
• Do not allow cannibalistic projects to be executed at the same time.  Pick one project that will address a specific efficiency, capacity, yield or quality opportunity and do not fund or deploy another competing solution.  You can make other process improvement projects, but don’t buy two bus tickets to get to the same ball game – you don’t get there any faster or better.  You’ve paid twice.
• Confirm that you know what will change to enable benefits and get agreement that this change is acceptable and can and will be made.
• Commit yourself to maintain this MPC system in some way.  Spending money on installation and then saving money by not maintaining it is the surest way to make the system fail.  Monies can be reduced over the short term in tight economics – but not too long, believe me.  All plant systems including MPC require some maintenance.

Our analysis on multiple processes that are MPC appropriate is that MPC offers roughly five times the ROI of its capital equipment equivalent and that delivery time of these benefits is one fifth of equipment installation.  So the ROI is high, the improvements received rapidly, but you need to consider best practices to assure that you receive this value.

Have I missed some?  Do you agree?  Make this technology option assured and beneficial!

There is a lot of talk throughout all industries about the United Nations’ Climate Change Conference in Copenhagen last December. It ended with a political agreement to cap temperature rise and reduce emissions, which could eventually require radical adjustments from manufacturers to reduce greenhouse gas emissions.

If a consensus can ultimately be reached for a real reduction in GHG with a reasonable implementation time, then we will see reduction techniques being implemented. These reduction methods will be in many forms from sequestering to alternative power. With the implementation of GHG control, will come optimization and monitoring with reporting as already initiated at the end of last year. In addition, if a successful method of a global C&T can be developed that will also direct poorer nations to use alternative power producing methods instead of coal then a real reduction can be expected. This will all come as a cost to the producer as well as the consumer.

So looking at sustainability options: reduce, reuse, recycle and the fact that any reduction in CO2 generally implies a reduction in fuel usage – why not proactively look at tracking CO2 in a way that enables active management of emissions as an asset of your company?  Does your current or foreseen energy management systems enable insight into ways to reduce, to live in a cap and trade world?  Could you respond effectively to a 17% reduction in your 2005 emissions or more or less?

Source: Inventory of US Greenhouse Gas Emissions and Sinks (April 2009)