October 9, 2009

Exceptional Opportunities in Process Control - Online Metrics

By Greg McMillan

The opportunity afforded by online metrics is worth summarizing in this series even though it has been discussed in several entries on this website.

The need to cut costs has translated to an increased emphasis on process efficiency and the ability to justify software, hardware, and personnel. Increasingly these need to be hard benefits (e.g. reduction in raw material, downtime, and energy costs).

When I worked in process control improvement (PCI) in the technology department of a large chemical company, we had to show new benefits each year that were at least twice our salary to justify our job. By the end of the five year process control improvement effort we had 75 million dollars per year in savings documented. The PCI core group had 5 modeling and control specialists working with 20 or more process control engineers at key plants. The benefits reported depended upon the skills of particularly one person Glenn Mertz) who was extremely proficient in cost sheet analysis and working with operations and process technology.

Some companies are fortunate enough to have PCI as part of their culture as seen in the Control Talk Columns "Going, Going, Gone - Part 2" (September) and Part 3 (October) for examples. For many companies, benefits need to be reported in order for PCI and our profession to move forward or even exist. See the December 1 and 5, 2008 entries on this website "Past, Present, and Future of Automation - Part 5 (Benchmarking and Opportunity Assessment)" and Part 6 (Operator Interface) and the December 28, 2007 entry "Biggest Opportunities in Process Control Improvement - The Operator (Online Metrics) for more discussion of the aspects and importance of identifying and showing PCI benefits.

There are a lot of initiatives in the plant to improve plant operation by better operating procedures, equipment, and maintenance. All of these people take great pride in their work and are naturally eager to attribute better process operation to their efforts. Process technology often has the last say. The best way for PCI to get credit for improvement in plant operation is for the improvement and change to be visible in the data historian. A visible change in capacity, efficiency, or quality after a change in the process control system provides the documentation needed. If the PCI could be turned on and off, the correlation would be irrefutable but this is usually not practical. If no other events occurred when the PCI went online, a beginning of improved plant operation coinciding with the completion of the PCI, and a good explanation of cause and effect, will normally suffice for PCI to get credit. To help guide management and operations, comments should be entered in the historian and event makers for PCI provided.

PCI metrics for continuous process capacity are generally available from product flow measurements, downtime due to trips, and the time to startup or make a product grade transitions. PCI metrics for batch process capability can be generated from batch size, end point concentration, batch cycle time, and time in between batches. Quick and dramatic improvements in batch capacity have been achieved be the elimination of operator attention requests, manual actions, trips, and wait times for resource allocation (e.g. utility or charge systems), lab results, and reaction completion. Model predictive control and override control applications have been very successful for fed-batch processes. Reductions of 25% or more in batch cycle time are common for PCI. For a summary of some of the many possible batch control opportunities see BatchCycleTimeReduction.pdf from my PCI days.

PCI metrics for process efficiency are best expressed as a ratio of kilogram (pound) of input used (e.g. feed, fuel, reagent, and utility) per kilogram (pound) of product produced. For fuels, the numerator in the ratio may be expressed in thermal units, such as kilojoules (BTUs). For batch processes, the totalized input flow is divided by the batch size multiplied by the fractional product end point concentration. For continuous processes the instantaneous input flows are divided by intermediate or final product flow multiplied by the fractional product concentration. Synchronization of input flows to output flows can be done by the addition of a time constant equal to residence time and a time delay equal to the transportation delay. The flows can be totalized to compare shifts and periods of operation. Online process efficiency measurements require online or at-line analyzers or inferential measurements from first principle, neural network, polynomial, or statistical (e.g. PLS) models. These models in turn require flow measurements because nonlinear valve characteristics, backlash, and stick-slip make the use of controller outputs directly as model inputs ineffective and misleading. While reactant and fuel flows are typically measured, utility and reagent flows are often not. This short sightedness by plant projects (figuratively and literally), severely limits the ability to make improvements in the efficiency of use of these process inputs. I would wager a 10% reduction in the use of these inputs would more than pay for the flow meters. The old saying, you cannot control what you don't measure holds true for process efficiency. If I was a project manager, I would have a flowmeter on any input flow whose usage cost per year exceeded twice the installed cost of the flowmeter. I would at least provide the process connections for inserting a mobile wireless flowmeter. Where energy heat transfer rate calculations (e.g. heat removal rate as an inference of reaction rate) would be useful, I would install wireless RTD temperature transmitters on the streams entering and exiting the coils, exchangers, and jackets. Wireless transmitters allow the user to find during actual process operation the applications with the maximum benefit.



10 Comments

Modern process control like this may gain performance by nanotechnical factor system analysis, which depends on the atomic topological function applied to exact quantum and relativistic material, force, or energy features.
Recent advancements in quantum science have produced the picoyoctometric, 3D, interactive video atomic model imaging function, in terms of chronons and spacons for exact, quantized, relativistic animation. This format returns clear numerical data for a full spectrum of variables. The atom's RQT (relative quantum topological) data point imaging function is built by combination of the relativistic Einstein-Lorenz transform functions for time, mass, and energy with the workon quantized electromagnetic wave equations for frequency and wavelength.

The atom labeled psi (Z) pulsates at the frequency {Nhu=e/h} by cycles of {e=m(c^2)} transformation of nuclear surface mass to forcons with joule values, followed by nuclear force absorption. This radiation process is limited only by spacetime boundaries of {Gravity-Time}, where gravity is the force binding space to psi, forming the GT integral atomic wavefunction. The expression is defined as the series expansion differential of nuclear output rates with quantum symmetry numbers assigned along the progression to give topology to the solutions.

Next, the correlation function for the manifold of internal heat capacity energy particle 3D functions is extracted by rearranging the total internal momentum function to the photon gain rule and integrating it for GT limits. This produces a series of 26 topological waveparticle functions of the five classes; {+Positron, Workon, Thermon, -Electromagneton, Magnemedon}, each the 3D data image of a type of energy intermedon of the 5/2 kT J internal energy cloud, accounting for all of them.

Those 26 energy data values intersect the sizes of the fundamental physical constants: h, h-bar, delta, nuclear magneton, beta magneton, k (series). They quantize nuclear dynamics by acting as fulcrum particles. The result is the picoyoctometric, 3D, interactive video atomic model data point imaging function, responsive to keyboard input of virtual photon gain events by relativistic, quantized shifts of electron, force, and energy field states and positions.

Images of the h-bar magnetic energy waveparticle of ~175 picoyoctometers are available online at http://www.symmecon.com with the complete RQT atomic modeling manual titled The Crystalon Door, copyright TXu1-266-788. TCD conforms to the unopposed motion of disclosure in U.S. District (NM) Court of 04/02/2001 titled The Solution to the Equation of Schrodinger.



It is trivial when compared to either a simple battery or the energy required to produce the magnet.

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The opinions expressed here are the personal opinions of Greg McMillan and Terry Blevins. Content published here is not read or approved by Emerson before it is posted and does not necessarily represent the views and opinions of Emerson. © 2006-2010 Greg McMillan and Terry Blevins. All rights reserved.