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Are You in Control?

Are You in Control?. Jim Anderson. Why managers should be interested in improved control. Simply, because it is one of the most cost-effective ways of improving profitability Experience shows remarkable benefits from some very simple, inexpensive control improvements

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Are You in Control?

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  1. Are You in Control? Jim Anderson

  2. Why managers should be interested in improved control • Simply, because it is one of the most cost-effective ways of improving profitability • Experience shows remarkable benefits from some very simple, inexpensive control improvements • It is virtually the only technology where major improvements can be made between shutdowns

  3. Where do the benefits come from? • Improved product YIELD (material efficiency) • Reduced ENERGY consumption • Increased CAPACITY • Improved product QUALITY (& consistency) • Reduced product GIVE-AWAY • Better PLANT RESPONSE TIME • Reduced ENVIRONMENTAL IMPACT • Better safety and effective use of manpower

  4. Global Examples • Warren Centre Study • 2-6% of material and energy costs • DuPont ‘Best of Best’ • showed an average of 14% improvement • UK study • add 1/3 to annual profit

  5. Years to return investment 25 100 Frequency Cumulative % of Total 90 20 80 70 15 60 Cumulative % 50 No. of examples 10 40 30 5 20 10 0 0 0.40 0.75 1.10 1.45 1.80 >2 Years to return Years to Return Investment

  6. A Simple Question ‘What would be the effect on your plant/enterprise profit of transferring just 1% of your raw material and energy costs to the bottom line?’

  7. 40 35 30 25 20 No. of samples 15 Specification = 20 ppm 10 5 0 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 ppm Over-purification is often a good way to highlight the need for improved control

  8. 100 80 Throughput 60 40 Throughput and energy in per cent 20 Energy input 0 10 1 month There was a simple solution 3 flow controllers were converted to ratio units Result: energy savings of £250,000 p.a.

  9. Industrial Attitude to Improved Control • The Energy Efficiency Best Practice Programme (EEBPP) carried out a survey recently by to find out what companies were doing to improve the control of their processes in response to the Climate Change Levy (CCL) • Answers ranged through: • ‘We don’t need the CCL to make us improve control’  • ‘The CCL has made management take an interest in energy saving but we don’t have time’  • 'What’s the Climate Change Levy?’ 

  10. Energy Efficiency Best Practice Programme (EEBPP) • The EEBPP has identified three high priority measures for energy saving: • Combined Heat and Power (CHP) • Motors and Drives. • Process Control

  11. Current Control Performance Source: Honeywell Loop Scout 26,000 loops, multiple industries

  12. SELECT CONTROLS AND DETERMINE STRATEGY QUANTIFY THE BENEFITS PREPARE THE OPPORTUNITIES LIST ESTABLISH THE BASE CASE ESTABLISH ATEAM Benefits Analysis - the five steps to success • Establish a team to investigate the process • Establish the ‘Base Case’ • Prepare an ‘Opportunities List’ • Quantify the benefits • Determine strategy

  13. Data Data Optimisation Wisdom Control Diagnostics Advanced Control Knowledge Information Basic Process Control The Complementarity of Process Control & Diagnostics

  14. Dimensionality Reduction • Principal Component Analysis (PCA) is a linear data analysis technique which can be used to reduce the number of variables in a data set without loss of information • The results can be used to identify or eliminate linear interdependence in the variables • Projection to Latent Structures (PLS) methods can be used for prediction

  15. Geometric Interpretation of PCA • The first principal component (t1) passes through the average point and represents the direction of greatest variance. t2 represents the next greatest direction of variance and is ORTHOGONAL to t1

  16. Reduction in Dimension • If there are only two significant PCs, the data dimension is reduced to two • In practice, only a few PCs are needed to represent a process with many hundreds of ‘independent’ variables • Every PC is orthogonal to all others, i.e. truly independent

  17. Principal Component Analysis • Principal components can be plotted against time as `normal` variables • Nominal ‘in control’ data can be used to define 95% and 99% confidence bounds • Normal SPC ‘rules’ can be applied • A particularly useful presentation is the scatter plot

  18. Multivariate SPC

  19. Monitoring Scores Plot of PC7 versus PC8

  20. 2 9 5 % C o n t r o l L i m i t 9 9 % C o n t r o l L i m i t 1 Scores for Principal Component 8 0 - 1 - 2 - 6 - 4 - 2 0 2 4 Scores for Principal Component 7 Detection of a Process Abnormality

  21. Contribution of the process variables Catalyst inventory O2 partial pressure Feed partial pressure

  22. Benefits of Process Diagnostics • Significant financial benefit can be gained from the additional insight provided by Process Diagnostics leading to improved control • Recent examples: • Monitoring of reaction end-point ~£800,000/annum • Catalyst savings in a fluidised Bed Reactor ~£1,000,000/annum • Early detection of faulty reactor dosing ~£250K/annum • Improved performance in a fermentation/extraction process ~£4,500,000/annum

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