PROCESS OPTIMISATION using MODEL BASED CONTROL IN THE MELTER

1. PROCESS OPTIMISATION usingMODEL BASED CONTROLIN THE MELTER

2. “We have millions of dollars invested in our plant…” “…are we getting the most from our processes?”

3. “We’re designing a complex integrated process…” “…how do we know it’s going to work?”

4. “We have a complex control scheme…” “…how do we know it will run our plant to it’s optimum efficiency?”

5. The Answer – Adaptive Model Based Control ADVANCED CONTROL SOLUTIONS INC

6. The way PID control works • Cannot easily control long dead time processes • No action taken until process pushed off target • Doesn’t respond well to non-linear processes • Can’t handle process disturbances quickly Most PID control loops are detuned or not performing as intended because the loop is out of tune with the dynamics of the process

7. The result of poor PID control: • Increased process variability • Inconsistent product quality • Lower production rates • Higher energy costs • Decrease in overall plant efficiency • Leads to Acceptance of controlling what you can – not what matters • Dependence on experienced operators to manually run, start up, and recover critical processes

8. MBC out performs PID MBC out performs PID because of its two main components: • An adaptive model • A predictive controller

9. The MBC advantage • Integrates with existing control systems • Average implementation time is less than 2 weeks • Ease of use — customer can deploy and maintain with existing manpower • Attractive project economics (Payback) • Operates reliably 100% of the time

10. Adaptive Model Based Control • Builds and adapts its own live models during normal plant operations • Models are built in closed loop while the plant is running • Patented methodology builds high fidelity models in real time without disrupting operations • This patented method is the key to our fast implementation • Models adapt as the dynamics change due to weather, wear, and other factors

11. predictive controller • Accurately forecasts process responses and accounts for multiple objectives • Predicts and prevents disturbances before process is pushed off target • (PID cannot do this, PID must wait for the error) • Start ups and grade changes are automated and uneventful • Solves difficult process control problems • Achieves automatic control of manually controlled processes

12. MBC runs where YOU decide, in one or multiple places DCS Engineering Station DCS Operator Station DCS Controller • If you have OPC, you can run Model Based Control • MBC can run on your DCS or on its own server • MBC can simultaneously communicate to multiple PLCs Ethernet MBC SERVER PLC Ethernet, Modbus Plus, Data Highway Plus

13. Building the Adaptive Model

14. The impact of improved control, closer upper and lower set point limits Operating Average Shift Low Set Point. Limit Operating Average High Set Point. Limit Low Set Point. Limit Energy Cost Productivity and Yield Product Quality

15. Glass melter temperature Glass furnace level Channel temperature Forehearth temperatures 9 point grid temperature Gob exit temperature Large Energy consumers Bottlenecks Annealing oven Bottle weight MBC Applications

16. Results • Float Glass – Stabilize at new setpoint in 4% of the previous time. • Fiberglass – huge reduction in variability and improved machine availability. • Float Glass Level Control – reduction in variance. • Lighting Glass – Reduce Temperature variation in Furnace and Forehearth. • Container – increase in line efficiency –increase profit annually.

17. MBC How to set it up? • Installed on an NT desktop PC • Communication to Existing Control System via Ethernet / OPC Server • Initial Models Developed from Historical Data Review • Models validated with one setpoint change • Entire system installed and operational in less than one week

18. MBC Results • Improved process dynamics • Reduced level control variations • Steady state control improved by 7X • Scrap rates reduced • Product change time reduced:

19. Product Changeover MBC vs PID

20. Level Control – Steady State

21. Level Control - PID

22. Level Control-MBC

23. Container Application • MBC installed and connected to existing Forehearth PLC or SLC control system • Goal was to improve stabilization time in forehearths after pull / product change. • Allow operators to focus on machine changes and control loops stay in automatic.

24. Container Glass Results • Forehearth Temperature stabilization time reduced by 50% after job changes – leading to more machine availability at optimum conditions • Ability to control using Mass Flow Temp (9-point grid as control parameter • Ability to control using Gob Exit Temperature as control parameter • Increased yield, 0.5 to 1% due to improved process stability.

25. Pull Change – conventional

26. Pull Change - MBC

27. Steady State Control

28. Fiberglass Manufacturing • Goal is to stabilize process & reduce variability in downstream processes. • Level control in melt tank is primary cause of defects. • MBC connected to existing DCS via OPC server.

29. Fiberglass Results • Profoundly stabilized system • Better bushing control • Reduced spinner blockage • Better quality • Higher production rates

30. Fiberglass Melter Temp

31. Float Glass Project • Major manufacturer of Flat/Float Glass • Level control variability decreases product quality • Installed to existing DCS • Commissioned in only 2 days • Immediate profound effect in operation

32. Increased Glass Level Stability

33. Melter Crown temperature stability

34. Reduction In Exit Temp Variation

35. Float Glass - PID

36. Float Glass - MBC

37. Float Glass Results “The control continues to be excellent. We had a port failure Tuesday night that took the MBC offline. For the 8-10 hours that we were back in DCS control, our level control was +/- 0.015", while MBC was able to maintain +/- 0.002". I printed the 24-hour trend chart for that period showing MBC controlling for 7 hours, Bailey DCS for 10 hours, and back to MBC for the remaining 7 hours and the charts show a graphic picture of why we need MBC for controlling glass level in our furnace!” – Ernie Curley, QA Manager, Cardinal Glass – Portage, WI

38. Testimonial “ In PID control, our level control was +/- 0.015", while MBC was able to maintain +/- 0.002”; the charts show a graphic picture of why we need MBC!” Ernie Curley, QA Manager, Cardinal Glass PID Level Control BrainWave Level Control >7 times better level control with MBC

39. Lighting Glass Optimization • Major manufacturer of Lighting Glass • Temperature Control Critical for proper forming • Installed to existing TI PLC environment • Commissioned in only 1 week • Immediate profound effect in operation

40. Lighting Glass Results • Dramatic Reduction in variability • Complete Automatic Control • Improved recovery from disturbances • Reduced operator workload • Reduced scrap • Increased profits

41. Testimonial “MBC stabilized our toughest loops – ones we have spent countless hours working on .” Steve HolmesSenior Process Controls EngineerBowater Newsprint

42. Testimonial “ This was something that could be done immediately with very little cost. And it did not require any outages; it was done on the run.” Andrey PawelczakContract Engineer, Syncrude Canada

43. MeadWestvaco Testimonial “ Reducing Lime Kiln temperature variability with MBC was easy and it reduced our fuel consumption over $400,000/year!” Our operators love it and rely on it for efficient operation. Terry Canup, Process & IT Manager, MeadWestvaco Before: +/- 90 degrees or more MBC +/- 5 to 10 degrees 88% improvement by control with MBC