DOC PREVIEW
ISU IE 361 - Engineering Feedback Control and Statistical Process Monitoring

This preview shows page 1-2-3-4-5 out of 15 pages.

Save
View full document
View full document
Premium Document
Do you want full access? Go Premium and unlock all 15 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 15 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 15 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 15 pages.
Access to all documents
Download any document
Ad free experience
View full document
Premium Document
Do you want full access? Go Premium and unlock all 15 pages.
Access to all documents
Download any document
Ad free experience
Premium Document
Do you want full access? Go Premium and unlock all 15 pages.
Access to all documents
Download any document
Ad free experience

Unformatted text preview:

1EFC and SPM(Engineering Feedback Control and StatisticalProcess Monitoring)(Section 3.6 of Vardeman and Jobe)2EFC is Process Guidance/On-Line Adjustment3SPM is “Process Watching” forPurposes of Change DetectionProcessMeasurement System4SPM and EFC are NOTCompeting Technologies• Both have their places• Both can be badly done• Both can contribute to variation reduction inan industrial process• Neither is a “weak version” of the other• In many applications EFC creates thephysical stability SPM monitors5Contrasts (V&J Table 3.10)EFC• “automatic”• compensation-oriented• expects process “drift”• on-going “tweaking”• typically computercontrolled• maintains optimaladjustment• tactical• can exploit modelsSPM• often manual• detection-oriented• expects “stability”• triggers intervention• typically a humanagent intervenes• warns of “specialcause” changes• strategic• warns of departurefrom model6SPM and EFC Technologies• SPM– Well known Shewhart control charts (assumedtoday)– Some fancier monitoring schemes(multivariate, EWMA, CUSUM)• EFC– Huge literature and highly specializeddiscipline– Simplest version is probably “PID” control(example here for sake of concreteness)7Paper Making (Example 3.6)pumppulptankweightsensorfinished (dry)paper about 4 minutes?algorithm?8Issues in Algorithm Development• Pulp mix thickness WILL vary ... pumpspeed can be used to compensate• This is NOT an SPC problem! (it is anautomated compensation problem)• Target is 70 g/• 1 “tick” on pump dial changes density about.3 g/• Time delay and potential for over-compensation/oscillation are serious issues2m2m9Algorithm Development• To remove the time delay issue, a 5-minutesampling/adjustment interval was adopted• Problem 3.38 gives baseline/no-adjustmentdata10More Algorithm Development• PID control algorithm is21232 ()()()()for ()density at time ()knob change after seeing () ()"error" at time ()() ()()(1) ()(())()(1)XtEtEtEtYttXtYtEttTtYtEtEtEtEtEtEtEtκκκ∆=∆++∆=∆===−∆=−−∆=∆∆=∆−∆−11Interpretation• “Integral” part of the algorithmreacts to deviations from target/offset• “Proportional” part of the algorithmreacts to changes in error (/level)• “Derivative” part of the algorithmreacts to curvature on plots of error2()Etκ1()Etκ∆23()Etκ ∆12Example Calculationst T(t) Y(t) E(t)()Et∆2()Et∆ ()Xt∆1 70.0 65.0 5.02 70.0 67.0 3.0 -2.03 70.0 68.6 1.4 -1.6 .4 1.3284 70.0 68.0 2.0 .6 2.2 5.6445 70.0 67.8 2.2 .2 -.4 3.4866 70.0 69.2 .8 -1.4 -1.6 -1.1622(().83()1.66().83())XtEtEtEt∆=∆++∆13More Algorithm Development(See Problems 3.39-3.43)• Tuning constants/“control gains” weredeveloped through a series of experimentaltrials (essentially sequential DOX)• Starting point was withmotivated by the “1 tick produces .3 g/change” information()3.33()XtEt∆=2m14Final Weight Consistency wasMuch Improved … SPM?• Compare the last 6 periods of Table 3.9with the baseline behavior on slide 9 (BTW,this is much better than the manufacturer’salgorithm!)• To this point, we have an EFC successstory• SPM now could have a role in monitoringfor unexpected changes from this behavior!15Workshop Exerciset T(t) Y(t) E(t)()Et∆2()Et∆ ()Xt∆1 4 02 4 23 4 24 4 35 5 36 5


View Full Document

ISU IE 361 - Engineering Feedback Control and Statistical Process Monitoring

Download Engineering Feedback Control and Statistical Process Monitoring
Our administrator received your request to download this document. We will send you the file to your email shortly.
Loading Unlocking...
Login

Join to view Engineering Feedback Control and Statistical Process Monitoring and access 3M+ class-specific study document.

or
We will never post anything without your permission.
Don't have an account?
Sign Up

Join to view Engineering Feedback Control and Statistical Process Monitoring 2 2 and access 3M+ class-specific study document.

or

By creating an account you agree to our Privacy Policy and Terms Of Use

Already a member?