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DOE Applications

DOE Applications. Oct 16th 2002 ASQ Section 702: San Gabriel Valley by Dr. Raj Palanna. Objective of Talk. Give a “flavor” for actual applications of DOE in industry Provide an insight into how complex theoretical concepts are applied in real-world situations

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DOE Applications

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  1. DOE Applications Oct 16th 2002 ASQ Section 702: San Gabriel Valley by Dr. Raj Palanna

  2. Objective of Talk • Give a “flavor” for actual applications of DOE in industry • Provide an insight into how complex theoretical concepts are applied in real-world situations • Build on the ASQ 702 September presentation DOE - Basic Concepts by Dr. Kurt Palmer

  3. Agenda • Deep Dive - 2 Examples • Quick High Level Overview - Few More Applications • Q&A * These examples are taken from applications at different companies. Some of the data and facts have been “coded” to protect proprietary information.

  4. 1. ECS Pack Switch Failure Investigation • Starting February 2002 (until April 2002) a total of 21 switches have been rejected at XXX Aircraft Company’s aircraft test line, for failure to “open” at max. 200 deg. F. • Shipments of multi million dollar aircraft are at risk

  5. Key Planning Aspects • Immediate containment actions taken • Teams working at 3 tiers of supply chain • Evaluate the “usual suspects”* • Testing setup and process • Manufacturing process • Application at system level, etc • Different schools of quality uses slightly different methods for this exercise * This presentation will concentrate only on the DOE aspect of the problem

  6. DOE Problem Statement • Parts that failed at customer passed at supplier test process. Test method is a suspect. A DOE was set up to understand the sensitivity of switches to the test parameters • 6 Parts were chosen for DOE - 3 New, 3 Rejected

  7. DOE Pre-planing • A complex DOE THOUGHT MAP was developed • Factor Selection • Response Selection • Measurement Repeatability Studies • Noise Impact • Confounding • Randomization • Resource Logistics • Management Approvals • Observation/ Copious Notes • etc

  8. DOE Orthogonal Matrix Building Exercise • You Have Been Tasked to Optimize Gas Mileage on Your Car • Team Needs to Test 4 Factors • Has Resources for 8 Runs • Res. IV Confounded Design in Acceptable (Don’t worry if you don’t understand this bullet!!) • What is the DOE Matrix?

  9. DOE Matrix 24-1ResIV

  10. DOE Analysis:“Rejected” Switches Average Trigger Temperature Type of TESTING OIL (C) influences test results and Type of MOUNTING (D) influences test results

  11. DOE Analysis:“New” Switches Average Trigger Temperature No Impact of Factors A, B, C and D on “New” Switches

  12. Spread of Results Under Different Testing Conditions Switches from New Batch Higher Spread Has been Observed in “Rejected Switches” Switches from Customer ‘Rejected” Batch

  13. Historical Review of Test Data to Evaluate Process

  14. Conclusions • A particular batch of switches were found to be in under-fill condition and switches became “sensitive” to testing parameters/ operating conditions and lost its robustness to environment • Manufacturing process was fixed • Test was augmented to prevent this situation from happening again

  15. 2. Aircraft Motor Performance Optimization • Problem statement: shop failures at test. Brake was releasing under the “brake release voltage specification” • Evaluate the “usual suspects” • Testing setup and process • Manufacturing process • Application at system level, etc • Developed a DOE thought map

  16. DOE Matrix .. Motor 25-1ResIV

  17. Use : • Run-In • High Armature TIR • Flat Disk

  18. With Low Disk Flatness Use 3 mm (Low) End-Play.

  19. Test for Statistical Significance Results Are Statistically Significant

  20. Randomness Test There is No Unusual Observations

  21. Conclusions - Motor DOE • Experiment showed statistical significance. • Settings for Static Brake • Brake Cycling….Introduce Brake Cycling in MOT- Chuck • High Armature TIR.???? Do we ask for “bad parts”? • Flat Disk….Within 1/10th..Need Process Control • With Low Disk Flatness Use 3 mm(Low) EndPlay. (With Flat Disk Set Low EndPlay). Change MOT - Chuck. • This will improve Static Brake Problems.

  22. 3. Nozzle Air Flow Optimization DOE • Problem statement: air cycle machine nozzle hole-to-hole variation need to be minimized to improve system performance • Process: multi spindle drilling • DOE response: diameter sigma between different holes in a single nozzle • Factors: machining factors • Reamer speed, Reamer feed, Reamer diameter, Stock (after drilling)

  23. 4. Vapor Cycle Pack Bearing Failure Investigation • Problem statement: bearing failures of VCS pack on aircraft • Type of DOE: design robustness evaluation • Response: measure of fatigue on the bearing after specified run time • DOE factors: product design variables

  24. 5. DOE for Car Door Panel Delimitation Problem • Problem statement: delaminating of vinyl from the foam substrate of an car door interior • Process: door panel molding process • Response: lamination evaluation on a likert scale + measure of area of delaminating • DOE factors: molding machine factor • Overall temp, Heat upper, Heat lower, Oven temp, Backing type, Density, Vacuum pressure, Vacuum delay

  25. 6. Actuator Pin Alignment DOE • Problem statement: aircraft door actuator connector pin alignment out of specification • Type of DOE: combination assembly process evaluation plus design features evaluation • DOE response: distance from nominal in circular domain • DOE factors: assembly technique variables plus part features • Twist, Length, Sleeve

  26. Practice Idea:Gas Mileage Optimization DOE • Problem statement: pick a response variable to optimize on the car (gas mileage…) • Choose factors that might influence this output response variable • Setup the DOE, run the DOE, analyze DOE • Other ideas: • Optimize volume of popcorn produced • Etc……. Any suggestions from audience? DOE Is Not the Easiest Application Tool Around Town…. But If You Master DOE, You Will Be a Champion QE!! Practice, Practice, Practice

  27. Appendix • Reference Books • Douglas C. Montgomery: Design and Analysis of Experiments • Ronald D. Moen Et Al.: Improving Quality Through Planned Experimentation • Madhav S. Phadke: Quality Engineering Using Robust Design • Software • Minitab • JMP • Etc

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