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Pi Media Type Sensing for AiO A/A4 Copy and Standalone Photo Printing Functions

Pi Media Type Sensing for AiO A/A4 Copy and Standalone Photo Printing Functions. Pi Project Team 15 Sep 06. Background Story. Customer selectable paper type is vulnerable Customers don’t know what “Plain Paper or Photo Paper” button was referring to: original media or output media

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Pi Media Type Sensing for AiO A/A4 Copy and Standalone Photo Printing Functions

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  1. Pi Media Type Sensing for AiO A/A4 Copy and Standalone Photo Printing Functions Pi Project Team 15 Sep 06

  2. Background Story • Customer selectable paper type is vulnerable • Customers don’t know what “Plain Paper or Photo Paper” button was referring to: original media or output media • No $ for Legolas sensor, Legolas sensor is not 100% correct. • Legolas sensor was used only to confirm or reject plain or photo paper type in the copy function

  3. Background Story • Need to remove a button to allow space for 1.5” CGD => simpler/better UI for cutomers

  4. Application/specific cases • Standalone copy or photo printing only and • Only on large (A/A4) size media; small media (4x6 or L size depending local setting) defaults to photo media

  5. Usage Model Pi usage model not available, this is to give a sense of the media detection • Is applied to no more than 35% of the total printed pages • Will mostly need to detect 3% (=4% x 75%) photo media over the machine life time Photo card printing information not available, estimated to be a small percentage of everyday printing

  6. Technical Model

  7. Math Model • No-Load Calibration before each job • Back EMF Correction • 3-Stage Regressive Discriminant Analysis: • Cardstock (Springhill) vs. other • Everyday Photo vs. other • Plain vs. Photo

  8. Calibration Problem:Plain and Photo Paper PWM Pick Profiles can be Indistinguishable Due to Variations in: • Motor temperature • Motor torque constants • Part dimensions and friction • Ambient temperature and humidity • Power supply voltage • Life (wear) Proposed Solution:Perform a No-Load PWM Calibration before every Job

  9. No-Load PWM Calibration Details: • Average PWM is measured before each pick • at a no-load shaft speeds of 5 ips and 20 ips. • The PWM values are corrected for back-EMF to approximate • the effective no-load system torque constant. • The resultant linear no-load PWM-to-Torque relationship is used • to convert all raw pick profile data into the equivalent calibrated no-load torque. As a Result: The differences between each calibrated pick profile should now be mostly due to paper differences only.

  10. Calibration Example Using Hot Motor Data:

  11. Cont: Calibration Example Using Hot Motor Data:

  12. Discriminant Analysis:The following calculations are applied to the select zones 1-7 for each profile: • Sum • Mean • Standard Deviation

  13. Discriminant AnalysisSample Equation:

  14. Latest Classification Results(For life test units @ 10K, 15K, 20K) Stage 1: Springhill (Plain) = 99.31% Stage 2: Everyday (Photo) = 71.72% Stage 3: Yamayuri (Plain) = 100% HP Printing (Plain) = 100% Premium Inkjet (Plain) = 99.31% Premium Presentation (Plain) = 97.93% PremiumPlus (Photo) = 97.24% Brochure (Photo) = 71.03%

  15. Path Forward • Refine Back-EMF Correction • Refine Discriminant Analysis • Chamber Data • Guarantee Pick/Load move does not change • Look a point in profile that OOPS flag trips to select a zone or to set the zero reference point for zones • Look at distance between trip point to top of form as an additional discriminator • Talk to Scott Smith (load profile insight) • Add the new Advanced Photo paper to analysis • Measure competitor’s media classification results • Perform T-Test on Everyday Media only

  16. Future Improvements • Modify pick/load move to emphasize paper differences • Add additional load moves real-time based on analysis to verify suspected media type

  17. Summary • Latest results look very promising • Continue refining analysis • Continue collecting data

  18. Backup

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