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Improving product recovery decisions through enhanced product information Ajith Parlikad, Duncan McFarlane, Anand Kulka

Improving product recovery decisions through enhanced product information Ajith Parlikad, Duncan McFarlane, Anand Kulkarni 05 th April 2005. Overview. Introduction to the problem Linking product information with product recovery decisions Enhancing product information with “networked RFID”

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Improving product recovery decisions through enhanced product information Ajith Parlikad, Duncan McFarlane, Anand Kulka

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  1. Improving product recovery decisions through enhanced product information Ajith Parlikad, Duncan McFarlane, Anand Kulkarni 05th April 2005 1

  2. Overview • Introduction to the problem • Linking product information with product recovery decisions • Enhancing product information with “networked RFID” • Improving product recovery decisions with enhanced product information • Conclusions 2

  3. The Problem Government Regulations • WEEE Directive • RoHS Directive Other financial benefits… 3

  4. WHAT CAN BE DONE? • Recycle • Not cost-effective • Not environment-friendly • Refurbish/Reuse • Desired option • Problem: Information availability Reuse Future Refurbish Cannibalise Current Recycle Dispose Volume 4

  5. Research Question How does ready availability of product information affect the effectiveness of product recovery decisions? How can we quantify the impact of information availability on product recovery decisions? 5

  6. Case Studies • 12 companies • 3 computer remanufacturers • 3 photocopier remanufacturers • 1 phone remanufacturer • 3 computer dismantlers • 2 white goods recyclers 6

  7. Product recovery operations 7

  8. Information Requirements • Current specifications (‘Decision enablers’) • Material content • Original specifications • Later modifications • Residual life (‘Decision verifiers’) • Reliability • Age • Usage • Maintenance • Current condition 8

  9. Information “Loss” Aero engines, Caterpillar,... Photocopiers, Automobiles,... High Toasters, Blenders,... Information associated with product Remanufacture Resale Disposal Low Production Retail Usage Product lifecycle stage 9

  10. Product Identification 10

  11. Information availability 11

  12. Linking Product Recovery Decisions to Information Quality • Uniqueness • to enable individual information trails for each unique object throughout its lifecycle and across the whole supply chain. 12

  13. Decision – Cost/Revenue Value Threshold Time Linking Product Recovery Decisions to Information Quality • Timeliness • to ensure that information is readily available for decision-making and execution process with minimal need for manual inspection or testing. 13

  14. Dell P2 500MHz; 128MB RAM; 20GB HDD… Dell P2 500MHz; 512MB RAM; 100GB HDD… Linking Product Recovery Decisions to Information Quality • Completeness • to ensure that all relevant information is available for optimising decisions. • Accuracy • to reduce or eliminate inaccurate representations of current and historical product information. 14

  15. A Networked RFID Solution for PLM D584.S421.CC21.AA21 F127.C238.DF1B.C7CC CD135.EEA2.DCF5.12DD BA132.FFA2.DEF1.12ED 1E1D.DD13.14CC.AC3B 15

  16. EPCtm Network TechnologyBuilding Blocks EPC Application ONS URL EPC PML Savant Local Remote EPCIS EPCIS RF Reader 16

  17. Information Quality <-> EPC • Uniqueness • Enable unique product “footprint” • Completeness • Ensure availability of relevant product info • Timeliness • Ensure “ready” availability of product info • Accuracy • Reduce/eliminate errors in info management ––> EPC ––> EPCIS/ONS/XML ––> RFID/Filtering ––> RFID/XML 17

  18. Networked RFID for PLM EPCIS Discovery Service EPCIS EPCIS EPCIS EPCIS Date of manufacture Parts/ materials used (Dis)assembly recipe Retail End-of-Life Manufacture Usage/Maintenance 18

  19. Networked RFID for PLM EPCIS Discovery Service EPCIS EPCIS EPCIS EPCIS Date of manufacture Parts/ materials used (Dis)assembly recipe Date of sale Warranty details Parts replaced Retail End-of-Life Manufacture Usage/Maintenance 19

  20. Networked RFID for PLM EPCIS Discovery Service EPCIS EPCIS EPCIS EPCIS Date of manufacture Parts/ materials used (Dis)assembly recipe Date of sale Warranty details Parts replaced On-board data Usage history Parts installed Retail End-of-Life Manufacture Usage/Maintenance 20

  21. Networked RFID for PLM EPCIS Discovery Service EPCIS EPCIS EPCIS EPCIS Date of manufacture Parts/ materials used (Dis)assembly recipe Date of sale Warranty details Parts replaced On-board data Usage history Parts installed Parts/materials identified Disassembly history Retail End-of-Life Manufacture Usage/Maintenance 21

  22. EPC xyz 1 “Where can I find information about EPC xyz?” EPC xyz “Tell me which part was replaced” 2 Networked RFID for PLM ONS EPCIS Discovery Service “100 GB HDD” EPCIS EPCIS EPCIS EPCIS Date of manufacture Parts/ materials used (Dis)assembly recipe Date of sale Warranty details Parts replaced On-board data Usage history Parts installed Parts/materials identified Disassembly history Retail End-of-Life Manufacture Usage/Maintenance 22

  23. EPCIS or Component-level tagging EPCIS or Sensor Data RFID-enabled Product recovery Information gathered Functional Condition Usage Rate Age Current Specifications Original Specifications History Logs Model Testing Brand Inspection Product Type Book-in Manual Barcode RFID 23

  24. A Bayesian Product Recovery Decision model Decisions D Utility of a decision = f (certainty, payoff) States/Hypotheses U Utilities Product Components ... Component 1 Component 2 Component n Features/ Evidences ... Feature 1 Feature 2 Feature m-1 Feature m 24

  25. 1 2 3 4 5 6 7 8 EPC enabled information Quicker decisions Certainty Higher Utility Utility (t) Payoff EPC enhanced product recovery decisions Time Test 1 Test 2 Test 3 Test 4 1 2 3 4 5 6 7 8 Information 25

  26. CONCLUSIONS • Process improvements • Quick and possibly automated identification & sorting • Error reduction • Decision improvements • Better estimation of residual life and value • Better estimation of recyclable material content • Rich information leads to better decisions 26

  27. Thank You ajith.parlikad@cantab.net http://www.ifm.eng.cam.ac.uk/cdac http://www.autoidlabs.org.uk 27

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