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Cost Based Decision Support System Development

Cost Based Decision Support System Development. Project 4 Xiaochang Li Masaki Watanabe Purdue University. Project Team. Mentor Mr. KN Swaminathan Mr. Richard Gomez Member Masaki Watanabe Purdue MBA Student 6 years working experience at Nissan Xiaochang Li

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Cost Based Decision Support System Development

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  1. Cost Based Decision Support System Development Project 4 Xiaochang Li Masaki Watanabe Purdue University

  2. Project Team • Mentor • Mr. KN Swaminathan • Mr. Richard Gomez • Member • Masaki Watanabe • Purdue MBA Student • 6 years working experience at Nissan • Xiaochang Li • Purdue undergraduate student • Major in industrial Engineering

  3. Project overview • Project Objective • Reduce SKUs of target parts • Scope • Forging parts • Deliverables • Identify cost drivers • Develop objective costing systems • Arrive at guidelines for application

  4. Agenda • Introduction • Definition for SKU • Benefit of reducing SKU • Competitors’ solutions • Methodology • An example of crank pin • An Example of connecting-rod • Statistical results and analysis • Standardization guideline • Recommendations • Guidelines for reducing SKU • Alternatives for reducing SKU • Learnings from India and TVS

  5. Introduction • What is SKU? • Stock Keeping Unit • Defined as an unique identifier • Why reduce SKU? • Easier data acquisition • Savings on engineering cost and lead time • Reduction on quality problems

  6. What competitor is doing Change to Port Injection 39.0x41.4 (49cc) Carburetor, 3 speed Kick start 39.0x41.4 (49cc) Port Injection, 3 speed Kick start Bore up Change to Self Start Change to 4 speed 39.0x41.4 (49cc) Carburetor, 3 speed Self start 47.0x41.4 (72cc) Carburetor, 3 speed Kick start 39.0x41.4 (49cc) Port Injection, 4 speed Kick start

  7. Insights from production line

  8. Methodology

  9. An Example of Crank Pin Data Table 1

  10. Access Data from SAP

  11. How to identify key parameters • Basic Criteria • Look at dimensions with tight tolerances • Record parameters when • Share interface with other parts • affecting the functionality of engine • special treatment is applied • Always record weight

  12. Methodology

  13. ICD/MiniTab Data Entry

  14. MiniTab Statistical Tests

  15. Cost Driver Identification

  16. Cost Objective Function Derived from the previous step

  17. Adjustment of Trend

  18. Adjustment of Trend Price= - 72.9 + 0.000017 Volume + 4.22 Diameter Adjustment Amount = Actual Price - Theoretic Price = 31.93 – 32.61 = -0.68 Adjusted Price= - 73.58 + 0.000017Volume + 4.22Diameter

  19. Methodology

  20. Criteria for Standardization • Purpose: find similar parts and do standardization • Two approaches to follow • Look at all parameters • Identify significant parameters by engineering knowledge • How to do standardization • Eliminate parts with low production volume • Standardization by looking at the cost drivers

  21. An Example of Connecting-Rod Data Table 2

  22. Cost Objective Function

  23. Input Material Cost Input Material Cost = 0.04 Rs/g * Input Material Weight Input Material Weight = Final Parts Weight * Ratio Final Pats Weight = f(Specification of Parts) Ratio = f(Specification of Part) Final Parts Weight = - 127 + 3.57 BE + 0.847 L + 3.99 W Ratio = 5.61 - 0.142 W

  24. Recap of Scrap Recap of Scrap= 0.012 Rs/g * Scrap Weight Scrap Weight = f(Input Material, Parts Weight) Scrap = - 44.0 + 0.906 *(Input Material – Parts Weight)

  25. Conversion Cost Conversion Cost= f(Parts Specification, Production Volume) Conversion Cost = - 34.1 + 2.46 SE - 3.06 W + 0.125 L + 27.1 BE/SE - 0.000005 Volume Adjusted Conversion Cost = - 34.55 + 2.46 SE - 3.06 W + 0.125 L + 27.1 BE/SE - 0.000005 Volume

  26. Recommendation • Guidelines for designers • Make new model by modifying current parts • Consider the cost drivers when designing • Standardization on varieties with small volume • Standardization on varieties with large fixed cost • Standardization based on engine model

  27. What else we can do • To Reduce Part Cost • Increase flexibility of machines and operators • Reduce fixed cost in production • To shorten R&D Lead Time • Develop e accelerated evaluation method • Collaborative R&D with suppler and manufacturing

  28. What we have learned • From India • Outstanding engineering education • Abundant manpower • Ambitions to dominate the world market • Beautiful palaces • Animal friendly city • Friendly people

  29. What we have learned • From TVS • Awareness of environmental conservation • Company Society Responsibility (CSR) • Ambitions and actions to learn, change and take risks • Team spirit

  30. WE ARE READY FOR QUESTIONS

  31. Thank You!

  32. Access Data from SAP Access the latest drawings Step 1 Search for specific part

  33. Access Data from SAP Press to search Step 3

  34. Access Data from SAP Find parts Enter key words here Step 4

  35. Access Data from SAP Step 5 Part number

  36. Access Data from SAP Go back to the main page and go to ZCV04N Step 6

  37. Access Data from SAP Step 7 2D drawings are always preferred

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