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Cost Based Decision Support System Development

A project focused on reducing SKUs of forging parts, aiming to identify cost drivers and develop costing systems for application guidelines. Includes methodology, statistical analysis, recommendations, and learnings from India and TVS.

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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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