P an American A lliance for S upply I mprovement: Beverly Kris Jaeger Alejandro MacCawley - PowerPoint PPT Presentation

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P an American A lliance for S upply I mprovement: Beverly Kris Jaeger Alejandro MacCawley

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  1. Pan American Advanced Studies InstituteSimulation and Optimization of Globalized Physical Distribution SystemsSantiago, Chile August, 2013 PASI Project: Case #2 Pan American Alliance for Supply Improvement: Beverly Kris Jaeger Alejandro MacCawley Marie-Eve Rancourt Carlos Solorio-Magana ShanthiMuthuswamy

  2. There’s a challenge to be met … • Agenda • Introduction • Current State • The Mission • Methods • Models & Paths • Calculations & Computations • Solution Options • Implications • Further considerations • PASI Objectives Interpretations & Assumptions

  3. Problem Overview: Case 2  • What do we ‘know’? • Introduction

  4. Problem Overview • 6 Manufacturing Plants • Newark NJ, St Louis MO, Springfield MO Memphis TN, Fort Worth TX , & Mexicali • 5 Current Distribution Centers • Canada: Toronto • USA: Salt Lake, Tulsa OK Allentown PA, Atlantic City, NJ • 2 Candidate DCs • Oakland CA • Los Angeles DC ? • Introduction

  5. Problem Overview • DC Leases Expiring in 18 months: • Toronto • Salt Lake City • Customers • Retailers across US and Canada • US Customers must be serviced by a US-based Distribution Center DC • Introduction


  6. CC CU To O SL AL NW MP LA SL Tu MC AT SP FW Mfg DC ? C • Introduction

  7. Problem Formulation Decisions Objective • Introduction • Active/open DC (yj) • Size of new DC (S) • Outbound flows (xjk) • Inbound flows given (% from each plant) Minimize: • Fixed & variables costs for the active DC(s) • The fixed cost of new DC is a function of S • Transportation costs • Inbound and outbound

  8. What is our mission? • Measurable challenges • Reduce total supply chain costs • Reduce delivery times • Solution(s) • Solution(s) • Introduction

  9. The Challenges, Q1 & Q2 • Q1: ID optimal location in Western NA • Salt Lake City (SL) • Los Angeles (LA) • Oakland (O) • Q2: ID optimal location serving Western CAN • Salt Lake City • Toronto (T) • LA or O • Introduction

  10. Q1 & Q2: Global Approach • Salt Lake City USA (as is currently) CAN • Oakland USA (candidate) CAN • Los Angeles USA (candidate) CAN SL O LA • Introduction

  11. Q1 & Q2: Global Approach • Salt Lake City USA Toronto CAN • Oakland USA Toronto CAN • Los Angeles USA Toronto CAN T SL O T T LA • Introduction

  12. The Challenges, Specific • For location serving Western North America: • Sizing of DC for peak inventory • Impact to inventory, freight, transit time, & DC costs • For locationserving Western CAN: • Sizing of DC to support customer demand • Associated costs for DC • Introduction

  13. Our Approach as a Team • Method

  14. Fundamental Phases • Plant to DC • Within DC • DC to Customer DC DC DC • Method

  15. Fundamental Phases • Plant to DC • Within DC • DC to Customer DC • Method

  16. Plant to DC DC • Method

  17. Plant to DC DC • Shipping distance & rates/mile • Method

  18. Plant to DC DC • Given factors: • Truck can drive 500 miles/day • Average of 40K lbs/shipment • Ship combination of TL & LTL • 100% of freight paid by Plant • Assumptions: • Only ground freight used • Method

  19. Plant to DC: Inbound Trans. • Method & Model

  20. Fundamental Phases • Plant to DC • Within DC • DC to Customer DC DC DC • Method

  21. Fundamental Phases • Plant to DC • Within DC DC to Customer DC • Method

  22. DC to Customer DC • Method

  23. DC to Customer DC • Method

  24. DC to Customer DC • Given factors: • Truck can drive 500 miles/day • Average of 25,000 lbs/shipment • Ship combination of LTL &TL • 100% OB freight paid by Plant • US DC serves US customer • Assumptions • No stop charges • Pallet weight includes tare & product • Method & Model

  25. DC to Customer • Model: • Method & Model

  26. Fundamental Phases • Plant to DC • Within DC • DC to Customer DC DC DC • Method & Model

  27. Fundamental Phases • Plant to DC • Within DC • DC to Customer DC • Method & Model

  28. Existing DC Costs DC Size and costs for the two new candidates, LA and Oakland??? • Method

  29. DC “Costs” DC • Given factors: • Average 11 sqft/pallet stored • Averages 1,500 lbs of product per pallet in DC inventory • Average 9 turns/yearfor the network ~40 daysof Supply • Peak Inventory levels up to 12% over the average level • Toronto is 100% utilized now • Candidate DC space costs for LA & Oakland are given • { $6.25 per square foot for fixed • { $0.095 per lb for variable cost • Method & Model

  30. Size for the new DC inventory DC

  31. Modeling warehouse capacity

  32. Warehouse capacity (fast movers) Convert in squared feet: Sf = 11/1,500 qf

  33. Warehouse capacity (s l o w m o v e r s) Convert in squared feet: Ss = 11/1,500 qs

  34. DC Design & Justification • Unknowns, affecting stacking height: • Height of packed goods • Fragility of packed goods  Stack a max of 3 high with block stacking • Unknowns, affecting configuration • Perishable items • ABC Control Breakdown • Slow vs. fast mover profile Block stacking for fast, Pallet rack for slow • Method & Model

  35. DC Facility Sizing Convention • 40% Bulk/Reserve + Fast Pick • Fast movers – block stacking; Slow movers – pallet racks • 60% Other storage support • Clearance, Aisles, Shipping/Receiving,Pallet & Vehicle Stow Slow movers Fast movers 3 3 • Method & Model S* = 246,000

  36. Toronto Extra Capacity Calculation • Toronto is currently at full capacity • Extra DC size calculated in sqft: 44,554 • DC fixed and variable costs calculated using only the extra space added to serve West CAN • Method  Options

  37. Salt Lake City New Option • Current DC size at SLC in sqft: 500,000 • New DC size calculated in sqft: 246,000 • Lease expires in 18 months • SLC new option: Rent only ½ the current space • Advantages • No new hiring, training • No new scoping required • CODB known, unchanged • Laws and regulations known • Method  Options

  38. Outcomes: Total Landed Costs • Method & Model • Outcomes

  39. Outcomes: Total Landed Costs • Outcomes

  40. Outcomes: Total Landed Costs by number of DCs • Outcomes

  41. Outcomes for Service Time Computed Demand: 84% from US customers, 16% from Canadian customers • Outcomes

  42. Outcomes for ROI • Outcomes

  43. Summary • Computed Landed Costs • Computed Service Times • Two Options: • LA  US, Toronto  Canada • SLC New  US, Toronto  Canada • “Solutions”

  44. CC CU To O SL AL NW MP LA SL Tu MC AT SP FW Mfg DC ? C • Introduction

  45. CC CU To O SL SL AL NW MP LA SL Tu MC AT SP FW Mfg DC ? C • Introduction

  46. Considerations & Recommendations • Product life cycles and turnover • Safety stock and demand variability • Load consolidation opportunities • Other transportation alternatives • Opportunities for DCs in other locations • Investigation into additional landed cost factors • External factors: workforce, unions, government, political unrest, regulations, CODB …

  47. Considerations & Recommendations • Size and orientation of racks and shelving • Storage configuration profile: Selective racks, push-backs, drive-through, block stacks, combo • Number and width and orientation of aisles • Clearance height available within the building • Fast-pick areas, Storage and retrieval systems • Special support areas, regional consideration

  48. PASI & Project Objectives • Apply concepts practically • Real-world problem • With interpretations assumptions & considerations • Collaborate across: • Cultures & Universities • Backgrounds & Perspectives • Experience & Enjoy!

  49. PASI & Project Objectives • Apply concepts practically • Real-world problem • With interpretations assumptions & considerations • Collaborate across: • Cultures & Universities • Backgrounds & Perspectives • + Experience & Enjoy! Thank You Alice, Jorge & PASI!!

  50. PASI Case 2 Data by PASIs