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Consumer Packaged Goods Manufacturing Industry

Consumer Packaged Goods Manufacturing Industry. Team: Aymaras Pan American Advanced Studies Institute Simulation and Optimization of Globalized Physical Distribution Systems Santiago, Chile August 17th 2013. Strategies for the Distribution Network Case Study #2. Outline.

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Consumer Packaged Goods Manufacturing Industry

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  1. Consumer Packaged Goods Manufacturing Industry Team: Aymaras Pan American Advanced Studies InstituteSimulation and Optimization of Globalized Physical Distribution Systems Santiago, Chile August 17th 2013. StrategiesfortheDistribution Network Case Study #2

  2. Outline Company Presentation Problem statement Issues to be addressed Scope of the Problem Assumptions and baseline results Applications of milk runs Conclusion & Recommendations

  3. St. OngeSupplyChainEngineering Top 100 SC partners SC strategy & Logistics http://www.stonge.com/default.aspx

  4. ProblemStatement

  5. Locations T M Al SLC N SL O Mfg S Tu M DC LA A M West DC Customers

  6. ProblemStatement

  7. Demandforthe Western RegionbyStates

  8. Issues To Be Addressed - Objectives • Constraints: Problemboundedfor Western distributionnetwork (unknown total demand)

  9. Scope of the Problem : The Network Plants Customers Plants DCs % Canada N T East and Central NA % SL Al ? ? % M D = ?? A % S Tu % F Western NA % SLC M % D = known M

  10. Scope of the Problem : Total Demand Calculation • Toronto : 100% utilized • SLC = known (sum all western customers) • Assumption : • Allentown, Atlanta and Tulsa 80% utilized • Formula : • Turnover = Demand/ average inventory • Average *1.12% = peak inventory = 80% DC sft • DemandDCi =

  11. Scope of the Problem : Optimization Model – Inbound Flows • Inbound flows only • No information on eastern and central customers • Minimize • Plants capacity • DC demand • Non negativity

  12. Scope of the Problem : Flows Between Plants and DCs (Inbound Flows) T Al N SLC SL S Tu M A M

  13. Scope of the Problem:Inbound + DC + Outbound SLC SL O S LA M

  14. Assumptions for the Baseline • Customers are served at least once a quarter • Square footage for Los Angeles and Oakland is assumed the same as in existing Salt Lake City DC • Holding costs are the amount of money required to keep the product in the warehouse • Capital cost, insurance, spoilage, utilities • Outsourcing Transportation • Infinite fleet of trucks: we can ship as many product as required • Once the trucks deliver the product they do not belong to us anymore: The cost of empty trucks is not consider

  15. Baseline Results • Los Angeles is the best option to locate the DC based on minimal total cost • Transportation Costs account for about 90% of the total cost • Locating the DC in Los Angeles is 8.5% cheaper than locating the DC in Salt Lake City (as it is done now) • More than half of the customers (about 60%) are visited at least twice a month

  16. Application of Milk Runs • Assumptions: • Transportation costs only include travel to deliver product (excludes empty runs) • Customers were ordered based on geography • Distances between customers were determined by mileage on Google map + 50 mile buffer (adjust for city-city & multiple customers) • Customer routes based on logical clusters based on distance • Goal: • Group low volume with high volume customers to reduce transportation

  17. Milk Run Results • Benefits: • Reduced time between deliveries for low volume customers • Reduced facility costs – only need 20 day supply • Disadvantages: • Increased transportation cost due to high variation between low and high volume customers

  18. Application of Combination of Milk Runs & Direct Runs • Assumptions: • All assumptions from milk runs still apply • For each milk run, there are only 300 deliveries/yr • Customers who have enough demand to send 300+ trucks/yr will receive direct shipments for the remaining demand (“extra” trucks) • Goals: • Group low volume with high volume customers to reduce transportation • Reduce transportation costs by allowing high volume customers to receive “extra” shipments

  19. Milk Run Examples Example 2 Example 1 SLC SLC SLC SLC

  20. Combination of Milk Runs & Direct Runs Results • Benefits: • Reduced time between deliveries for low volume customers • Reduced facility costs only need 20 day supply • Reduced transportation costs $14M/yr in Savings 19.4% Impr Consider using this approach for Toronto, Allentown, Tulsa, Atlanta

  21. Conclusions • Los Angeles selected as the single Distribution Center. • Rough sizing for selected DC based on milk runs hybrid approach (250,000 SqFt). • Inventorylevelsreducedby 50% • Inboundfreightcosts reduces from ~41M to ~33M. • Outboundfreightcosts reduces from~72M to~58M. • Impacttotransit times more frequentdeliverybasedonmilkrunsapproach • DC costsreducedby 50% • Savings of 14M a yearwill offset buildingcosts. • Los Angeles DC for serving Western Canadian demand. • Investigateexpansion Mexicali planttoserve Western demand.

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