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Consumer Packaged Goods Manufacturing Industry Team: Aymaras Pan American Advanced Studies Institute Simulation and Optimization of Globalized Physical.

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Presentation on theme: "Consumer Packaged Goods Manufacturing Industry Team: Aymaras Pan American Advanced Studies Institute Simulation and Optimization of Globalized Physical."— Presentation transcript:

1 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.

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. Onge Supply Chain Engineering Top 100 SC partners SC strategy & Logistics http://www.stonge.com/default.aspx

4 Problem Statement Operations - Regional presence - Leases expiring for Western USA DCs & Canada. -Salt Lake City serves Western demand. - Consolidated plants. Demand Retailers across Canada and USA Steady forcasted growth The Problem Optimize use of capacity of Distribution Centers to serve Western customers Reduce total supply chain costs and reduce delivery times.

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

6 Problem Statement Operations - Regional presence - Leases expiring for Western USA DCs & Canada. -Salt Lake City serves Western demand. - Consolidated plants. Demand Retailers across Canada and USA Steady forcasted growth The Problem Optimize use of capacity of Distribution Centers to serve Western customers Reduce total supply chain costs and reduce delivery times.

7 Demand for the Western Region by States

8 Issues To Be Addressed - Objectives Constraints: Problem bounded for Western distribution network (unknown total demand) Define the scope of the problem : set of options to be compared and metrics to be used Calculate and design the distribution network and its main indicators for the each options selected. Select a distribution center according to the metrics esthablished

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

10 Scope of the Problem : Total Demand Calculation

11 Scope of the Problem : Optimization Model – Inbound Flows

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

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

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 SLC Example 1 Example 2

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). Inventory levels reduced by 50% Inbound freight costs reduces from ~41M to ~33M. Outbound freight costs reduces from ~72M to ~58M. Impact to transit times more frequent delivery based on milk runs approach DC costs reduced by 50% Savings of 14M a year will offset building costs. Los Angeles DC for serving Western Canadian demand. Investigate expansion Mexicali plant to serve Western demand.


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