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Facility Location

Facility Location. Operations Management Dr. Ron Tibben-Lembke. Location Decisions. Long-term decisions Difficult to reverse Affect fixed & variable costs Transportation costs (25% of price) Other costs: taxes, wages, rent Objective: maximize benefit of location to firm.

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Facility Location

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  1. Facility Location Operations Management Dr. Ron Tibben-Lembke

  2. Location Decisions • Long-term decisions • Difficult to reverse • Affect fixed & variable costs • Transportation costs (25% of price) • Other costs: taxes, wages, rent • Objective: maximize benefit of location to firm

  3. What factors should we consider? • Skilled workforce • Environmental laws / cost of compliance • Cost of utilities, labor, taxes • Suppliers close by – fast & cheap access • Customers close by • Competitors close by? Skilled labor pool • International - control issues?

  4. Service Facilities – Traffic focus • Revenue changes a huge amount, depending on the location. • Old Navy in Stead because of cheap land? • Location, location, location: you need traffic • Make it convenient! • vitamins: need enough, but it has to be the right kind • people who would want to buy your products when they are there. • Cost probably doesn’t change nearly as much, by location • All malls have high rent

  5. Wal-Mart Toys Party Office Max WinCo

  6. A Tale of Two Stores W K

  7. “I-80 & McCarran” sounds great. • Kmart Sins: • Can’t see from anywhere • - see where we’re going • Very circuitous entry • feels inconvenient, no matter • how long it actually takes

  8. Cost Focus • Revenue does not vary much, depending on the location. • Customers don’t care if your warehouse is in Sparks or Sacramento • Location is a major cost driver • Impacts shipping, labor, production costs • Varies greatly by location

  9. Cost Minimization Identify the costs that will vary most with the location you choose. • Transportation, taxes, labor, • Facility construction cost, utilities Other considerations • Proximity of services, suppliers • Quality of life • Government incentives

  10. Cost Focus Process Overview • Identify general region to locate in • Usually based on mostly on transp. costs • Identify a list of candidate cities • Choose cities with good transp. Access • Estimate labor cost & availability, facilities costs • Select metro area, identify candidate properties. • Find cost of building or leasing individual properties

  11. Case Study:Importing from China to E. Coast

  12. Customer Location

  13. Interstate Detail

  14. China to U.S. Container Rates NY / NJ $3,600 36 days Wilmington DE $3,950 36 days (door) Norfolk $3,600 34 days Charleston $3,600 35 days Atlanta $3,200 37 days (door) New Orleans $3,200 36 days

  15. Allentown 305 575 428 DrayageRates North Elizabeth, NJ 850 Harrisburg 295 343 350 Philadelphia 305 265 375 850 Wilmington 656 825 750 Baltimore 305 375 750 780 950 1125 725 950 888 Roanoke 750 Norfolk

  16. China to Long Beach

  17. Landbridge Data Columbus $3000, 21days Cincinnati $2925, 21d Louisville $3050, 20d Murray $3350, 22d Nashville $3300, 22d Memphis $2900, 18.5d Atlanta $3300, 23d

  18. Distribution Center Location • Minimize demand-weighted distance: distance to each customer times the volume of shipments to the customer • How many to build? • Where to build?

  19. Case Study: Retailer • Location of a 5th returns processing facility • Addresses of 2125 Continental U.S. stores • Location of 4 Return Goods Processing Centers • List of all return shipments from each store, including pounds and # pallets • Calculated actual highway distances from every store to its DC

  20. Local Streets

  21. Transportation Cost Approx. • Current Pallets: 205,254 • Current Pallet Miles: 77.9m • Cost / pallet-mile 11.68 cents • Pallet-Mile = 1 pallet traveling 1 mile • Minimize average distance traveled

  22. Solution Software • Some locations must have a facility • Considers adding a facility at every existing store • We won’t really build next to a store, but that’s ok • Finds one best facility to add • Finds second best facility to add • Reconsider first added facility, then second, etc. • Improvement heuristics, optimal methods

  23. Current RCs

  24. Dallas Realignment

  25. Close 1 existing RDC

  26. Location Methods • Minimize demand-weighted distance • Center of Gravity – minimizing demand-weighted distances of one facility • Ardalan – minimize transportation of multiple facilities, but must locate by customers • (P-Median Problem, Maximum Covering) • Factor Weighting – consider qualitative factors • Break-even – Consider fixed & variable costs

  27. Center of Gravity • Compute X and Y coordinates separately • dix is the X coordinate of location i. • diy is the Y coordinate of i. • Wi is the X demand at i. • CX and CY are the coordinates of the DC.

  28. Center of Gravity Example 1 • You need to decide where to build a new DC for Motorola. • It needs to serve wholesalers in Reno, Dallas, and Chicago. • Locate these cities on an unscientific, rectangular grid. • Grid must maintain relative distances, but X and Y grids could be different.

  29. 100 80 60 40 20 0 0 20 40 60 80 100 120 140 160

  30. Center of Gravity Method City X YDemand • Reno is at 17, 55100 • Dallas is at 78, 2090 • Chicago is at 110, 65120 • Demand is TL/month

  31. Center of Gravity

  32. 100 80 60 40 20 0 0 20 40 60 80 100 120 140 160

  33. North Platte Sharon Springs Salina KS

  34. Compromise Solution • Closest town is Sharon Springs, KN • Population 872 • 30 miles from I-70. • Probably not a good choice • Salina, KN puts us at I-70 and I-35 • North Platte NE is at I-80 and 83. • Access to Dallas less convenient

  35. 100 80 60 40 20 0 0 20 40 60 80 100 120 140 160

  36. Finalizing City • Go where other warehouses are • More choice in pre-built buildings • Cheaper, easier to build a new one • More trucks to and from town, means more carriers there, means cheaper rates. • Backhaul situation • Get estimates of inbound, outbound trucking costs. • Provide lists of # loads per year to each destination, from each source

  37. Center of Gravity Example 2 • You need to decide where to locate a DC in South Dakota X Y Demand • Pierre 78 47 50 • Watertown 150 65 8 • Sioux Falls 160 25 90 • Rapid 12 42 60

  38. 100 80 60 40 20 0 0 20 40 60 80 100 120 140 160

  39. Center of Gravity

  40. 100 80 60 40 20 0 0 20 40 60 80 100 120 140 160

  41. Ardalan Heuristic • Need a matrix of distances or costs from each customer location to every other location • Demand at each location • Weight – give higher weight to more important customers – their pain of traveling a longer distance is worth more. • Only consider locating where customers are • Identify the one best place to locate at, then the second one to add, then the third, etc.

  42. Ardalan Heuristic • Minimize cost (distance) traveled From ToA B C DDem. A 0 11 8 12 10 B 11 0 10 7 8 C 8 10 0 9 20 D 9.5 7 9 0 12 The distance from A to A is shown as 0, but there is no reason we couldn’t put the actual mileage in. Carriers might charge more on popular routes, so costs may not be symmetrical. Cost to serve A from D is $12. Cost to serve D from A is $9.5.

  43. Ardalan Method • Expected demand at each location. • Step 1: Multiply distances * demand • A to B: 11 * 10 = 110

  44. Ardalan Heuristic • Multiply distances times demand, and sum ToA B C D * Dem = A B C D A 0 11 8 12 * 10 0 110 80 120 B 11 0 10 7 * 8 88 0 80 56 C 8 10 0 9 * 20 160 200 0 180 D 9.5 7 9 0 * 12 114 84 108 0 Total 362 394 268 356

  45. Ardalan Heuristic • Choose smallest total as first location A B C D A 0 110 80 120 B 88 0 80 56 C 160 200 0 180 D 114 84 108 0 Total 362 394 268 356 If we only build one facility, we should build it in C, and the total transportation costs will be 268. (This is in dollars, or truckload miles, or whatever the units in the table were.) Notice that even if we built a facility in B or D, it will continue to be cheaper to serve A from C. In the next step, we will make use of that.

  46. Ardalan Heuristic • Compare each cost in row to the cost in the chosen cost, and switch is lower A B C D A 0 80 80 80 B 80 0 80 56 C 0 0 0 0 D 108 84 108 0 Total 188 164 268 136 Why do we do that? Before, the first row said “0, 110, 80, 120.” We’ve decided to build in C If we build in A, B, or D, how much will we spend to haul to A? No matter what, we’ll spend 80. If we locate in D, we’ll serve B from D, but otherwise, we’ll serve B from C, because it’s cheaper.

  47. Ardalan Heuristic • Don’t need first chosen city any more. • Choose second cheapest city A B D A 0 80 80 B 80 0 56 C 0 0 0 D 108 84 0 Total 188 164 136 This means that if we locate #2 in D (and we already decided to locate one in C), total costs will be $136. How? A served at cost of $80 by C. B served at cost of $56 by D. C served at cost of $0 by C. D served at cost of $0 by D. This is why we needed to change the costs above.

  48. Ardalan Heuristic • Compare non-chosen cities’ costs to cost of chosen, and choose the lower cost From A B D A 0 80 80 B 56 0 56 C 0 0 0 D 0 0 0 Total 56 80 136

  49. Ardalan Heuristic • Compare non-chosen cities’ costs to cost of chosen, and choose the lower cost From A B A 0 80 B 56 0 C 0 0 D 0 0 Total 56 80 If we locate the third facility in A, we will have facilities in C, D, and A. B is the only city without a DC, and it will be served at a cost of $56. What happens if we do the method one more time?

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