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Penjelasan mengenai transportasi dan distribusi barang
- 1. 1 utdallas.edu/~metin Managing Transportation in aSupply Chain Chapter 13 Sections 4.3, 4.4 and 4.5
- 2. 2 utdallas.edu/~metin Outline Key modesof transport and major issues Transportation System Design Tradeoffs in transportation design – Transportation and service Vehicle Routing
- 3. 3 utdallas.edu/~metin Parties Involved inTransportation Carriers, owners of the vehicles; E.g. Passengers by Southwest airlines; Cargo by Cargolux airlines, only freight; Passengers and cargo by railways Care about Vehicle related costs Fixed operating costs, hubs Trip related costs Quantity related cost Overhead cost Shippers, consolidator of shipments; E.g. Postal service; Administrative assistants; Care about Transportation cost -paid to carriers Inventory cost Consolidating facility cost Processing cost Service levels, customer satisfaction Is FedEx a Carrier or a Shipper?
- 4. 4 utdallas.edu/~metin 14.3: Transportation Modes Trucks – TL: Truckload. High utilization of trucks. – LTL: Less than truckload. Fast delivery. » Suffering from high transportation costs, Lennox wants to use more TL in the future. Rail – Carload – Intermodal Air Package Carriers Water Pipeline
- 5. 5 utdallas.edu/~metin Truckload (TL) Averagerevenue per ton mile in 1996 = 9.13 cents Average haul = 274 miles Average Capacity = 17.5 to 21 tons = 42,000 - 50,000 lb. Low fixed and variable costs Major Issues – Coordination of local and interstate hauls – Utilization – Backhauls » Return trips are empty » What to send back to China from the U.S.? – Consistent service among different companies – Dynamic pricing, is the industry ready?
- 6. 6 utdallas.edu/~metin Less Than Truckload(LTL) Average revenue per ton-mile in 1996 = 25.08 cents Average haul = 646 miles compare to 274 miles of TL Higher fixed costs (terminals) and low variable costs Major Issues – Location of consolidation facilities – Utilization – Vehicle routing – Customer service
- 7. 7 utdallas.edu/~metin Rail Average revenue/ ton-mile in 1996 = 2.5 cents Average haul = 720 miles Average load = 80 tons Key Issues – Scheduling to minimize delays / improve service – Off track delays (at pick up and delivery end) – Yard operations » To build a train – on the next page – Variability of delivery times
- 8. 8 utdallas.edu/~metin Yard operations tobuild a train 3 1 1 2 2 3 1 2 3 1 2 1 3 2 1 3 3 2 2 3 3 Cities: Disassembling and assembling a train
- 9. 9 utdallas.edu/~metin Air Key Issuesfor Passenger Airlines, $250 B /year – Cost cutting, costs in 2004 are about $0.1 per customer per mile – Location/Number of hubs – Depeaking: Moving operations away from rush hours – Location of fleet bases / crew bases – Schedule optimization, Fleet assignment, Crew scheduling » Recent idea: Always keep the same crew with the same aircraft – Yield management Cargo Airlines, $40 B /year – Shape, weight, volume of the cargo – Cargo shippers, consolidators – Safety: Risk sharing between shipper and carrier. New legislation expected. Service supply chains deal heavily with airline issues
- 10. 10 utdallas.edu/~metin How far does1 Ton of Cargo go with 1 Gallon of Fuel? Source: Brian Wickett Fall 2007 SCM student
- 11. 11 utdallas.edu/~metin 14.4: Transportation SystemDesign AC Delco: Very high value, low volume parts – Three plants: Milwaukee(Wisc), Kokomo(Ind), Matamoros(Mex) – 21 assembly plants (customers for above plants) Products: ACs, batteries, hoses, brakes, belts, etc. What are the distribution options? Which one to select? On what basis?
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- 13. 13 utdallas.edu/~metin All Shipments ViaKokomo (with or without cross dock) Milwaukee Kokomo Matamoros
- 14. 14 utdallas.edu/~metin Some Shipments Direct,Others Via Kokomo Milwaukee Kokomo Matamoros
- 15. 15 utdallas.edu/~metin Milk Runs FromKokomo Milwaukee Kokomo Matamoros Milk run is loop that contains either a single supplier or a single customer.
- 16. 16 utdallas.edu/~metin Milk Runs FromPlants Milwaukee Kokomo Matamoros
- 17. 17 utdallas.edu/~metin Shipments via aCentral Warehouse Milwaukee Kokomo Matamoros
- 18. 18 utdallas.edu/~metin Shipments via CentralWarehouse Using Milk Runs Milwaukee Kokomo Matamoros
- 19. 19 utdallas.edu/~metin Cross Docking This approachis useful if deliveries are time sensitive and there are several small dropoffs in proximity, not all of which can be delivered on a single truck. Items are shifted from one truck to another without going in to storage. Timing of truck arrivals/departures is very crucial. Milwaukee Kokomo Matamoros
- 20. 20 utdallas.edu/~metin Total Costs=Transportation+Inventory Routes TransportInventory Total Direct, Full Load 2.0 17.5 19.5 Direct,Optimal Load 4.0 5.6 9.6 Via Kokomo, Full Load 2.1 9.7 11.8 Via Kokomo, Optimal Load 3.0 7.2 10.2 Direct + Kokomo 3.7 5.8 9.5 Milk run from Kokomo 2.4 7.2 9.6 Milk run from Plants 3.5 4.6 8.1
- 21. 21 utdallas.edu/~metin Section 4.3: DesignOptions for Distribution 4.3.1: Drop-Shipping or Direct Shipping to Consumer Products are shipped directly to the consumer from the manufacturer Manufacturer often uses package carriers for delivery Retailer is an information collector: – It picks consumer orders from customers and passes them to the manufacturers – It does not hold product inventory, rather it is purely for order generation (naturally or via promotions, ads) E.g.: Medical equipment salespeople can be considered as retailers. Dell, Nordstrom catalogues Retailer Manufacturers Consumers
- 22. 22 utdallas.edu/~metin Drop shipping for High-valueand low, unpredictable demand items All consumers’ needs for a particular product is satisfied from a manufacturer: All finished goods inventory for a product reside at one manufacturer. Finished goods inventory is aggregated over different consumers. – Aggregated demand often has smaller standard deviation than the sum of the standard deviations of the individual demands in the aggregation because extremes cancel out. Manufacturers postpone customization of products until an order is placed. Component and sub-assembly inventory is aggregated over different products. A wide range of products can be provided at a low cost due to postponement. – e.g. Dell uses postponement very effectively. Direct shipment simplifies retailers’ functions but complicates manufacturers’. Can manufacturer’s handle shipping units one by one to the consumers? Manufacturers and retailers must coordinate their actions using an integrated information systems. Product returns are harder to handle. Response times to consumer orders are longer with direct shipping. Direct shipping increases shipment costs.
- 23. 23 utdallas.edu/~metin How to reduceshipment costs for moderate demand? 4.3.2: In-Transit Merge The distribution network is too extensive with direct shipping and no economies of scale in transportation costs can be achieved. Consider merging shipments at Mergers. Shipments to Mergers are larger so economies of scale is achieved. Mergers increase facility costs. Mergers can be done within trucks: Cross-docking becomes useful. Response time may go up. Example: – Furniture retailers merge couches and coffee tables produced by different manufacturers – Dell merges a Dell PC with a Sony flat screen Retailer Mergers Consumers Manufacturers
- 24. 24 utdallas.edu/~metin How to reducetransportation costs/response times? 4.3.3: Distributor Storage with Carrier Delivery Keep finished goods inventory at a warehouse which ships to consumers using carriers. Shipments from manufacturers to warehouses are in TL or LTL to exploit economies of scale. Warehouses are physically closer to consumers which leads to – Shorter order fulfillment time – Shorter distance to cover with package carriers for outbound shipment. With respect to In-Transit Merge – Inventory aggregation is less because inventory is pushed to warehouses – Higher inventory costs – Facility costs are higher Easier to run. Warehouse meets the demands so infrequent orders from manufacturers to warehouses. Less information to keep track of. Only warehouses need real time demand/order status information. Example: Amazon Distributor Warehouse Manufacturers Consumers Distributor Warehouse
- 25. 25 utdallas.edu/~metin How to providemore delivery service? 4.3.4: Distributor Storage with Last Mile Delivery Very similar to Distributor Storage with Carrier Delivery except that the warehouse delivers to the consumers using Milk Runs. Transportation costs go up because warehouses are not as effective as package carriers in aggregating loads to have economies of scale. Warehouse may need to own a trucking fleet so the physical infrastructure costs are higher. Products must be flowing fast to justify the infrastructure. The cost for drivers and load handlers are high. Last mile delivery can be a sound option if labor costs are relatively small with respect to the premium consumers are willing to pay for home delivery. Response times are shorter – Warehouses are located closer to consumers – A private fleet of trucks can deliver faster than package carriers. Home delivery is high customer service; appreciated by the customers for bulky products, e.g. a washer Consumer must pay for delivery costs. – Peapod charged $9.95/delivery – Delivery costs can depend on the time of the day Example: Milk delivery, Grocery delivery Distributor Warehouse Manufacturers Consumers Distributor Warehouse
- 26. 26 utdallas.edu/~metin How to reduceeliminate consumer’s delivery cost? 4.3.5: Manufacturer or Distributor Storage with Consumer Pickup If consumers are willing to pick up the products easily, let them do so. Otherwise, they would be charged for the delivery costs. This is very similar to Last Mile Delivery except that the consumers come to pick up sites (warehouse, retailer) to get the products. Order tracking is crucial. Consumers must be alerted when their order is ready for pick up. Once a consumer arrives at the pick up site, the products must be quickly located. Significant amount of information is required to run. Example: 7dream.com of Japanese 7- Eleven – Check it out but it is in Japanese Distributor Warehouse Manufacturers Consumers Distributor Warehouse
- 27. 27 utdallas.edu/~metin How to pushproducts closer to consumers? 4.3.5: Retail Storage with Consumer Pickup Consumers can also pick up from retailers. This is the most common form of shopping. This is very similar to consumer pick up from warehouses except that now the consumers go to retailers which are closer to consumers and more conveniently located for pick ups. Inventories at warehouses are aggregated over consumers. Typically a single warehouse serves many more consumers than a single retailer would. Inventory aggregation happens at a greater extent when consumers pick up from the warehouses. No order tracking necessary. If the product is available at the retailer, the consumer buys. Otherwise goes to another retailer Example: All the retail stores. Wal-Mart, Albertson’s, Van Heusen Shirts, JCPenny Retailer Manufacturers Consumers Retailer Retailer
- 28. 28 utdallas.edu/~metin Performance: 1 isgood Information Facility & Handling Transportation Inventory Returnability Order Visibility Customer Experience Product Availability Product Variety Response Time Pickup from Warehouse Last Mile Delivery Package Carrier Delivery In-Transit Merge Drop Shipping Pickup from Retailer 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 3 4 4 4 4 4 4 4 4 4 4 4 4 4 5 5 5 5 5 5 5 6 6 5
- 29. 29 utdallas.edu/~metin There are manydistribution options but which are suitable for a given circumstance? Drop Ship In-Transit Merge Package Carrier Delivery Last Mile Delivery Pickup from Warehouse Pickup from Retailer High-demand Medium-demand Low-demand Very low-demand Many product resources High product value Quick desired response High product variety Low customer effort Red very suitable.
- 30. 30 utdallas.edu/~metin What value dodistributors add to SCs? Economies of scale in inbound transportation costs to distributors by combining shipments of several products coming from the same manufacturer. Economies of scale in outbound transportation costs from distributor to retailers by combining shipments coming from several manufacturers and going to the same retailer. Inventory aggregation at the distributor as opposed to individual retailer inventories Smoothes out orders coming from retailers and going to manufacturers. This is a side effect of combining shipments. Distributors provide a compromise strategy, for keeping inventories in the SCs, between – Storage at the manufacturer with direct shipments » Low inventory cost but high transportation cost – Storage at the retailer with customer pickups » High inventory cost but low transportation cost By specializing on distribution, distributors do a better job in logistics of shipments: – On time deliveries – Breaking bulk shipments, e.g., kitting – Shipment tracking
- 31. 31 utdallas.edu/~metin E-Business and theDistribution Network Impact of E-Business on Customer Service – Faster » Response to customer orders » New product introductions » Modifications of Product portfolios, pricing, promotions » Revenue collection – Product variety » Number of products – Product availability » Number of products in the storage Improved Information and Aggregation Potential – Customer experience » Ease (+); After-hours-shopping (+); Distant-shopping (+); » Order visibility (-) for the customer. – Profit can increase with the removal of the distributors
- 32. 32 utdallas.edu/~metin E-Business and theDistribution Network Impact of E-Business on Cost – Inventory » Improved Information and Aggregation Potential – Facilities » Facility costs » Operating costs Simplification of order taking Increased handling of products – Transportation » Aggregation increases the outbound transportation costs – Information » Increased demand visibility » Increased supplier visibility Using E-Business: Dell, Amazon, Peapod, Grainger
- 33. 33 utdallas.edu/~metin 13.5: Tradeoffs inTransportation Design Transportation, facility, and inventory cost tradeoff – Choice of transportation mode (later) – Inventory aggregation (later) Transportation cost and responsiveness tradeoff – Temporal aggregation leads to economies of scale – Temporal aggregation decreases responsiveness
- 34. 34 utdallas.edu/~metin Temporal aggregation: Extremescancel out Day 1 Load: Day 2 Load: 2 trucks at the end of each day (one truck half-full) or 3 trucks at the end of the 2. day (both trucks full)?
- 35. 35 utdallas.edu/~metin 13.6: Tailored Transportation By product characteristics: life cycle, spoilage. By customer density and distance – High density, short distance: private fleet, milk runs » Milkman, 7-Eleven Japan – Low density, high distance: package carrier » Amazon By customer size – Various frequencies of deliveries – Delivery on Even days to Retailers L and H , on Odd days to Retailer H By value and volume – If High value, use fast transportation; semiconductor chips – If High volume, can afford to disaggregate inventories that is use several warehouses; Wal-Mart DCs – If High cube (very heavy), ?
- 36. 36 utdallas.edu/~metin Routing and Schedulingin Transportation Use frequency decomposition Clustering – Assignment of trucks to demand points (retailers) Routing – Sequencing demand points – Trucks use these sequences to visit demand points Scheduling – Exact time of visits/loading and unloading
- 37. 37 utdallas.edu/~metin Classification: Vehicle RoutingProblems Demand uncertainty – Repair operations, spare parts demand for Xerox machines The nature of operations: pick up / load Planning periods: Single vs. Multiple – In multiple periods, initial configuration of where trucks are every period can be different. Static vs. Dynamic, to the extent real time info used – Wireless technologies can help – After all what are RFID (Radio Frequency ID) tags for? Fleet capacity, known? Strategic vs Operational. Delivery time windows. – I want » my paper in the morning » my pizza in the night Objective: transportation costs, inventory costs, crew costs
- 38. 38 utdallas.edu/~metin Two-phase VRP heuristics Clustering – Saving matrix method – Generalized assignment method Sequencing – Route sequencing – Route improvement More detailed discussion is in – OPRE 6370: Logistics and Distribution offered every Fall semester.
- 39. 39 utdallas.edu/~metin Summary of LearningObjectives Strengths and weaknesses of transport modes Choices of transportation networks Tradeoffs in transportation network design Tailored transportation networks Heuristics for Clustering and Sequencing
- 40. 40 utdallas.edu/~metin Appendix Some detailsabout clustering and routing are included here. There is more discussion on these in the 1st and 2nd edition of the Chopra and Meindl textbook.
- 41. 41 utdallas.edu/~metin Clustering: Saving matrixmethod Distances are Euclidean or Rectilinear Savings of consolidating two customers X and Y: – Eliminating going from X to DC and – Eliminating going from DC to Y – But adding going from X to Y S(X,Y)=Dist(DC,X)+Dist(DC,Y)-Dist(X,Y) S(X,Y) < 0 , when is this possible if ever? DC X Y
- 42. 42 utdallas.edu/~metin X-Coordinate Y-Coordinate Demand Warehouse0 0 Customer 1 0 12 48 Customer 2 6 5 36 Customer 3 7 15 43 Customer 4 9 12 92 Customer 5 15 3 57 Customer 6 20 0 16 Customer 7 17 -2 56 Customer 8 7 -4 30 Customer 9 1 -6 57 Customer 10 15 -6 47 Customer 11 20 -7 91 Customer 12 7 -9 55 Customer 13 2 -15 36 Clustering Example
- 43. 43 utdallas.edu/~metin Whse Cust 1 Cust 2 Cust 3 Cust 4 Cust 5 Cust 6 Cust 7 Cust 8 Cust 9 Cust 10 Cust 11 Cust 12 Cust 13 Whse 0 Cust1 12 0 Cust 2 8 9 0 Cust 3 17 8 10 0 Cust 4 15 9 8 4 0 Cust 5 15 17 9 14 11 0 Cust 6 20 23 15 20 16 6 0 Cust 7 17 22 13 20 16 5 4 0 Cust 8 8 17 9 19 16 11 14 10 0 Cust 9 6 18 12 22 20 17 20 16 6 0 Cust 10 16 23 14 22 19 9 8 4 8 14 0 Cust 11 21 28 18 26 22 11 7 6 13 19 5 0 Cust 12 11 22 14 24 21 14 16 12 5 7 9 13 0 Cust 13 18 28 19 28 25 15 13 10 11 14 6 8 8 0 Clustering: Distance Matrix S(6,11)=Dist(W,6)+Dist(W,11)-Dist(6,11)=20+21-7=34
- 44. 44 utdallas.edu/~metin Truck Cust 1 Cust 2 Cust 3 Cust 4 Cust 5 Cust 6 Cust 7 Cust 8 Cust 9 Cust 10 Cust 11 Cust 12 Cust 13 Cust 11 0 Cust 2 2 11 0 Cust 3 3 21 15 0 Cust 4 4 18 15 28 0 Cust 5 5 10 14 18 19 0 Cust 6 6 9 13 17 19 29 0 Cust 7 7 7 12 14 16 27 33 0 Cust 8 8 3 7 6 7 12 14 15 0 Cust 9 9 0 2 1 1 4 6 7 8 0 Cust 10 10 5 10 11 12 22 28 29 16 8 0 Cust 11 11 5 11 12 14 25 34 32 16 8 32 0 Cust 12 12 1 5 4 8 12 15 16 14 10 18 19 0 Cust 13 13 2 7 7 8 18 25 25 15 10 28 31 21 0 Clustering Largest saving 34, combine 6 and 11: consumed capacity 107. Largest saving 33, combine 7: consumed capacity 163. Largest saving 32, combine 7: Not possible. Already in the route. Largest saving 32, combine 10: Not possible. Lack of capacity.
- 45. 45 utdallas.edu/~metin Clustering with savingsmatrix Attempt to combine different routes with the highest available saving – If load is over capacity, reject the combination – Else accept the combination and make savings unavailable Truck routes: {1,3,4}, {2,9}, {6,7,8,11} (=fills truck by 193/200) and {5,10,12,13}
- 46. 46 utdallas.edu/~metin Clustering: Generalized AssignmentMethod Skip to page Traveling Salesman Problem Assign seed points for each route – Seeds: Center of retailers in the route » Seeds do not exist, we imagine them to compute costs – Sweep clockwise by to obtain cones to assign seeds – Seed is at (dmax, /2) where dmax is the distance from origin to the furthest demand point in the cone Evaluate insertion cost for each customer i and seed k – cik=Dist(DC,i)+Dist(i,Sk)-Dist(DC,Sk) where DC is a seed. Assign customers to routes with an Integer Program
- 47. 47 utdallas.edu/~metin How Much toSweep For every cone sweep as much as possible before going over the transportation (truck) capacity bk What if for same demand point i: – If i is not included, below capacity and if i is included above capacity » Use the ArcTan method of the book » Decide ad hoc, remember you are not making the final call here. The final assignments and cluster construction is by the Integer Program.
- 48. 48 utdallas.edu/~metin Assign Customers toRoutes Using either savings matrix or generalized assignment we obtain the clustering. Min c y ST y a y b ik ik i n k K ik k K i ik i n k 1 1 1 1 1 0 1 : , For all customer i 's For all truck k 's yik
- 49. 49 utdallas.edu/~metin Traveling Salesman Problem Routingby Construction Traveling Salesman Problem, construction heuristics: – Farthest insert: Given a trip and customers to be inserted, obtain the best way to insert each customer. Insert the customer giving the longest trip. – Nearest insert: Exactly the same as farthest insert, except that the customer giving the shortest trip is inserted. – Nearest neighbor: Insert the nearest neighbor. – Sweep: Insert in the order of a sweep. Sweep needs a picture
- 50. 50 utdallas.edu/~metin Routing by Improvement Traveling Salesman problem, route improvement – 2-Opt, cuts into two paths, how many ways to join? – 3-Opt, cuts into three paths, how many ways to join? – Both needs a route to begin with. They cut and paste pieces of routes to improve the total length of the tour.
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- #17 Notes: This is effective if there are several delivery sites in proximity that cannot all be delivered on one truck from the plant in time. For example if the assembly plants want just in time delivery, line hauling and dcross docking may be an effective way to achieve that.
- #18 Notes: This is effective if there are several delivery sites in proximity that cannot all be delivered on one truck from the plant in time. For example if the assembly plants want just in time delivery, line hauling and dcross docking may be an effective way to achieve that.
- #19 Notes: This is effective if there are several delivery sites in proximity that cannot all be delivered on one truck from the plant in time. For example if the assembly plants want just in time delivery, line hauling and dcross docking may be an effective way to achieve that.
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