The University of Southern Mississippi College of Science & Technology IET 670 Section: G001 Supply Chain Design & Management Midterm Exam Full Points: 100 Student ID: Name: Closed book closed notes Answer all questions Instructions: Submit a word or pdf file with answers only (do not type questions) Multiple Choice Questions: Select the best choice/s - 50 points 1. Boeing Aircraft's inventory write-down of $2.6 billion was partly due to a. Stiff competition b. Introduction of new plane by Airbus c. Shortage of raw materials and supplier parts d. Larger than anticipated inventories e. Slowdown of Boeing 7XX model in the market 2. Which is not a factor of increasing uncertainty and risk in supply chain? a. Lean implementation b. Real-time information sharing c. Outsourcing parts from different company d. Off-shoring labor intensive products e. None of the above 3. The second highest contributing factor in supply chain cost is a. Transportation cost b. Inventory cost c. Handling cost d. Quality cost e. Management cost 4. Which is not a key issue in Global optimization of supply chain? a. Supply contracts b. Distribution strategies c. Inventory control d. Strategic partnering e. Outsourcing 5. For an automobile parts warehouse, what will be the safety stock of a part that has an average demand of 500 unit per week with = 125? The review period is 0.5 week, lead time is 0.5 week, and z = 1.92. a. 365 b. 625 c. 125 d. 240 e. None of the above 6. What would be the expected inventory level for the above problem? a. 365 b. 625 c. 125 d. 240 e. Cannot be calculated 7. Inventory is generally bad but required for all of the following except a. Uncertainty in customer demand b. Uncertainty in supply c. Delivery lead time d. Discounts for larger shipments e. Reducing inventory carrying cost 8. What is the best true statement for total cost? a. It stays at the lowest where holding cost and order cost line intersects b. It goes up with increase in holding cost c. It goes down with increase in holding cost Pull d. It goes up with increase in order cost e. It goes down with increase in holding cost 9. If marginal profit is higher than marginal cost of a product that has an average demand of 1000 units, what should be the optimum order quantity for this product? a. Insufficient data for calculating the value b. 0-999 units c. 1000 units d. 1001 units or more e. None of the above 10. If you have to choose between producing 9,000 units and 16,000 units, which one should you choose? Provided the average demand is 12,000 units, marginal cost is $50, and marginal profit is $51. a. 9,000 b. c. d. e. 12,000 16,000 Any one of those choices Can't be determined due to lack of data 11. One of the purpose of inventory positioning is to a. Determine the capacity of manufacturing plants b. Assign retail outlets to warehouses c. Design delivery schedules d. Determine the optimum order quantity for suppliers e. Select facilities that will produce to stock an keep inventory 12. What is not a reason to reevaluate the infrastructure design? a. Change in demand pattern b. Change in management c. Change in production process d. Change in cost of running facilities e. Change in sourcing strategies 13. Data aggregation is done to improve all but a. Forecasts at aggregate level b. Calculation process c. Simplicity in representation d. All of the above e. None of the above 14. What is SMC3 CzarLite? a. A tool for determining bullwhip effect b. Demand forecasting tool c. A fair TLT pricing system based on zip codes d. Bear Game software e. All of the above 15. The annual demand of a product is 12,000 units that are stored in a warehouse whose inventory turnover is 6.7, what is the average inventory level at that warehouse? a. 0 unit b. 500 unit c. 1000 unit d. 1791 unit e. 2000 unit 16. What is the space requirement of the warehouse in the above problem? If one unit requires 1 square foot (sft) of space. a. 12000 sft b. 1000 sft c. 5373 sft d. 1791 sft e. 7290 sft 17. What happens if supplier share risks with the buyer? a. It reduces profit for buyer b. It reduces profit for supplier c. It reduces out of stock probability d. It reduces inventory for buyers e. None of the above 18. Reverse logistics is very important for a. Revenue sharing contract b. Sales rebate contract c. Buy back contract d. Cost sharing contract e. Short-term contract 19. Southwest Airlines was able to buy jet fuel up to a certain amount from Shell at a price of $1.5 per gallons until 2009 while the market price for jet fuel was $3 per gallon at that time. What type of contact did Southwest made with Shell? a. Fixed commitment contract b. Option contract c. Spot purchase contract d. Portfolio contract e. None of the above 20. Which of the following situation is the best for spot purchase? a. Market demand is lower than fixed commitment contract made with supplier b. There exists a very high demand of products in the open market c. The open market do not have any products to sell d. Market demand is equal to fixed and option contacts made with suppliers e. Market demand is higher than total contracts made and low product price at the open market 21. Longer lead time in customer order fulfillment has an immediate negative impact on a. Inventory level b. Transportation cost c. Service level d. Warehouse location e. Profit margin 22. Forward buying is amplified by a. Lower price of products than usual b. c. d. e. Promotions offered from manufacturer Volume discounts from whole sellers All of the above None of the above 23. VMI is an example of a. Strategic partnership b. RFID use c. Bullwhip effect d. Variability reduction e. Risk sharing 24. If cost of overage is $1 and cost of underage is $2, what is the probability of not stocking out? a. 50% b. 100% c. 0% d. 67% e. Can't be calculated 25. L6 manufacturing in Dell Computer case better than L5 because of all of the following except a. L6 does not need air shipping cost for mother board b. L5 increases supply chain flexibility c. L6 reduces mother board packing cost d. L5 incurs 3rd party integration cost e. L6 saves labor cost Descriptive Questions: 10 points 1. Why Dell Computer was outperforming other competitors? 2. Explain the relationship between customer service level and inventory level. 3. Explain the way of setting the push pull boundary. Mathematical Questions: 40 points 1. Toshiba's actual demand of its Laptop model X over the last 10 period is given below. Calculate the optimal order quantity for its laptop and average inventory level per period. - 10 points Period Demand 1 225 2 120 3 200 4 235 5 175 6 250 7 195 Following information is given; Fixed ordering cost = $200 Cost of a laptop X to the distributor = $700 Inventory holding cost per period = 1.5% of product cost Replenishment lead time = 0.25 periods Expected service level = 95% (corresponding z value is 1.65) 8 210 9 150 10 185 2. Chiquita LLC delivers its concentrated pineapple juice to Dallas and Chicago through three warehouses located in Gulfport, Memphis and Baton Rouge. Pineapple juice is produced in Honduras and Columbia plants with a capacity of 100,000 boxes in each plant at the same production cost. The shipment costs are given in the following table. Dallas has a market demand of 75,000 juice boxes and Chicago has a market demand of 60, 000 juice boxes. Calculate the total shipment costs using the heuristics of cheapest warehouse to source demand. - 10 points Warehouses Biloxi Baton Rouge Memphis Honduras Plant $1 $1.5 $2 Columbia Plant $1.25 $1.75 $2.25 Dallas Market $3 $2.25 $2 Chicago Market $3 $2 $1 3. Solve the same problem # 2 on page 139 of your text with the following data set - all other data remain same. (you solved this problem in your first assignment) - 20 points Demand 5000 6000 7000 8000 9000 10000 Probability 9% 12% 20% 40% 11% 8% IET 670 Supply Chain Design & Management Lecture 1 Chapter 1:Introduction to Supply Chain Management Dr. MD Sarder Copyright 2008 by The McGraw-Hill Companies, Inc. All rights reserved. What Is a Supply Chain? Flow of products and services from: Raw materials manufacturers Intermediate products manufacturers End product manufacturers Wholesalers and distributors and Retailers Connected by transportation and storage activities Integrated through information, planning, and integration activities Cost and service levels 1-2 1.1 What Is Supply Chain Management? Supply chain management is a set of approaches utilized to efficiently integrate suppliers, manufacturers, warehouses, and stores, so that merchandise is produced and distributed at the right quantities, to the right locations, and at the right time, in order to minimize system wide costs while satisfying service level requirements. 1-3 Two Other Formal Definitions The design and management of seamless, valueadded process across organizational boundaries to meet the real needs of the end customer Institute for Supply Management Managing supply and demand, sourcing raw materials and parts, manufacturing and assembly, warehousing and inventory tracking, order entry and order management, distribution across all channels, and delivery to the customer The Supply Chain Council 1-4 PC Industry Supply Chain Tracing back the screen you stare at for the bulk of your time. 1-5 Cisco's Value Network 1-6 SCM Definition Material Flow Supplier Converter Distributor Retailer Source Converter Supplier Distributor Consumers End-User Value-Added Services Funds/Demand Flow Information Flow Reuse/Maintenance/After Sales Service Flow 1-7 The SCM Network FIGURE 1.1: The logistics network 1-8 Key Observations Every facility that impacts costs need to be considered Efficiency and cost-effectiveness throughout the system is required Suppliers' suppliers Customers' customers System level approach Multiple levels of activities Strategic - Tactical - Operational 1-9 Other Related Observations Supply chain strategy linked to the Development Chain Challenging to minimize system costs and maximize system service levels Inherent presence of uncertainty and risk 1-10 1.2 The Development Chain Set of activities and processes associated with new product introduction. Includes: product design phase associated capabilities and knowledge sourcing decisions production plans 1-11 1.2 The Development Chain FIGURE 1-2: The enterprise development and supply chain 1-12 1.3 Global Optimization Geographically dispersed complex network Conflicting objectives of different facilities Dynamic system Variations over time Matching demand-supply difficult Different levels of inventory and backorders Recent developments have increased risks Lean production/Off-shoring/Outsourcing 1-13 Global Apparel Value Chain Tracing back the dress you are wearing 1-14 1-15 Globally Dispersed Manufacturing An Illustration: How Li & Fung Limited Might Make a Dress Product Design [Hong Kong] Yarn Spinning [Korea] QC & Shipping [Hong Kong] Weaving [Taiwan] Stitching [Indonesia] Zippers+... [Japan+...] 1-16 1.4 Uncertainty and Risk Factors Matching Supply and Demand a Major Challenge REASONS EXAMPLES Raw material shortages Internal and supplier parts Boeing Aircraft's inventory writedown of $2.6 billion shortages Productivity inefficiencies Sales and earnings shortfall Larger than anticipated inventories Stiff competition General slowdown in the PC Sales at U.S. Surgical Corporation declined 25 percent, resulting in a loss of $22 million Intel reported a 38 percent decline in quarterly profit market Higher than expected orders for new products over existing products EMC Corp. missed its revenue guidance of $2.66 billion for the second quarter of 2006 by around $100 million 1-17 1.4 Uncertainty and Risk Factors Fluctuations of Inventory and Backorders throughout the Supply Chain FIGURE 1-3: Order variations in the supply chain 1-18 1.4 Uncertainty and Risk Factors Forecasting is not a solution Demand is not the only source of uncertainty Recent trends make things more uncertain Lean manufacturing Outsourcing Off-shoring 1-19 1.4 Uncertainty and Risk Factors August 2005 - Hurricane Katrina 2002 West Coast port strike Losses of $1B/day Store stock-outs, factory shutdowns 1999 Taiwan earthquake P&G coffee supplies from sites around New Orleans Six month impact Supply interruptions of HP, Dell 2001 India (Gujarat state) earthquake Supply interruptions for apparel manufacturers 1-20 1.5 Evolution of Supply Chain Management Further Refinement of SCM Capabilities SCM Formation/ Extensions JIT, TQM, BPR, Alliances Inventory Management/Cost Optimization Traditional Mass Manufacturing 1950s 1960s 1970s 1980s 1990s 2000s Beyond 1-21 Progression of Logistics Costs FIGURE 1-4: Logistics costs' share of the U.S. economy 1-22 Composition of Logistics Costs FIGURE 1-5: Total U.S. logistics costs between 1984 and 2005 1-23 1.6 Complexity: The Magnitude U.S. companies spend more than $1 trillion in supplyrelated activities (10-15% of Gross Domestic Product) Transportation 58% Inventory 38% Management 4% The grocery industry could save $30 billion (10% of operating cost) by using effective logistics strategies A typical box of cereal spends 104 days getting from factory to supermarket. A typical new car spends 15 days traveling from the factory to the dealership. 1-24 Complexity: The Magnitude Compaq computer's loss of $500 million to $1 billion in sales in one year Boeing's forced announcement of write-downs of $2.6b Laptops and desktops were not available when and where customers were ready to buy them Raw material shortages, internal and supplier parts shortages.... Cisco's multi-billion ($2.2b) dollar write-off of inventories in 2001-2002 Customers balked on orders due to market meltdown 1-25 Transactional Complexity National Semiconductors: Production: - Produces chips in six different locations: four in the US, one in Britain and one in Israel - Chips are shipped to seven assembly locations in Southeast Asia. Distribution - The final product is shipped to hundreds of facilities all over the world - 20,000 different routes - 12 different airlines are involved - 95% of the products are delivered within 45 days - 5% are delivered within 90 days. 1-26 PC Value Chain Performance of Traditional PC Manufacturer 1-27 PC Value Chain: Focus on Cost Reduction Performance of Dell Computers 1-28 Magnitude of Supply Chain Costs Cost Elements of a Typical Trade Book 1-29 Magnitude of Supply Chain Costs Example: The Apparel Industry Cost per Percent Shirt Saving Manufacturer Distributor Retailer Customer $52.72 0% Manufacturer Distributor Retailer Customer $41.34 28% Manufacturer Distributor Retailer Customer $20.45 62% 1-30 Supply Chain: The Potential P&G's estimated savings to retail customers of $65 million through logistics gains Dell Computer's outperforming of the competition in terms of shareholder value growth over more than two decades by over 3,000% using: Direct business model Build-to-order strategy Wal-Mart transformation into the world's largest retailer by changing its logistics system: highest sales per square foot, inventory turnover and operating profit of any discount retailer 1-31 1.7 Key Issues in Supply Chain Management Chain Distribution Network Configuration Inventory Control Production Sourcing Supply Contracts Distribution Strategies Strategic Partnering Outsourcing and Offshoring Product Design Information Technology Customer Value Smart Pricing Supply Supply Supply Both Supply Development Development Development Supply Both Supply Global Optimization Managing Risk and Uncertainty Y Y Y Y Y Y Y Y Y Y Y Y Y Y Y TABLE 1-1: Key supply chain management issues 1-32 1.8 Book Objectives and Overview Inventory management Logistics network planning Supply contracts for strategic as well as commodity components. The value of information and the effective use of information in the supply chain. Supply chain integration. Centralized and decentralized distribution strategies. Strategic alliances. Outsourcing, off-shoring, and procurement strategies. International supply chain management. Supply chain management and product design. Customer value. Revenue management and pricing strategies. Information technology and business processes. Technical standards and their impact on the supply chain. 1-33 Software Packages Computerized Beer Game Risk Pool Game Procurement Game 1-34 CASE: Meditech Surgical Intent - diagnosis of supply chain Business overview Supply chain Production planning What's wrong? How to fix it? 1-35 Endoscopic Surgical Instruments Permits minimally invasive surgery Market created in early 80's, rapidly growing Old products continually updated and replaced with new product introductions 1-36 Business Overview National and Meditech split the market Compete based on product innovations, customer service, cost National sells to physicians; Meditech sells to material managers Customer preferences change slowly 1-37 External Supply Chain Hospitals Domestic Dealers Part suppliers Meditech Assembly Meditech Warehouse Hospitals Int'l Meditech Affiliates 1-38 Internal Supply Chain Parts Inventory 2 - 16 weeks Assembly 2 weeks Bulk Inventory Packaging & Sterilization FG Inventory 1 week 1-39 Production Planning Annual Forecast Monthly Revision Transfer Requirements Monthly Plan MRP Parts Procurement Plan Weekly Assembly Schedule 1-40 Production Planning Monthly Plan MRP Order point; Order quantity Material Plan Parts Inventory Assembly Bulk Inventory Packaging & Sterilization FG inventory 1-41 What's Wrong? Poor service for new product introductions Poor forecasting? Panic ordering? And high FG inventory 1-42 What Is Going On? Demand is quite predictable Usage in hospitals is quite stable Market share moves slowly over time With each new product, dealer must build inventory to fill pipeline 1-43 Why Did Meditech Think Demand Was Unpredictable? Poor information systems No one looked at demand No one had responsibility for forecast errors Tendency to shift the blame Built-in delays and monthly buckets in planning system Amplifier in planning system 1-44 What to Do? Recognize that demand is stable and predictable Establish accountability for forecast Eliminate planning delays and/or reduce time bucket Alternatively, put assembly within pull system and eliminate bulk inventory 1-45 IET 670 Supply Chain Design & Management Lecture 2 Chapter 2:Inventory Management and Risk Pooling Dr. MD Sarder Copyright 2008 by The McGraw-Hill Companies, Inc. All rights reserved. CASE: Steel Works Background of case and intent Overview of business What does data tell you about Specialty? How much inventory might you expect? What opportunities are there for Custom? Wrap up Stephen C. Graves Copyright 2003 All Rights Reserved 2-2 Background & Intent Abstraction from summer consulting job Intent is to examine a realistic, but simplified inventory context and perform a diagnosis of problem - poor service and too much inventory Stephen C. Graves Copyright 2003 All Rights Reserved 2-3 Custom Products Rapid growth, 1/3 of total sales ($133 MM) One customer per product Very high margins High service level 3 plants, co-located with R&D center Each product produced at a single plant Stephen C. Graves Copyright 2003 All Rights Reserved 2-4 Specialty Products Rapid growth, 2/3 of total sales ($267 MM) 6 product families 3 plants, each producing 2 product families 130 customers, 120 products Few big customers Highly volatile demand High service level Stephen C. Graves Copyright 2003 All Rights Reserved 2-5 Consultant Recommendation Drop low volume products Improve forecasts Consolidate warehouses Stephen C. Graves Copyright 2003 All Rights Reserved 2-6 What Does Data Tell You? cv DB R10 15.5 13.2 0.85 DB R12 1008 256 0.25 DB R15 2464 494 0.20 DF R10 97 92.5 0.95 DF R12 18.5 11.4 0.62 DF R15 55 80 1.46 DF R23 35.5 45.9 1.29 Stephen C. Graves Copyright 2003 All Rights Reserved 2-7 What Does Data Tell You? Durabend R12: One customer accounts for 97% of demand 7 products: High volume (2) is not very volatile Low volume (5) is very volatile Stephen C. Graves Copyright 2003 All Rights Reserved 2-8 How Much Inventory Should You Expect? Assume base stock model with periodic review Review period = r = ? Lead time = L = ? E I r 2 z r L Stephen C. Graves Copyright 2003 All Rights Reserved 2-9 Cycle stock Saf. stock E[I] Act. Inv. DB R10 15.5 13.2 8 26 34 72 DB R12 1008 256 504 510 1014 740 DB R15 2464 494 1232 990 2222 1875 DF R10 97 92.5 49 185 234 604 DF R12 18.5 11.4 9 23 32 55 DF R15 55 80 28 160 188 388 DF R23 35.5 45.9 18 92 110 190 1848 1986 3834 3824 S Assumes r = 1; L=0.25; and z = 1.8 Cycle stock = r /2 Safety stock = z r+L Stephen C. Graves Copyright 2003 All Rights Reserved 2-10 What Are the Opportunities at Custom? Combine production and inventory for common items, e. g. DF R23 Produce monthly: reduce setups by half and pool safety stocks Produce twice a month: same number of setups but cut cycle stock and review period in half Stephen C. Graves Copyright 2003 All Rights Reserved 2-11 Wrap Up Realistic diagnostic exercise In real life: not as clean, more data and more considerations Yet simple models and principles can provide valuable guidance Stephen C. Graves Copyright 2003 All Rights Reserved 2-12 2.1 Introduction Why Is Inventory Important? Distribution and inventory (logistics) costs are quite substantial Total U.S. Manufacturing Inventories ($m): 1992-01-31: $m 808,773 1996-08-31: $m 1,000,774 2006-05-31: $m 1,324,108 Inventory-Sales Ratio (U.S. Manufacturers): 1992-01-01: 1.56 2006-05-01: 1.25 2-13 Why Is Inventory Important? GM's production and distribution network Freight transportation costs: $4.1 billion (60% for material shipments) GM inventory valued at $7.4 billion (70%WIP; Rest Finished Vehicles) Decision tool to reduce: 20,000 supplier plants 133 parts plants 31 assembly plants 11,000 dealers combined corporate cost of inventory and transportation. 26% annual cost reduction by adjusting: Shipment sizes (inventory policy) Routes (transportation strategy) 2-14 Why Is Inventory Required? Uncertainty in customer demand Shorter product lifecycles More competing products Uncertainty in supplies Quality/Quantity/Costs/Delivery Times Delivery lead times Incentives for larger shipments 2-15 Holding the right amount at the right time is difficult! Dell Computer's was sharply off in its forecast of demand, resulting in inventory write-downs Liz Claiborne's higher-than-anticipated excess inventories 1993 unexpected earnings decline, IBM's ineffective inventory management 1993 stock plunge 1994 shortages in the ThinkPad line Cisco's declining sales 2001 $ 2.25B excess inventory charge 2-16 Inventory Management-Demand Forecasts Uncertain demand makes demand forecast critical for inventory related decisions: What to order? When to order? How much is the optimal order quantity? Approach includes a set of techniques INVENTORY POLICY!! 2-17 Supply Chain Factors in Inventory Policy Estimation of customer demand Replenishment lead time The number of different products being considered The length of the planning horizon Costs Order cost: Inventory holding cost, or inventory carrying cost: Product cost Transportation cost State taxes, property taxes, and insurance on inventories Maintenance costs Obsolescence cost Opportunity costs Service level requirements 2-18 2.2 Single Stage Inventory Control Single supply chain stage Variety of techniques Economic Lot Size Model Demand Uncertainty Single Period Models Initial Inventory Multiple Order Opportunities Continuous Review Policy Variable Lead Times Periodic Review Policy Service Level Optimization 2-19 2.2.1. Economic Lot Size Model FIGURE 2-3: Inventory level as a function of time 2-20 Assumptions D items per day: Constant demand rate Q items per order: Order quantities are fixed, i.e., each time the warehouse places an order, it is for Q items. K, fixed setup cost, incurred every time the warehouse places an order. h, inventory carrying cost accrued per unit held in inventory per day that the unit is held (also known as, holding cost) Lead time = 0 (the time that elapses between the placement of an order and its receipt) Initial inventory = 0 Planning horizon is long (infinite). 2-21 Deriving EOQ Total cost at every cycle: K hTQ 2 Average inventory holding cost in a cycle: Q/2 Cycle time T =Q/D KD hQ Average total cost per unit time: Q 2 Q * 2 KD h 2-22 EOQ: Costs FIGURE 2-4: Economic lot size model: total cost per unit time 2-23 Sensitivity Analysis Total inventory cost relatively insensitive to order quantities Actual order quantity: Q Q is a multiple b of the optimal order quantity Q*. For a given b, the quantity ordered is Q = bQ* b .5 .8 .9 1 1.1 1.2 1.5 2 Increase in cost 25% 2.5% 0.5% 0 .4% 1.6% 8.9% 25% 2-24 2.2.2. Demand Uncertainty The forecast is always wrong The longer the forecast horizon, the worse the forecast It is difficult to match supply and demand It is even more difficult if one needs to predict customer demand for a long period of time Aggregate forecasts are more accurate. More difficult to predict customer demand for individual SKUs Much easier to predict demand across all SKUs within one product family 2-25 2.2.3. Single Period Models Short lifecycle products One ordering opportunity only Order quantity to be decided before demand occurs Order Quantity > Demand => Dispose excess inventory Order Quantity < Demand => Lose sales/profits 2-26 Single Period Models Using historical data identify a variety of demand scenarios determine probability each of these scenarios will occur Given a specific inventory policy determine the profit associated with a particular scenario given a specific order quantity weight each scenario's profit by the likelihood that it will occur determine the average, or expected, profit for a particular ordering quantity. Order the quantity that maximizes the average profit. 2-27 Single Period Model Example FIGURE 2-5: Probabilistic forecast 2-28 Additional Information Fixed production cost: $100,000 Variable production cost per unit: $80. During the summer season, selling price: $125 per unit. Salvage value: Any swimsuit not sold during the summer season is sold to a discount store for $20. 2-29 Two Scenarios Manufacturer produces 10,000 units while demand ends at 12,000 swimsuits Profit = 125(10,000) - 80(10,000) - 100,000 = $350,000 Manufacturer produces 10,000 units while demand ends at 8,000 swimsuits Profit = 125(8,000) + 20(2,000) - 80(10,000) - 100,000 = $140,000 2-30 Probability of Profitability Scenarios with Production = 10,000 Units Probability of demand being 8000 units = 11% Probability of demand being 12000 units = 27% Probability of profit of $140,000 = 11% Probability of profit of $140,000 = 27% Total profit = Weighted average of profit scenarios 2-31 Order Quantity that Maximizes Expected Profit FIGURE 2-6: Average profit as a function of production quantity 2-32 Relationship Between Optimal Quantity and Average Demand Compare marginal profit of selling an additional unit and marginal cost of not selling an additional unit Marginal profit/unit = Selling Price - Variable Ordering (or, Production) Cost Marginal cost/unit = Variable Ordering (or, Production) Cost - Salvage Value If Marginal Profit > Marginal Cost => Optimal Quantity > Average Demand If Marginal Profit < Marginal Cost => Optimal Quantity < Average Demand 2-33 For the Swimsuit Example Average demand = 13,000 units. Optimal production quantity = 12,000 units. Marginal profit = $45 Marginal cost = $60. Thus, Marginal Cost > Marginal Profit => optimal production quantity < average demand. 2-34 Risk-Reward Tradeoffs Optimal production quantity maximizes average profit is about 12,000 Producing 9,000 units or producing 16,000 units will lead to about the same average profit of $294,000. If we had to choose between producing 9,000 units and 16,000 units, which one should we choose? 2-35 Risk-Reward Tradeoffs FIGURE 2-7: A frequency histogram of profit 2-36 Risk-Reward Tradeoffs Production Quantity = 9000 units Profit is: Production quantity = 16,000 units. either $200,000 with probability of about 11 % or $305,000 with probability of about 89 % Distribution of profit is not symmetrical. Losses of $220,000 about 11% of the time Profits of at least $410,000 about 50% of the time With the same average profit, increasing the production quantity: Increases the possible risk Increases the possible reward 2-37 Observations The optimal order quantity is not necessarily equal to forecast, or average, demand. As the order quantity increases, average profit typically increases until the production quantity reaches a certain value, after which the average profit starts decreasing. Risk/Reward trade-off: As we increase the production quantity, both risk and reward increases. 2-38 2.2.4. What If the Manufacturer Has an Initial Inventory? Trade-off between: Using on-hand inventory to meet demand and avoid paying fixed production cost: need sufficient inventory stock Paying the fixed cost of production and not have as much inventory 2-39 Initial Inventory Solution FIGURE 2-8: Profit and the impact of initial inventory 2-40 2.2.5. Multiple Order Opportunities REASONS To balance annual inventory holding costs and annual fixed order costs. To satisfy demand occurring during lead time. To protect against uncertainty in demand. TWO POLICIES Continuous review policy inventory is reviewed continuously an order is placed when the inventory reaches a particular level or reorder point. inventory can be continuously reviewed (computerized inventory systems are used) Periodic review policy inventory is reviewed at regular intervals appropriate quantity is ordered after each review. it is impossible or inconvenient to frequently review inventory and place orders if necessary. 2-41 2.2.6. Continuous Review Policy Daily demand is random and follows a normal distribution. Every time the distributor places an order from the manufacturer, the distributor pays a fixed cost, K, plus an amount proportional to the quantity ordered. Inventory holding cost is charged per item per unit time. Inventory level is continuously reviewed, and if an order is placed, the order arrives after the appropriate lead time. If a customer order arrives when there is no inventory on hand to fill the order (i.e., when the distributor is stocked out), the order is lost. The distributor specifies a required service level. 2-42 Continuous Review Policy AVG = Average daily demand faced by the distributor STD = Standard deviation of daily demand faced by the distributor L = Replenishment lead time from the supplier to the distributor in days h = Cost of holding one unit of the product for one day at the distributor = service level. This implies that the probability of stocking out is 1 - 2-43 Continuous Review Policy (Q,R) policy - whenever inventory level falls to a reorder level R, place an order for Q units What is the value of R? 2-44 Continuous Review Policy Average demand during lead time: L x AVG z STD L Safety stock: Reorder Level, R: L AVG z STD Order Quantity, Q: Q L 2 K AVG h 2-45 Service Level & Safety Factor, z Service Level 90% 91% 92% 93% 94% 95% 96% 97% 98% 99% 99.9% z 1.29 1.65 1.34 1.41 1.48 1.56 1.75 1.88 2.05 2.33 3.08 z is chosen from statistical tables to ensure that the probability of stockouts during lead time is exactly 1 - 2-46 Inventory Level Over Time FIGURE 2-9: Inventory level as a function of time in a (Q,R) policy Inventory level before receiving an order = z STD L Inventory level after receiving an order = Q z STD L Average Inventory = Q 2 z STD L 2-47 Continuous Review Policy Example A distributor of TV sets that orders from a manufacturer and sells to retailers Fixed ordering cost = $4,500 Cost of a TV set to the distributor = $250 Annual inventory holding cost = 18% of product cost Replenishment lead time = 2 weeks Expected service level = 97% 2-48 Continuous Review Policy Example Month Sept Oct Nov. Dec. Jan. Feb. Mar. Apr. May June July Aug Sales 200 152 100 221 287 176 151 198 246 309 98 156 Average monthly demand = 191.17 Standard deviation of monthly demand = 66.53 Average weekly demand = Average Monthly Demand/4.3 Standard deviation of weekly demand = Monthly standard deviation/4.3 2-49 Continuous Review Policy Example Parameter Average weekly demand Standard deviation of weekly demand Average demand during lead time Safety stock Reorder point Value 44.58 32.08 89.16 86.20 176 Weekly holding cost = 0.18 250 52 Optimal order quantity = Q 0.87 2 4,500 44.58 .87 679 Average inventory level = 679/2 + 86.20 = 426 2-50 2.2.7. Variable Lead Times Average lead time, AVGL Standard deviation, STDL. Reorder Level, R: R AVG AVGL z AVGL STD 2 AVG 2 STDL2 2 z AVGL STD Amount of safety stock= Order Quantity = Q 2K AVG 2 STDL2 AVG h 2-51 2.2.8. Periodic Review Policy Inventory level is reviewed periodically at regular intervals An appropriate quantity is ordered after each review Two Cases: Short Intervals (e.g. Daily) Define two inventory levels s and S During each inventory review, if the inventory position falls below s, order enough to raise the inventory position to S. (s, S) policy Longer Intervals (e.g. Weekly or Monthly) May make sense to always order after an inventory level review. Determine a target inventory level, the base-stock level During each review period, the inventory position is reviewed Order enough to raise the inventory position to the base-stock level. Base-stock level policy 2-52 (s,S) policy Calculate the Q and R values as if this were a continuous review model Set s equal to R Set S equal to R+Q. 2-53 Base-Stock Level Policy Determine a target inventory level, the basestock level Each review period, review the inventory position is reviewed and order enough to raise the inventory position to the base-stock level Assume: r = length of the review period L = lead time AVG = average daily demand STD = standard deviation of this daily demand. 2-54 Base-Stock Level Policy Average demand during an interval of r + L days= (r L) AVG Safety Stock= z STD r L 2-55 Base-Stock Level Policy FIGURE 2-10: Inventory level as a function of time in a periodic review policy 2-56 Base-Stock Level Policy Example Assume: distributor places an order for TVs every 3 weeks Lead time is 2 weeks Base-stock level needs to cover 5 weeks Average demand = 44.58 x 5 = 222.9 Safety stock = 1.9 32.8 5 Base-stock level = 223 + 136 = 359 Average inventory level = 3 442 .58 1.9 32.08 Distributor keeps 5 (= 203.17/44.58) weeks of supply. 5 203.17 2-57 2.2.9. Service Level Optimization Optimal inventory policy assumes a specific service level target. What is the appropriate level of service? May be determined by the downstream customer Retailer may require the supplier, to maintain a specific service level Supplier will use that target to manage its own inventory Facility may have the flexibility to choose the appropriate level of service 2-58 Service Level Optimization FIGURE 2-11: Service level inventory versus inventory level as a function of lead time 2-59 Trade-Offs Everything else being equal: the higher the service level, the higher the inventory level. for the same inventory level, the longer the lead time to the facility, the lower the level of service provided by the facility. the lower the inventory level, the higher the impact of a unit of inventory on service level and hence on expected profit 2-60 Retail Strategy Given a target service level across all products determine service level for each SKU so as to maximize expected profit. Everything else being equal, service level will be higher for products with: high profit margin high volume low variability short lead time 2-61 Profit Optimization and Service Level FIGURE 2-12: Service level optimization by SKU 2-62 Profit Optimization and Service Level Target inventory level = 95% across all products. Service level > 99% for many products with high profit margin, high volume and low variability. Service level < 95% for products with low profit margin, low volume and high variability. 2-63 2.3 Risk Pooling Demand variability is reduced if one aggregates demand across locations. More likely that high demand from one customer will be offset by low demand from another. Reduction in variability allows a decrease in safety stock and therefore reduces average inventory. 2-64 Demand Variation Standard deviation measures how much demand tends to vary around the average Gives an absolute measure of the variability Coefficient of variation is the ratio of standard deviation to average demand Gives a relative measure of the variability, relative to the average demand 2-65 Acme Risk Pooling Case Electronic equipment manufacturer and distributor 2 warehouses for distribution in New York and New Jersey (partitioning the northeast market into two regions) Customers (that is, retailers) receiving items from warehouses (each retailer is assigned a warehouse) Warehouses receive material from Chicago Current rule: 97 % service level Each warehouse operate to satisfy 97 % of demand (3 % probability of stock-out) 2-66 New Idea Replace the 2 warehouses with a single warehouse (located some suitable place) and try to implement the same service level 97 % Delivery lead times may increase But may decrease total inventory investment considerably. 2-67 Historical Data PRODUCT A Week 1 2 3 4 5 6 7 8 Massachusetts 33 45 37 38 55 30 18 58 New Jersey 46 35 41 40 26 48 18 55 Total 79 80 78 78 81 78 36 113 PRODUCT B Week 1 2 3 4 5 6 7 8 Massachusetts 0 3 3 0 0 1 3 0 New Jersey 2 4 3 0 3 1 0 0 Total 2 6 3 0 3 2 3 0 2-68 Summary of Historical Data Statistics Product Average Demand Standard Deviation of Demand Coefficient of Variation Massachusetts A 39.3 13.2 0.34 Massachusetts B 1.125 1.36 1.21 New Jersey A 38.6 12.0 0.31 New Jersey B 1.25 1.58 1.26 Total A 77.9 20.71 0.27 Total B 2.375 1.9 0.81 2-69 Inventory Levels Product Average Demand During Lead Time Safety Stock Reorder Point Q Massachusetts A 39.3 25.08 65 132 Massachusetts B 1.125 2.58 4 25 New Jersey A 38.6 22.8 62 31 New Jersey B 1.25 3 5 24 Total A 77.9 39.35 118 186 Total B 2.375 3.61 6 33 2-70 Savings in Inventory Average inventory for Product A: At NJ warehouse is about 88 units At MA warehouse is about 91 units In the centralized warehouse is about 132 units Average inventory reduced by about 36 percent Average inventory for Product B: At NJ warehouse is about 15 units At MA warehouse is about 14 units In the centralized warehouse is about 20 units Average inventory reduced by about 43 percent 2-71 Critical Points The higher the coefficient of variation, the greater the benefit from risk pooling The higher the variability, the higher the safety stocks kept by the warehouses. The variability of the demand aggregated by the single warehouse is lower The benefits from risk pooling depend on the behavior of the demand from one market relative to demand from another risk pooling benefits are higher in situations where demands observed at warehouses are negatively correlated Reallocation of items from one market to another easily accomplished in centralized systems. Not possible to do in decentralized systems where they serve different markets 2-72 2.4 Centralized vs. Decentralized Systems Safety stock: lower with centralization Service level: higher service level for the same inventory investment with centralization Overhead costs: higher in decentralized system Customer lead time: response times lower in the decentralized system Transportation costs: not clear. Consider outbound and inbound costs. 2-73 2.5 Managing Inventory in the Supply Chain Inventory decisions are given by a single decision maker whose objective is to minimize the system-wide cost The decision maker has access to inventory information at each of the retailers and at the warehouse Echelons and echelon inventory Echelon inventory at any stage or level of the system equals the inventory on hand at the echelon, plus all downstream inventory (downstream means closer to the customer) 2-74 Echelon Inventory FIGURE 2-13: A serial supply chain 2-75 Reorder Point with Echelon Inventory Le = echelon lead time, lead time between the retailer and the distributor plus the lead time between the distributor and its supplier, the wholesaler. AVG = average demand at the retailer STD = standard deviation of demand at the retailer e Le Reorder point R L AVG z STD 2-76 4-Stage Supply Chain Example Average weekly demand faced by the retailer is 45 Standard deviation of demand is 32 At each stage, management is attempting to maintain a service level of 97% (z=1.88) Lead time between each of the stages, and between the manufacturer and its suppliers is 1 week 2-77 Costs and Order Quantities K D H Q retailer 250 45 1.2 137 distributor 200 45 .9 141 wholesaler 205 45 .8 152 manufacturer 500 45 .7 255 2-78 Reorder Points at Each Stage For the retailer, R=1*45+1.88*32*1 = 105 For the distributor, R=2*45+1.88*32*2 = 175 For the wholesaler, R=3*45+1.88*32*3 = 239 For the manufacturer, R=4*45+1.88*32*4 = 300 2-79 More than One Facility at Each Stage Follow the same approach Echelon inventory at the warehouse is the inventory at the warehouse, plus all of the inventory in transit to and in stock at each of the retailers. Similarly, the echelon inventory position at the warehouse is the echelon inventory at the warehouse, plus those items ordered by the warehouse that have not yet arrived minus all items that are backordered. 2-80 Warehouse Echelon Inventory FIGURE 2-14: The warehouse echelon inventory 2-81 2.6 Practical Issues Periodic inventory review. Tight management of usage rates, lead times, and safety stock. Reduce safety stock levels. Introduce or enhance cycle counting practice. ABC approach. Shift more inventory or inventory ownership to suppliers. Quantitative approaches. FOCUS: not reducing costs but reducing inventory levels. Significant effort in industry to increase inventory turnover Inventory_ Turnover_ Ratio Annual_ Sales Average_ Inventory_ Level 2-82 Inventory Turnover Ratios for Different Manufacturers Industry Upper quartile Median Lower quartile Electronic components and accessories 8.1 4.9 3.3 Electronic computers 22.7 7.0 2.7 Household audio and video equipment 6.3 3.9 2.5 Paper Mills 11.7 8.0 5.5 Industrial chemicals 14.1 6.4 4.2 Bakery products 39.7 23.0 12.6 Books: Publishing and printing 7.2 2.8 1.5 2-83 2.7 Forecasting RULES OF FORECASTING The forecast is always wrong. The longer the forecast horizon, the worse the forecast. Aggregate forecasts are more accurate. 2-84 Utility of Forecasting Part of the available tools for a manager Despite difficulties with forecasts, it can be used for a variety of decisions Number of techniques allow prudent use of forecasts as needed 2-85 Techniques Judgment Methods Market research/survey Time Series Moving Averages Exponential Smoothing Trends Sales-force composite Experts panel Delphi method Regression Holt's method Seasonal patterns - Seasonal decomposition Trend + Seasonality - Winter's Method Causal Methods 2-86 The Most Appropriate Technique(s) Purpose of the forecast How will the forecast be used? Dynamics of system for which forecast will be made How accurate is the past history in predicting the future? 2-87 SUMMARY Matching supply with demand a major challenge Forecast demand is always wrong Longer the forecast horizon, less accurate the forecast Aggregate demand more accurate than disaggregated demand Need the most appropriate technique Need the most appropriate inventory policy 2-88 IET 670 Supply Chain Design & Management Lecture 3 Chapter 3:Network Planning Dr. MD Sarder McGraw-Hill/Irwin Copyright 2008 by The McGraw-Hill Companies, Inc. All rights reserved. 3.1 Why Network Planning? Find the right balance between inventory, transportation and manufacturing costs, Match supply and demand under uncertainty by positioning and managing inventory effectively, Utilize resources effectively by sourcing products from the most appropriate manufacturing facility 3-2 Three Hierarchical Steps Network design Inventory positioning: Number, locations and size of manufacturing plants and warehouses Assignment of retail outlets to warehouses Major sourcing decisions Typical planning horizon is a few years. Identifying stocking points Selecting facilities that will produce to stock and thus keep inventory Facilities that will produce to order and hence keep no inventory Related to the inventory management strategies Resource allocation: Determine whether production and packaging of different products is done at the right facility What should be the plants sourcing strategies? How much capacity each plant should have to meet seasonal demand? 3-3 3.2 Network Design Physical configuration and infrastructure of the supply chain. A strategic decision with long-lasting effects on the firm. Decisions relating to plant and warehouse location as well as distribution and sourcing 3-4 Reevaluation of Infrastructure Changes in: demand patterns product mix production processes sourcing strategies cost of running facilities. Mergers and acquisitions may mandate the integration of different logistics networks 3-5 Key Strategic Decisions Determining the appropriate number of facilities such as plants and warehouses. Determining the location of each facility. Determining the size of each facility. Allocating space for products in each facility. Determining sourcing requirements. Determining distribution strategies, i.e., the allocation of customers to warehouse 3-6 Objective and Trade-Offs Objective: Design or reconfigure the logistics network in order to minimize annual system-wide cost subject to a variety of service level requirements Increasing the number of warehouses typically yields: An improvement in service level due to the reduction in average travel time to the customers An increase in inventory costs due to increased safety stocks required to protect each warehouse against uncertainties in customer demands. An increase in overhead and setup costs A reduction in outbound transportation costs: transportation costs from the warehouses to the customers An increase in inbound transportation costs: transportation costs from the suppliers and/or manufacturers to the warehouses. 3-7 Data Collection Locations of customers, retailers, existing warehouses and distribution centers, manufacturing facilities, and suppliers. All products, including volumes, and special transport modes (e.g., refrigerated). Annual demand for each product by customer location. Transportation rates by mode. Warehousing costs, including labor, inventory carrying charges, and fixed operating costs. Shipment sizes and frequencies for customer delivery. Order processing costs. Customer service requirements and goals. Production and sourcing costs and capacities 3-8 Data Aggregation Customer Zone Aggregate using a grid network or other clustering technique for those in close proximity. Replace all customers within a single cluster by a single customer located at the center of the cluster Five-digit or three-digit zip code based clustering. Product Groups Distribution pattern Products picked up at the same source and destined to the same customers Logistics characteristics like weight and volume. Product type product models or style differing only in the type of packaging. 3-9 Replacing Original Detailed Data with Aggregated Data Technology exists to solve the logistics network design problem with the original data Data aggregation still useful because forecast demand is significantly more accurate at the aggregated level Aggregating customers into about 150-200 zones usually results in no more than a 1 percent error in the estimation of total transportation costs 3-10 General Rules for Aggregation Aggregate demand points into at least 200 zones Make sure each zone has approximately an equal amount of total demand Holds for cases where customers are classified into classes according to their service levels or frequency of delivery Zones may be of different geographic sizes. Place aggregated points at the center of the zone Aggregate products into 20 to 50 product groups 3-11 Customer Aggregation Based on 3-Digit Zip Codes Total Cost:$5,796,000 Total Customers: 18,000 Total Cost:$5,793,000 Total Customers: 800 Cost Difference < 0.05% 3-12 Product Aggregation Total Cost:$104,564,000 Total Products: 46 Total Cost:$104,599,000 Total Products: 4 Cost Difference: 0.03% 3-13 Transportation Rates Rates are almost linear with distance but not with volume Differences between internal rate and external rate 3-14 Internal Transportation Rate For company-owned trucks Data Required: Annual costs per truck Annual mileage per truck Annual amount delivered Truck's effective capacity Calculate cost per mile per SKU. 3-15 External Transportation Rate Two Modes of Transportation Truckload, TL Country sub-divided into zones. One zone/state except for: Zone-to-zone costs provides cost per mile per truckload between any two zones. Big states, such as Florida or New York (two zones) TL cost from Chicago to Boston = Illinois-Massachusetts cost per mile X ChicagoBoston distance TL cost structure is not symmetric 3-16 External Transportation Rate Two Modes of Transportation Less-Than-Truckload, LTL Class rates standard rates for almost all products or commodities shipped. Classification tariff system that gives each shipment a rating or a class. Factors involved in determining a product's specific class include: After establishing rating, identify rate basis number. product density, ease or difficulty of handling and transporting, and liability for damage. Approximate distance between the load's origin and destination. With the two, determine the specific rate per hundred pounds (hundred weight, or cwt) from a carrier tariff table (i.e., a freight rate table). Exception rates provides less expensive rates Commodity rates are specialized commodity-specific rates 3-17 SMC3's CzarLite Engine to find rates in fragmented LTL industry Nationwide LTL zip code-based rate system. Offers a market-based price list derived from studies of LTL pricing on a regional, interregional, and national basis. A fair pricing system Often used as a base for negotiating LTL contracts between shippers, carriers, and thirdparty logistics providers 3-18 Transportation Rate for Shipping 4,000 lbs. FIGURE 3-7: Transportation rates for shipping 4,000 lb 3-19 Mileage Estimation Estimate lona and lata, the longitude and latitude of point a (and similarly for point b) Distance between a and b For short distances Dab 69 (lona lonb ) 2 (lata latb ) 2 For large distances Dab 2(69) sin 1 (sin( lata latb 2 lona lonb 2 )) cos(lata ) X cos(latb ) X (sin( )) 2 2 3-20 Circuity Factor, Equations underestimate the actual road distance. Multiply Dab by . Typical values: = 1.3 in metropolitan areas = 1.14 for the continental United States 3-21 Chicago-Boston Distance lonChicago = -87.65 latChicago = 41.85 lonBoston = -71.06 lonBoston = 42.36 DChicago, Boston = 855 miles Multiply by circuity factor = 1.14 Estimated road distance = 974 miles Actual road distance = 965 miles GIS systems provide more accuracy Slows down systems Above approximation good enough! 3-22 Warehouse Costs Handling costs Fixed costs Labor and utility costs Proportional to annual flow through the warehouse. All cost components not proportional to the amount of flow Typically proportional to warehouse size (capacity) but in a nonlinear way. Storage costs Inventory holding costs Proportional to average positive inventory levels. 3-23 Determining Fixed Costs FIGURE 3-8: Warehouse fixed costs as a function of the warehouse capacity 3-24 Determining Storage Costs Multiply inventory turnover by holding cost Inventory Turnover = Annual Sales / Average Inventory Level 3-25 Warehouse Capacity Estimation of actual space required Average inventory level = Annual flow through warehouse/Inventory turnover ratio Space requirement for item = 2*Average Inventory Level Multiply by factor to account for access and handling aisles, picking, sorting and processing facilities AGVs Typical factor value = 3 3-26 Warehouse Capacity Example Annual flow = 1,000 units Inventory turnover ratio = 10.0 Average inventory level = 100 units Assume each unit takes 10 sqft. of space Required space for products = 2,000 sqft. Total space required for the warehouse is about 6,000 square feet 3-27 Potential Locations Geographical and infrastructure conditions. Natural resources and labor availability. Local industry and tax regulations. Public interest. Not many will qualify based on all the above conditions 3-28 Service Level Requirements Specify a maximum distance between each customer and the warehouse serving it Proportion of customers whose distance to their assigned warehouse is no more than a given distance 95% of customers be situated within 200 miles of the warehouses serving them Appropriate for rural or isolated areas 3-29 Future Demand Strategic decisions have to be valid for 3-5 years Consider scenario approach and net present values to factor in expected future demand over planning horizon 3-30 Number of Warehouses Optimal Number of Warehouses $90 $80 Cost (millions $) $70 $60 Total Cost Transportation Cost Fixed Cost Inventory Cost $50 $40 $30 $20 $10 $- 0 2 4 6 8 10 Number of Warehouses 3-31 Industry Benchmarks: Number of Distribution Centers Pharmaceuticals Avg. # of WH 3 - High margin product - Service not important (or easy to ship express) - Inventory expensive relative to transportation Food Companies 14 Chemicals 25 - Low margin product - Service very important - Outbound transportation expensive relative to inbound 3-32 Model Validation Reconstruct the existing network configuration using the model and collected data Compare the output of the model to existing data Compare to the company's accounting information Make local or small changes in the network configuration to see how the system estimates impact on costs and service levels. Often the best way to identify errors in the data, problematic assumptions, modeling flaws. Positing a variety of what-if questions. Answer the following questions: Does the model make sense? Are the data consistent? Can the model results be fully explained? Did you perform sensitivity analysis? 3-33 Solution Techniques Mathematical optimization techniques: 1. Exact algorithms: find optimal solutions 2. Heuristics: find \"good\" solutions, not necessarily optimal Simulation models: provide a mechanism to evaluate specified design alternatives created by the designer. 3-34 Example 3.3 Single product Two plants p1 and p2 Plant p2 has an annual capacity of 60,000 units. The two plants have the same production costs. There are two warehouses w1 and w2 with identical warehouse handling costs. There are three markets areas c1,c2 and c3 with demands of 50,000, 100,000 and 50,000, respectively. 3-35 Unit Distribution Costs Facility warehouse p1 p2 c1 c2 c3 w1 0 4 3 4 5 w2 5 2 2 1 2 3-36 Heuristic #1: Choose the Cheapest Warehouse to Source Demand D = 50,000 $2 x 50,000 $5 x 140,000 Cap = 60,000 $2 x 60,000 D = 100,000 $1 x 100,000 $2 x 50,000 D = 50,000 Total Costs = $1,120,000 3-37 Heuristic #2: Choose the warehouse where the total delivery costs to and from the warehouse are the lowest [Consider inbound and outbound distribution costs] $0 D = 50,000 $3 $5 $4 $2 $5 $3 $7 $7 $4 D = 100,000 $4 Cap = 60,000 P1 to WH1 P1 to WH2 P2 to WH1 P2 to WH 2 P1 to WH1 P1 to WH2 P2 to WH1 P2 to WH 2 $1 $2 $2 $4 $6 $8 $3 D = 50,000 P1 to WH1 P1 to WH2 P2 to WH1 P2 to WH 2 $5 $7 $9 $4 Market #1 is served by WH1, Markets 2 and 3 are served by WH2 3-38 Heuristic #2: Choose the warehouse where the total delivery costs to and from the warehouse are the lowest [Consider inbound and outbound distribution costs] $0 x 50,000 D = 50,000 $3 x 50,000 Cap = 200,000 P1 to WH1 P1 to WH2 P2 to WH1 P2 to WH 2 $5 x 90,000 D = 100,000 $1 x 100,000 Cap = 60,000 $3 $7 $7 $4 $2 x 60,000 $2 x 50,000 P1 to WH1 P1 to WH2 P2 to WH1 P2 to WH 2 $4 $6 $8 $3 D = 50,000 P1 to WH1 P1 to WH2 P2 to WH1 P2 to WH 2 $5 $7 $9 $4 Total Cost = $920,000 3-39 The Optimization Model The problem described earlier can be framed as the following linear programming problem. Let x(p1,w1), x(p1,w2), x(p2,w1) and x(p2,w2) be the flows from the plants to the warehouses. x(w1,c1), x(w1,c2), x(w1,c3) be the flows from the warehouse w1 to customer zones c1, c2 and c3. x(w2,c1), x(w2,c2), x(w2,c3) be the flows from warehouse w2 to customer zones c1, c2 and c3 3-40 The Optimization Model The problem we want to solve is: min 0x(p1,w1) + 5x(p1,w2) + 4x(p2,w1) + 2x(p2,w2) + 3x(w1,c1) + 4x(w1,c2) + 5x(w1,c3) + 2x(w2,c1) + 2x(w2,c3) subject to the following constraints: x(p2,w1) + x(p2,w2) 60000 x(p1,w1) + x(p2,w1) = x(w1,c1) + x(w1,c2) + x(w1,c3) x(p1,w2) + x(p2,w2) = x(w2,c1) + x(w2,c2) + x(w2,c3) x(w1,c1) + x(w2,c1) = 50000 x(w1,c2) + x(w2,c2) = 100000 x(w1,c3) + x(w2,c3) = 50000 all flows greater than or equal to zero. 3-41 Optimal Solution Facility warehouse p1 p2 c1 c2 c3 w1 140,000 0 50,000 40,000 50,000 w2 0 60,000 0 60,000 0 Total cost for the optimal strategy is $740,000 3-42 Simulation Models Useful for a given design and a micro-level analysis. Examine: Individual ordering pattern. Specific inventory policies. Inventory movements inside the warehouse. Not an optimization model Can only consider very few alternate models 3-43 Which One to Use? Use mathematical optimization for static analysis Use a 2-step approach when dynamics in system has to be analyzed: Use an optimization model to generate a number of least-cost solutions at the macro level, taking into account the most important cost components. Use a simulation model to evaluate the solutions generated in the first phase. 3-44 DSS for Network Design Flexibility to incorporate a large set of preexisting network characteristics Other Factors: Customer-specific service level requirements. Existing warehouses kept open Expansion of existing warehouses. Specific flow patterns maintained Warehouse-to-warehouse flow possible Production and Bill of materials details may be important Robustness Relative quality of the solution independent of specific environment, data variability or specific settings 3-45 3.3 Inventory Positioning and Logistics Coordination Multi-facility supply chain that belongs to a single firm Manage inventory so as to reduce system wide cost Consider the interaction of the various facilities and the impact of this interaction on the inventory policy of each facility Ways to manage: Wait for specific orders to arrive before starting to manufacture them [make-to-order facility] Otherwise, decide on where to keep safety stock? Which facilities should produce to stock and which should produce to order? 3-46 Single Product, Single Facility Periodic Review Inventory Model Assume SI: amount of time between when an order is placed until the facility receives a shipment (Incoming Service Time) S: Committed Service Time made by the facility to its own customers. T: Processing Time at the facility. SI T S Net Lead Time = SI + T - S Safety stock at the facility: zh SI T S 3-47 2-Stage System Reducing committed service time from facility 2 to facility 1 impacts required inventory at both facilities Inventory at facility 1 is reduced Inventory at facility 2 is increased Overall objective is to choose: the committed service time at each facility the location and amount of inventory minimize total or system wide safety stock cost. 3-48 ElecComp Case Large contract manufacturer of circuit boards and other high tech parts. About 27,000 high value products with short life cycles Fierce competition => Low customer promise times < Manufacturing Lead Times High inventory of SKUs based on long-term forecasts => Classic PUSH STRATEGY High shortages Huge risk PULL STRATEGY not feasible because of long lead times 3-49 New Supply Chain Strategy OBJECTIVES: ACHIEVE THE FOLLOWING: Push Stages produce to stock where the company keeps safety stock Pull stages keep no stock at all. Challenge: Determining the optimal location of inventory across the various stages Calculating the optimal quantity of safety stock for each component at each stage Hybrid strategy of Push and Pull Reduce inventory and financial risks Provide customers with competitive response times. Identify the location where the strategy switched from Push-based to Pull-based Identify the Push-Pull boundary Benefits: For same lead times, safety stock reduced by 40 to 60% Company could cut lead times to customers by 50% and still reduce safety stocks by 30% 3-50 Notations Used FIGURE 3-11: How to read the diagrams 3-51 Trade-Offs If Montgomery facility reduces committed lead time to 13 days assembly facility does not need any inventory of finished goods Any customer order will trigger an order for parts 2 and 3. Part 2 will be available immediately, since it is held in inventory Part 3 will be available in 15 days 13 days committed response time by the manufacturing facility 2 days transportation lead time. Another 15 days to process the order at the assembly facility Order is delivered within the committed service time. Assembly facility produces to order, i.e., a Pull based strategy Montgomery facility keeps inventory and hence is managed with a Push or Make-to-Stock strategy. 3-52 Current Safety Stock Location FIGURE 3-12: Current safety stock location 3-53 Optimized Safety Stock Location FIGURE 3-13: Optimized safety stock 3-54 Current Safety Stock with Lesser Lead Time FIGURE 3-14: Optimized safety stock with reduced lead time 3-55 Supply Chain with More Complex Product Structure FIGURE 3-15: Current supply chain 3-56 Optimized Supply Chain with More Complex Product Structure FIGURE 3-16: Optimized supply chain 3-57 Key Points Identifying the Push-Pull boundary Taking advantage of the risk pooling concept Demand for components used by a number of finished products has smaller variability and uncertainty than that of the finished goods. Replacing traditional supply chain strategies that are typically referred to as sequential, or local, optimization by a globally optimized supply chain strategy. 3-58 Local vs. Global Optimization FIGURE 3-17: Trade-off between quoted lead time and safety stock 3-59 Global Optimization For the same lead time, cost is reduced significantly For the same cost, lead time is reduced significantly Trade-off curve has jumps in various places Represents situations in which the location of the Push-Pull boundary changes Significant cost savings are achieved. 3-60 Problems with Local Optimization Prevalent strategy for many companies: try to keep as much inventory close to the customers hold some inventory at every location hold as much raw material as possible. This typically yields leads to: Low inventory turns Inconsistent service levels across locations and products, and The need to expedite shipments, with resulting increased transportation costs 3-61 Integrating Inventory Positioning and Network Design Consider a two-tier supply chain Items shipped from manufacturing facilities to primary warehouses From there, they are shipped to secondary warehouses and finally to retail outlets How to optimally position inventory in the supply chain? Should every SKU be positioned both at the primary and secondary warehouses?, OR Some SKU be positioned only at the primary while others only at the secondary? 3-62 Integrating Inventory Positioning and Network Design FIGURE 3-18: Sample plot of each SKU by volume and demand 3-63 Three Different Product Categories High variability - low volume products Low variability - high volume products, and Low variability - low volume products. 3-64 Supply Chain Strategy Different for the Different Categories High variability low volume products Inventory risk the main challenge for Position them mainly at the primary warehouses Low variability high volume products demand from many retail outlets can be aggregated reducing inventory costs. Position close to the retail outlets at the secondary warehouses Ship fully loaded tracks as close as possible to the customers reducing transportation costs. Low variability low volume products Require more analysis since other characteristics are important, such as profit margins, etc. 3-65 3.4 Resource Allocation Supply chain master planning The process of coordinating and allocating production, and distribution strategies and resources to maximize profit or minimize system-wide cost Process takes into account: interaction between the various levels of the supply chain identifies a strategy that maximizes supply chain performance 3-66 Global Optimization and DSS FACTORS TO CONSIDER Facility locations: plants, distribution centers and demand points Transportation resources including internal fleet and common carriers Products and product information Production line information such as min lot size, capacity, costs, etc. Warehouse capacities and other information such as certain technology (refrigerators) that a specific warehouse has and hence can store certain products Demand forecast by location, product and time. 3-67 Focus of the Output Sourcing Strategies: where should each product be produced during the planning horizon, OR Supply Chain Master Plan: production quantities, shipment size and storage requirements by product, location and time period. 3-68 The Extended Supply Chain: From Manufact