AGGREGATE & CAPACITY PLANNING

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1 7 Ir. Haery Sihombing/IP Pensyarah Fakulti Kejuruteraan Pembuatan Universiti Teknologi Malaysia Melaka AGGREGATE & CAPACITY PLANNING Aggregate Planning Determine the resource capacity needed to meet demand over an intermediate time horizon Aggregate refers to product lines or families Aggregate planning matches supply and demand Objectives Establish a company wide game plan for allocating resources Develop an economic strategy for meeting demand Aggregate Planning Process Meeting Demand Strategies Adjusting capacity Resources necessary to meet demand are acquired and maintained over the time horizon of the plan Minor variations in demand are handled with overtime or under-time Managing demand Proactive demand management Strategies for Adjusting Capacity Level Production Level production Producing at a constant rate and using inventory to absorb fluctuations in demand Chase demand Hiring and firing workers to match demand Peak demand Maintaining resources for high-demand levels Overtime and under-time Increasing or decreasing working hours Subcontracting Let outside companies complete the work Part-time time workers Hiring part time workers to complete the work Backordering Providing the service or product at a later time period Units Demand Production Time

2 Chase Demand Demand Production Strategies for Managing Demand Shifting demand into other time periods Incentives Sales promotions Advertising campaigns Units Offering products or services with counter-cyclical cyclical demand patterns Partnering with suppliers to reduce information distortion along the supply chain Time Quantitative Techniques For APP Pure Strategies Example: Pure Strategies Mixed Strategies Linear Programming Transportation Method Other Quantitative Techniques QUARTER Spring Summer Fall Winter SALES FORECAST (LB) Spring 80,000 Summer 50,000 Fall 120,000 Winter 150,000 Hiring cost = $100 per worker Firing cost = $500 per worker Regular production cost per pound = $2.00 Inventory carrying cost = $0.50 pound per quarter Production per employee = 1,000 pounds per quarter Beginning work force = 100 workers Level Production Strategy Chase Demand Strategy Level production (50, , , ,000) 4 = 100,000 pounds SALES PRODUCTION QUARTER FORECAST PLAN INVENTORY Spring 80, ,000 20,000 Summer 50, ,000 70,000 Fall 120, ,000 50,000 Winter 150, , , ,000 Cost of Level Production Strategy (400,000 X $2.00) + (140,00 X $.50) = $870,000 QUARTER SALES PRODUCTION FORECAST PLAN WORKERS WORKERS WORKERS NEEDED HIRED FIRED Spring 80,000 80, Summer 50,000 50, Fall 120, , Winter 150, , Cost of Chase Demand Strategy (400,000 X $2.00) + (100 x $100) + (50 x $500) = $835,000

3 Mixed Strategy Combination of Level Production and Chase Demand strategies Examples of management policies no more than x% of the workforce can be laid off in one quarter inventory levels cannot exceed x dollars Many industries may simply shut down manufacturing during the low demand season and schedule employee vacations during that time General Linear Programming (LP) Model LP gives an optimal solution, but demand and costs must be linear Let W t = workforce size for period t P t =units produced in period t I t =units in inventory at the end of period t F t =number of workers fired for period t H t = number of workers hired for period t Subject to LP MODEL Minimize Z = $100 (H 1 + H 2 + H 3 + H 4 ) + $500 (F 1 + F 2 + F 3 + F 4 ) + $0.50 (I 1 + I 2 + I 3 + I 4 ) P 1 - I 1 = 80,000 (1) Demand I 1 + P 2 - I 2 = 50,000 (2) constraints I 2 + P 3 - I 3 = 120,000 (3) I 3 + P 4 - I 4 = 150,000 (4) Production 1000 W 1 = P 1 (5) constraints 1000 W 2 = P 2 (6) 1000 W 3 = P 3 (7) 1000 W 4 = P 4 (8) H 1 - F 1 = W 1 (9) Work force W 1 + H 2 - F 2 = W 2 (10) constraints W 2 + H 3 - F 3 = W 3 (11) W 3 + H 4 - F 4 = W 4 (12) QUARTER Transportation Method EXPECTED DEMAND REGULAR CAPACITY OVERTIME CAPACITY Regular production cost per unit $20 Overtime production cost per unit $25 Subcontracting cost per unit $28 Inventory holding cost per unit per period $3 Beginning inventory 300 units SUBCONTRACT CAPACITY Transportation Tableau PERIOD OF USE Burruss Production Plan Unused PERIOD OF PRODUCTION Capacity Capacity Beginning Inventory Regular Overtime Subcontract Regular Overtime Subcontract Regular Overtime Subcontract Regular Overtime Subcontract Demand REGULAR PERIOD DEMAND PRODUCTION OVERTIME SUB- ENDING CONTRACT INVENTORY Total

4 Other Quantitative Techniques Hierarchical Nature of Planning Linear decision rule (LDR) Search decision rule (SDR) Management coefficients model Items Product lines or families Individual products Production Planning Aggregate production plan Master production schedule Capacity Planning Resource requirements plan Rough-cut capacity plan Resource Level Plants Critical work centers Components Material requirements plan Capacity requirements plan All work centers Manufacturing operations Shop floor schedule Input/ output control Individual machines Available-to-Promise (ATP) ATP: Example Quantity of items that can be promised to the customer Difference between planned production and customer orders already received AT in period 1 = (On-hand quantity + MPS in period 1) - (CO until the next period of planned production) ATP in period n = (MPS in period n) - (CO until the next period of planned production) ATP: Example (cont.) ATP: Example (cont.) ATP in April = (10+100) 70 = 40 ATP in May = = -10 ATP in June = = 50 Take excess units from April = 30 = 0

5 Rule Based ATP Aggregate Planning for Services Product Request Allocate inventory Yes Yes Yes Is the product available at this location? No Is an alternative product available at this location? No Is this product available at a different location? Is an alternative product available at an alternate location? No Availableto-promise Capable-topromise date Is the customer willing to wait for the product? No Yes Yes Availableto-promise Allocate inventory Revise master schedule Trigger production 1. Most services can t t be inventoried 2. Demand for services is difficult to predict 3. Capacity is also difficult to predict 4. Service capacity must be provided at the appropriate place and time 5. Labor is usually the most constraining resource for services No Lose sale Yield Management Yield Management (cont.) Yield Management: Example TIME - BREAK NO-SHOWS PROBABILITY P(N < X) Optimal probability of no-shows C P(n < x) u 75 = =.517 C u + C o Hotel should be overbooked by two rooms

6 OBJECTIVES Strategic Capacity Planning Strategic Capacity Planning Defined Capacity Utilization & Best Operating Level Economies & Diseconomies of Scale The Experience Curve Capacity Focus, Flexibility & Planning Determining Capacity Requirements Decision Trees Capacity Utilization & Service Quality Strategic Capacity Planning Defined Capacity can be defined as the ability to hold, receive, store, or accommodate Strategic capacity planning is an approach for determining the overall capacity level of capital intensive resources, including facilities, equipment, and overall labor force size Capacity Utilization Capacity utilization rate Capacity used Best operating level Where is it used Capacity used rate of output actually achieved Best operating level capacity for which the process was designed Best Operating Level Example: Engineers design engines and assembly lines to operate at an ideal or best operating level to maximize output and minimize ware Average unit cost of output Underutilization Volume Overutilization Best Operating Level Example of Capacity Utilization During one week of production, a plant produced 83 units of a product. Its historic highest or best utilization recorded was 120 units per week. What is this plant s s capacity utilization rate? Answer: Capacity utilization rate = Capacity used. Best operating level = 83/120 =0.69 or 69%

7 Economies & Diseconomies of Scale Economies of Scale and the Experience Curve working The Experience Curve As plants produce more products, they gain experience in the best production methods and reduce their costs per unit Average unit cost of output 100-unit plant 200-unit plant 300-unit plant 400-unit plant Cost or price per unit Yesterday Today Tomorrow Diseconomies of Scale start working Volume Total accumulated production of units Capacity Focus The concept of the focused factory holds that production facilities work best when they focus on a fairly limited set of production objectives Plants Within Plants (PWP) (from Skinner) Extend focus concept to operating level Capacity Flexibility Flexible plants Flexible processes Flexible workers Capacity Planning: Balance Capacity Planning Units per month Unbalanced stages of production Stage 1 Stage 2 Stage 3 6,000 7,000 5,000 Frequency of Capacity Additions Maintaining System Balance: : Output of one stage is the exact input requirements for the next stage Units per month Balanced stages of production Stage 1 Stage 2 Stage 3 6,000 6,000 6,000 External Sources of Capacity

8 Determining Capacity Requirements 1. Forecast sales within each individual product line 2. Calculate equipment and labor requirements to meet the forecasts 3. Project equipment and labor availability over the planning horizon Example of Capacity Requirements A manufacturer produces two lines of mustard, FancyFine and Generic line. Each is sold in small and family-size plastic bottles. The following table shows forecast demand for the next four years. Year: FancyFine Small (000s) Family (000s) Generic Small (000s) Family (000s) Example of Capacity Requirements (Cont): Product from a Capacity Viewpoint Example of Capacity Requirements (Cont) : Equipment and Labor Requirements Question: : Are we really producing two different types of mustards from the standpoint of capacity requirements? Answer: : No, it s s the same product just packaged differently. Year: Small (000s) Family (000s) Three 100,000 units-per per-year machines are available for small-bottle production. Two operators required per machine. Two 120,000 units-per per-year machines are available for family-sized sized-bottle production. Three operators required per machine. Question: What are the Year 1 values for capacity, machine, and labor? Year: Small (000s) Family (000s) Small Mach. Cap. 300,000 Labor 6 Family-size Mach. Cap. 240,000 Labor 6 Small 150,000/300,000=50% At 1 machine for 100,000, it takes 1.5 machines for 150,000 Percent capacity used 50.00% Machine requirement 1.50 Labor requirement 3.00 At 2 operators for Family-size Percent capacity used 47.92% 100,000, it takes 3 operators for 150,000 Machine requirement 0.96 Labor requirement 2.88 The McGraw-Hill Companies, Inc., Question: What are the values for columns 2, 3 and 4 in the table below? Year: Small (000s) Family (000s) Small Mach. Cap. 300,000 Labor 6 Family-size Mach. Cap. 240,000 Labor 6 Small Percent capacity used 50.00% 56.67% Machine requirement Labor requirement Family-size Percent capacity used 47.92% 58.33% Machine requirement Labor requirement % % % % The McGraw-Hill Companies, Inc., 2004

9 Example of a Decision Tree Problem A glass factory specializing in crystal is experiencing a substantial backlog, and the firm's management is considering three courses of action: A) Arrange for subcontracting B) Construct new facilities C) Do nothing (no change) The correct choice depends largely upon demand, which may be low, medium, or high. By consensus, management estimates the respective demand probabilities as 0.1, 0.5, and 0.4. Example of a Decision Tree Problem (Cont): The Payoff Table The management also estimates the profits when choosing from the three alternatives (A, B, and C) under the differing probable levels of demand. These profits, in thousands of dollars are presented in the table below: Low Medium High A B C Example of a Decision Tree Problem (Cont): Step 1. We start by drawing the three decisions Example of Decision Tree Problem (Cont): Step 2. Add our possible states of nature, probabilities & payoffs A C B A B C $90k $50k $10k $200k $25k -$120k $60k $40k $20k Example of Decision Tree Problem (Cont): Step 3. 3 Determine the expected value of each decision Example of Decision Tree Problem (Cont): Step 4. Make decision A $62k $90k $50k $10k EV A =0.4(90)+0.5(50)+0.1(10)=$62k $62k A $80.5k B C $46k $90k $50k $10k $200k $25k -$120k $60k $40k $20k Alternative B generates the greatest expected profit, so our choice is B or to construct a new facility

10 Planning Service Capacity vs. Manufacturing Capacity Time: : Goods can not be stored for later use and capacity must be available to provide a service when it is needed Location: : Service goods must be at the customer demand point and capacity must be located near the customer Volatility of Demand: : Much greater than in manufacturing Capacity Utilization & Service Quality Best operating point is near 70% of capacity From 70% to 100% of service capacity, what do you think happens to service quality? The objective of Strategic Capacity Planning is to provide an approach for determining the overall capacity level of which of the following? a. Facilities b. Equipment c. Labor force size d. All of the above. To improve the Capacity Utilization Rate we can do which of the following? a. Reduce capacity used b. Increase capacity used. c. Increase best operating level d. All of the above (This increases the numerator in the Capacity Utilization Rate ratio, which is desirable.) When we talk about Capacity Flexibility which of the following types of flexibility are included? a. Plants b. Processes c. Workers d. All of the above. When adding capacity to existing operations which of the following are considerations that should be included in the planning effort? a. Maintaining system balance b. Frequency of additions c. External sources d. All of the above.

11 Which of the following is a term used to describe the difference between projected capacity requirements and the actual capacity requirements? a. Capacity cushion. b. Capacity utilization c. Capacity utilization rate d. All of the above In determining capacity requirements we must do which of the following? a. Address the demands for individual product lines b. Address the demands for individual plants c. Allocate production throughout the plant network d. All of the above. In a Decision Tree problem used to evaluate capacity alternatives we need which of the following as prerequisite information? a. Expect values of payoffs b. Payoff values. c. A tree d. All of the above (Expected values are what is computed, not prerequisite to the analysis.) THE END

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