Long-Range Capacity Planning William J. Stevenson 9th edition

Learning Objectives Explain the importance of capacity planning. Discuss ways of defining and measuring capacity. Describe the determinants of effective capacity. Discuss the major considerations related to developing capacity alternatives. Briefly describe approaches that are useful for evaluating capacity alternatives

The Hierarchy of Production Decisions All planning starts with the demand forecast. Demand forecasts are the basis for the top level long_range capacity, and medium term aggregate planning. The Master Production Schedule (MPS) is the result of disaggregating aggregate plans down to the individual item level. Based on the MPS, MRP is used to determine the size and timing of component and subassembly production. Detailed shop floor schedules are required to meet production plans resulting from the MRP.

Hierarchy of Production Decisions Long-range Capacity Planning

Capacity Planning Capacity is the upper limit or ceiling on the load that an operating unit can handle. The basic questions in capacity handling are: What kind of capacity is needed? How much is needed? (Forecasts are key inputs) When is it needed?

Importance of Capacity Decisions Capacity decisions are important to all departments of the organization; An accountant would be interested in collecting cost accounting information in order to ensure that correct capacity expansion decision is reached.

Importance of Capacity Decisions Similarly a financial manager would be interested in performing the financial analysis of whether the investment decision is justified for a plant or capacity increase.

Importance of Capacity Decisions An Information Technology Manager would end up preparing data bases that would aid the organization to decide about the capacity and last but not the least an operations manager would select strategies that would help the organization achieve the optimum capacity levels to meet the customer demand.

Importance of Capacity Decisions Impacts ability to meet future demands Affects operating costs Major determinant of initial costs Involves long-term commitment Affects competitiveness Affects ease of management Globalization adds complexity Impacts long range planning

Globalization adds complexity Capacity decision often involves making a decision in a foreign country which requires the management to know about the political, economic and cultural issues.

Capacity Design capacity Effective capacity Actual output maximum output rate or service capacity an operation, process, or facility is designed for Effective capacity Design capacity minus allowances such as personal time, maintenance, and scrap Actual output rate of output actually achieved--cannot exceed effective capacity.

Efficiency and Utilization Actual output Efficiency = Effective capacity Utilization = Design capacity Both measures expressed as percentages

Efficiency/Utilization Example Design capacity = 50 trucks/day Effective capacity = 40 trucks/day Actual output = 36 units/day Actual output = 36 units/day Efficiency = = 90% Effective capacity 40 units/ day Utilization = Actual output = 36 units/day = 72% Design capacity 50 units/day

Key Decisions of Capacity Planning Amount of capacity needed Timing of changes Need to maintain balance Extent of flexibility of facilities Capacity cushion – extra demand intended to offset uncertainty The greater the degree of demand uncertainity, the greater the amount of cushion

Steps for Capacity Planning Estimate future capacity requirements Evaluate existing capacity Identify alternatives Conduct financial analysis Assess key qualitative issues Select one alternative Implement alternative chosen Monitor results

Calculating Processing Requirements If annual capacity is 2000 (8hr/day*250 days *1 machine) hours, then we need three machines to handle the required volume: 5,800 hours/2,000 hours = 2.90 machines

Planning Service Capacity Need to be near customers Capacity and location are closely tied Inability to store services Capacity must be matched with timing of demand Degree of volatility of demand Peak demand periods

Make or Buy? Available capacity. If an organization has available the equipment, necessary skills, and time, it often makes sense to produce an item or perform a service in-house. Expertise. If a firm lacks the expertise to do a job satisfactorily, buying might be a reasonable alternative. Quality considerations. Firms that specialize can usually offer higher quality than an organization can attain itself. Conversely, unique quality requirements or the desire to closely monitor quality may cause an organization to perform a job itself. The nature of demand. When demand for an item is high and steady, the organization is often better off doing the work itself. However, wide fluctuations in demand or small orders are usually better handled by specialists who are able to combine orders from multiple sources, which results in higher volume and tends to offset individual buyer fluctuations. Cost. Cost savings might come from the item itself or from transportation cost savings. If there are fixed costs associated with making an item that cannot be reallocated if the service or product is outsourced, that has to be recognized in the analysis. Conversely, outsourcing may help a firm avoid incurring fixed costs. Risk. Outsourcing may involve certain risks. One is loss of control over operations. Another is the need to disclose proprietary information. http://www.baskent.edu.tr/~kilter

Capacity Planning Based-on Bottleneck Operation Figure 5.2 Bottleneck operation: An operation in a sequence of operations whose capacity is lower than that of the other operations Bottleneck Operation Machine #1 Machine #3 Machine #4 10/hr 30/hr Machine #2

Bottleneck Operation Operation 1 20/hr. Operation 2 10/hr. Maximum output rate limited by bottleneck

Developing Capacity Alternatives 1. Design flexibility into systems 2. Take stage of life cycle into account 3. Take a “big picture” approach to capacity changes 4.Prepare to deal with capacity “chunks” 5. Attempt to smooth out capacity requirements (due to random variations or seasonal variations) 6. Identify the optimal operating level

Prepare to deal with capacity “chunks Prepare to deal with capacity “chunks.” Capacity increases are often acquired in fairly large chunks rather than smooth increments, making it difficult to achieve a match between desired capacity and feasible capacity. Attempt to smooth out capacity requirements. Unevenness in capacity requirements also can create certain problems. http://www.baskent.edu.tr/~kilter

Economies of Scale Economies of scale Diseconomies of scale If the output rate is less than the optimal level, increasing output rate results in decreasing average unit costs. This results from fixed costs, labor cost being spread over more units Diseconomies of scale If the output rate is more than the optimal level, increasing the output rate results in increasing average unit costs. Due to scheduling problems, quality problems, reduced morale, increased use of overtime.

Evaluating Alternatives Figure 5.3 Production units have an optimal rate of output for minimal cost. Minimum cost Average cost per unit Rate of output Minimum average cost per unit

Economies and Diseconomies of Scale Average Unit Cost of Output ($) Economies of Scale Diseconomies of Scale Best Operating Level Annual Volume (units)

Larger Plants Tend to Have Higher Optimal Output Rates Figure 5.4 Minimum cost & optimal operating rate are functions of size of production unit. Small plant Average cost per unit Medium plant Large plant Output rate

Evaluating Alternatives Cost-volume analysis Break-even point Financial analysis Cash flow Present value Decision theory Waiting-line analysis Simulation

Assumptions of Cost-Volume Analysis One product is involved Everything produced can be sold Variable cost per unit is the same regardless of volume Fixed costs do not change with volume Revenue per unit constant with volume Revenue per unit exceeds variable cost per unit

Cost-Volume Relationships Figure 5.5a Amount ($) Q (volume in units) Total cost = VC + FC Total variable cost (VC) Fixed cost (FC)

Cost-Volume Relationships Figure 5.5b Amount ($) Q (volume in units) Total revenue

Cost-Volume Relationships Figure 5.5c Amount ($) Q (volume in units) BEP units Profit Total revenue Total cost

Break-Even Problem with Step Fixed Costs Figure 5.6a Quantity FC + VC = TC Step fixed costs and variable costs. 1 machine 2 machines 3 machines

Break-Even Problem with Step Fixed Costs Figure 5.6b $ TC BEP 2 3 TR Quantity 1 Multiple break-even points

Example 4: page 195 A manager has the option of purchasing one, two, or three machines. # of mach. Tot. Annual FC Correspond. Output 1 $9600 0 – 300 2 15000 301 - 600 3 20000 601 – 900 Variable cost is $10, revenue is $40 per unit. Determine the break-even point for each range. If projected demand is between 580 and 660 units, how many machines should the manager purchase?

Example 2 a) For one machine Q = 9600/(40-10)= 320 units For two machines Q= 15000/(40-10)= 500 units For three machines Q=20000/(40-10)=666.67 units b) Manager should choose two machines. Because even if demand is at low end of the range (i.e., 580), it would be above the break-even point and thus yield a profit. If three machines are purchased, even at the top end of projected demand (i.e., 660), the volume would still be less than the break-even point for that range, so there would be no profit.

Financial Analysis Cash Flow - the difference between cash received from sales and other sources, and cash outflow for labor, material, overhead, and taxes. Present Value - the sum, in current value, of all future cash flows of an investment proposal.

Decision Tree Analysis Structures complex, multiphase decisions Allows objective evaluation of alternatives Incorporates uncertainty Develops expected values

Example: Decision Tree Analysis Good Eats Café is about to build a new restaurant. An architect has developed three building designs, each with a different seating capacity. Good Eats estimates that the average number of customers per hour will be 80, 100, or 120 with respective probabilities of 0.4, 0.2, and 0.4. The payoff table showing the profits for the three designs is on the next slide.

Example: Decision Tree Analysis Payoff Table Average Number of Customers Per Hour c1 = 80 c2 = 100 c3 = 120 Design A $10,000 $15,000 $14,000 Design B $ 8,000 $18,000 $12,000 Design C $ 6,000 $16,000 $21,000

Example: Decision Tree Analysis Expected Value For Each Decision Choose the design with largest EV -- Design C. EV = .4(10,000) + .2(15,000) + .4(14,000) = $12,600 d1 2 Design A EV = .4(8,000) + .2(18,000) + .4(12,000) = $11,600 Design B d2 1 3 d3 Design C EV = .4(6,000) + .2(16,000) + .4(21,000) = $14,000 4

Waiting-Line Analysis Useful for designing or modifying service systems Waiting-lines occur across a wide variety of service systems Waiting-lines are caused by bottlenecks in the process Helps managers plan capacity level that will be cost-effective by balancing the cost of having customers wait in line with the cost of additional capacity