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Capacity Planning For Products and Services

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1 Capacity Planning For Products and Services

2 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

3 Capacity Planning Capacity is the upper limit or ceiling on the load that an operating unit can handle. Capacity also includes Equipment Space Employee skills The basic questions in capacity handling are: What kind of capacity is needed? How much is needed? When is it needed?

4 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

5 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.

6 Efficiency and Utilization
Actual output Efficiency = Effective capacity Utilization = Design capacity Both measures expressed as percentages (%)

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

8 Determinants of Effective Capacity
Facilities (design, location, layout, environment) Product and service factors (design, product mix) Process factors (quantity capacity, quality capacity) Human factors (job content, job design, training & experience, motivation, compensation, learning rate, absenteeism and turnover) Policy factors Operational factors (scheduling, materials management, QA, maintenance, breakdown) Supply chain factors External factors (standard, safety regulation, unions, pollution control standard)

9 Strategy Formulation Capacity strategy for long-term demand patterns involve; Growth rate and variability of demand Cost of building and operating facilities of various size Rate and direction of technology changes Behavior of competitors Availability of capital and other inputs

10 Key Decisions of Capacity Planning
Amount of capacity needed Capacity cushion (100% - Utilization) Timing of changes Need to maintain balance of the system Extent of flexibility of facilities and workforce Capacity cushion – extra demand intended to offset uncertainty

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

12 Forecasting Capacity Requirements
Long-term vs. short-term capacity needs Long-term relates to overall level of capacity such as facility size, trends, and cycles Short-term relates to variations from seasonal, random, and irregular fluctuations in demand

13 Calculating Processing Requirements
Working 8-hour shift, 250 day/year Annual capacity = 2000 hours Machine required to handle these job = 5,800 /2,000 = 2.90 Machine required to handle these job = 3 machines

14 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

15 In-House or Outsourcing (Make or Buy)
Available capacity Expertise Quality considerations Nature of demand Cost Risk

16 Developing Capacity Alternatives
Design flexibility into systems Take stage of life cycle into account Take a “big picture” approach to capacity changes (to focus bottleneck) Prepare to deal with capacity “chunks” Attempt to smooth out capacity requirements Identify the optimal operating level (economy of scale)

17 Company Strategy/Issues Drive-through restaurants
Product Life Cycle Introduction Growth Maturity Decline Company Strategy/Issues Best period to increase market share R&D engineering is critical Practical to change price or quality image Strengthen niche Poor time to change image, price, or quality Competitive costs become critical Defend market position Cost control critical Internet Flat-screen monitors Sales DVD CD-ROM Drive-through restaurants Fax machines 3 1/2” Floppy disks Color printers

18 Product Life Cycle Introduction Growth Maturity Decline
OM Strategy/Issues Product design and development critical Frequent product and process design changes Short production runs High production costs Limited models Attention to quality Forecasting critical Product and process reliability Competitive product improvements and options Increase capacity Shift toward product focus Enhance distribution Standardization Less rapid product changes – more minor changes Optimum capacity Increasing stability of process Long production runs Product improvement and cost cutting Little product differentiation Cost minimization Overcapacity in the industry Prune line to eliminate items not returning good margin Reduce capacity

19 Bottleneck Operation Machine #1 Machine #2 Bottleneck Operation
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 30/hr Machine #2

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

21 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

22 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 Diseconomies of scale If the output rate is more than the optimal level, increasing the output rate results in increasing average unit costs

23 Economies of Scale Small Medium plant Large plant Output rate
Minimum cost & optimal operating rate are functions of size of production unit. Small plant Average cost per unit Medium plant Large plant Output rate

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

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

26 Cost-Volume Relationships
Total revenue Amount ($) Q (volume in units)

27 Cost-Volume Relationships
Profit Total revenue Amount ($) Total cost BEP units Q (volume in units) BEP = Break Even Point

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

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

30 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

31 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.

32 Decision Theory Helpful tool for financial comparison of alternatives under conditions of risk or uncertainty Suited to capacity decisions

33 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

34 Product and service design
Decision Theory Decision Theory represents a general approach to decision making which is suitable for a wide range of operations management decisions, including: Capacity planning Product and service design Location planning Equipment selection

35 Decision Theory Elements
A set of possible future conditions exists that will have a bearing on the results of the decision A list of alternatives for the manager to choose from A known payoff for each alternative under each possible future condition

36 Decision Theory Process
Identify possible future conditions called states of nature Develop a list of possible alternatives, one of which may be to do nothing Determine the payoff associated with each alternative for every future condition If possible, determine the likelihood of each possible future condition Evaluate alternatives according to some decision criterion and select the best alternative

37 Causes of Poor Decisions
Bounded Rationality The limitations on decision making caused by costs, human abilities, time, technology, and availability of information

38 Causes of Poor Decisions (Cont’d)
Suboptimization The result of different departments each attempting to reach a solution that is optimum for that department

39 Decision Process Identify the problem
Specify objectives and criteria for a solution Develop suitable alternatives Analyze and compare alternatives Select the best alternative Implement the solution Monitor to see that the desired result is achieved

40 Decision Environments
Certainty - Environment in which relevant parameters have known values Risk - Environment in which certain future events have probable outcomes Uncertainty - Environment in which it is impossible to assess the likelihood of various future events

41 Decision Making under Uncertainty
Maximin - Choose the alternative with the best of the worst possible payoffs Maximax - Choose the alternative with the best possible payoff Laplace - Choose the alternative with the best average payoff of any of the alternatives Minimax Regret - Choose the alternative that has the least of the worst regrets

42 Decision Making Under Risk
Risk: The probability of occurrence for each state of nature is known Risk lies between the extremes of uncertainty and certainty Expected monetary value (EMV) criterion: The best expected value among alternatives Determine the expected payoff of each alternative, and choose the alternative with the best expected payoff

43 Decision Trees Decision tree: a Schematic representation of the available alternatives and their possible consequences. Useful for analyzing situations that involve sequential decisions

44 Format of a Decision Tree
State of nature 1 B Payoff 1 State of nature 2 Payoff 2 Payoff 3 2 Choose A’1 Choose A’2 Payoff 6 Payoff 4 Payoff 5 Choose A’3 Choose A’4 Choose A’ 1 Decision Point Chance Event

45 Example of a Decision Tree
Low demand (0.4) B 40M High demand (0.6) 55M 2 Do nothing Expand 70M 10M 50M Reduce price Build small Build large 1 Decision Point Chance Event Overtime 50M

46 Expected Value of Perfect Information
Expected value of perfect information: the difference between the expected payoff under certainty and the expected payoff under risk Expected value of perfect information Expected payoff under certainty Expected payoff under risk - =

47 Sensitivity Analysis Sensitivity Analysis: Determining the range of probability for which an alternative has the best expected payoff Useful for decision makers to have some indication of how sensitive the choice of an alternative is to changes in one or more of these values

48 Example ตารางแสดง Payoff ของแต่ละทางเลือก State of nature #1 #2
#1 #2 Alternative A B C จงเขียนภาพแสดง Sensitivity

49 Sensitivity Analysis A B C A best C best B best #1 Payoff #2 Payoff 16 14 12 10 8 6 4 2 16 14 12 10 8 6 4 2 Sensitivity analysis: determine the range of probability for which an alternative has the best expected payoff

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