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Capacity Planning For Products and Services. Learning Objectives  Explain the importance of capacity planning.  Discuss ways of defining and measuring.

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Presentation on theme: "Capacity Planning For Products and Services. Learning Objectives  Explain the importance of capacity planning.  Discuss ways of defining and measuring."— Presentation transcript:

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 1.Impacts ability to meet future demands 2.Affects operating costs 3.Major determinant of initial costs 4.Involves long-term commitment 5.Affects competitiveness 6.Affects ease of management 7.Globalization adds complexity 8.Impacts long range planning Importance of Capacity Decisions

5 Capacity  Design capacity  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 Actual output Utilization = Design capacity Both measures expressed as percentages (%)

7 Actual output = 36 units/day Efficiency = = 90% Effective capacity 40 units/ day Utilization = Actual output = 36 units/day = 72% Design capacity 50 units/day Efficiency/Utilization Example Design capacity = 50 trucks/day Effective capacity = 40 trucks/day Actual output = 36 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 1.Amount of capacity needed Capacity cushion (100% - Utilization) 2.Timing of changes 3.Need to maintain balance of the system 4.Extent of flexibility of facilities and workforce Capacity cushion – extra demand intended to offset uncertainty

11 Steps for Capacity Planning 1.Forecast future capacity requirements 2.Evaluate existing capacity 3.Identify alternatives 4.Conduct financial analysis 5.Assess key qualitative issues 6.Select one alternative 7.Implement alternative chosen 8.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 Annual capacity = 2000 hours Machine required to handle these job = 5,800 /2,000 = 2.90 Machine required to handle these job = 3 machines Working 8-hour shift, 250 day/year

14  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 Planning Service Capacity

15 In-House or Outsourcing (Make or Buy) 1.Available capacity 2.Expertise 3.Quality considerations 4.Nature of demand 5.Cost 6.Risk

16 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 (to focus bottleneck) 4.Prepare to deal with capacity “chunks” 5.Attempt to smooth out capacity requirements 6.Identify the optimal operating level (economy of scale)

17 Product Life Cycle 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 IntroductionGrowthMaturityDecline Company Strategy/Issues Internet Flat-screen monitors Sales DVD CD-ROM Drive-through restaurants Fax machines 3 1/2” Floppy disks Color printers

18 Product Life Cycle Product design and development critical Frequent product and process design changes Short production runs High production costs Limited models Attention to quality IntroductionGrowthMaturityDecline OM Strategy/Issues 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 #2 Bottleneck Operation Bottleneck Operation Machine #1 Machine #3 Machine #4 10/hr 30/hr Bottleneck operation: An operation in a sequence of operations whose capacity is lower than that of the other operations 30/hr

20 Bottleneck Operation Operation 1 20/hr. Operation 2 10/hr. Operation 3 15/hr. 10/hr. Bottleneck Maximum output rate limited by bottleneck

21 Optimal Rate of Output Minimum cost Average cost per unit 0 Rate of output Production units have an optimal rate of output for minimal cost. Minimum average cost per unit

22 Economies of Scale  Economies 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 Minimum cost & optimal operating rate are functions of size of production unit. Average cost per unit 0 Small plant 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 ($) 0 Q (volume in units) Total cost = VC + FC Total variable cost (VC) Fixed cost (FC)

26 Cost-Volume Relationships Amount ($) Q (volume in units) 0 Total revenue

27 Cost-Volume Relationships Amount ($) Q (volume in units) 0 BEP units Profit Total revenue Total cost 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 $ TC BEP 2 3 TR Quantity Multiple break-even points

30 1.One product is involved 2.Everything produced can be sold 3.Variable cost per unit is the same regardless of volume 4.Fixed costs do not change with volume 5.Revenue per unit constant with volume 6.Revenue per unit exceeds variable cost per unit Assumptions of Cost-Volume Analysis

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

35  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 Decision Theory Elements

36  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 Decision Theory Process

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

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

39 Decision Process 1.Identify the problem 2.Specify objectives and criteria for a solution 3.Develop suitable alternatives 4.Analyze and compare alternatives 5.Select the best alternative 6.Implement the solution 7.Monitor to see that the desired result is achieved

40  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 Decision Environments

41 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 Decision Making under Uncertainty

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 State of nature 2 2 Payoff 4 Payoff 5 Choose A’ 3 Choose A’ 4 State of nature 1 Choose A’ Choose A’ 2 1 Decision Point Chance Event

45 Example of a Decision Tree Low demand (0.4) B 40M High demand (0.6) 40M 55M 2 Do nothing Expand 70M High demand (0.6) 2 10M 50M Do nothing Reduce price Low demand (0.4) 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 AlternativeA 412 B16 2 C12 8 จงเขียนภาพแสดง Sensitivity

49 Sensitivity Analysis A B C A bestC bestB best #1 Payoff#2 Payoff Sensitivity analysis: determine the range of probability for which an alternative has the best expected payoff


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