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The Hierarchy of Production Decisions

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0 Long-Range Capacity Planning

1 The Hierarchy of Production Decisions
The logical sequence of operations in factory planning corresponds to the sequence of chapters in a text-book with title «Production and Operations Management». 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.

2 Hierarchy of Production Decisions
Long-range Capacity Planning

3 Capacity Definitions Capacity is a statement of the rate of producing output and is generally measured as the output of the process per unit period of time. Capacity essentially limits the rate of output possible. The Load represents the work released and planned for the process for a given period of time. Think the load being the amount of water in a tank and the capacity being the rate at which the water can be drained from the tank.

4 Capacity Planning Capacity planning is the process of reconciling the difference between the capacity available for the process and the capacity required to satisfy the customer order which represents the load. In capacity planning, it is important to adjust the capacity to meet the load in order to maintain a high level of customer service. Critical elements of capacity to be planned include labor, machine hours, facilities and warehouse space.

5 Capacity Planning A major function of capacity planning is to match the capacity of the machine or facility with the demand for the products of the firm. Capacity planning can be classified into three planning horizons: Long range Medium range Short range

6 Long-Term Capacity Planning
The long range planning generally considers planning horizons of one year or longer. A time period of one year or longer is needed to provide sufficient time to build a new facility, to expand the existing facility or to move to a new facility due to forecasted changes in demand. We determine long-term capacity needs by forecasting demand over a time horizon and then converting those forecasts into capacity requirements Long-term considerations relate to overall level of capacity, such as facility size (affected by trends and cycles)

7 Medium-term capacity Planning
Medium range capacity planning horizon ranges approximately from one month to six months. At this level of planning, decisions or activities include acquisition of a major piece of machinery and subcontracting.

8 Short-term Capacity Planning
Short range planning horizon covers capacity planning activities on a daily or a weekly basis and are generated as a result of disaggregation of the long or medium range capacity plans. These activities include machine loading and detailed production scheduling.

9 Short-term Capacity Planning
Short-term considerations relate to probable variations in capacity requirements created by such things as seasonal, random, and irregular fluctuations in demand When time intervals are too short to have a seasonal variations in demand, a probability distribution such as Normal, Uniform, Poisson can be used to forecast the demand.

10 Questions to be answered in Long-Range Capacity Planning
How much long-range production capacity is needed? - adding too much capacity means the capacity will be underutilized. - adding too little capacity means that the comapany will soon be faced with the problem of increasing capacity again. When additional capacity is needed? - It is important to pay attention to changing patterns of demand.

11 Questions to be answered in Long-Range Capacity Planning
Where the production facilities should be located? - Consideration of the logistics of material flows suggests that new facilities be located near suppliers of raw materials and market outlets. How the production facilities are arranged? Facility layout decisions affect the production rates.

12 Importance of Capacity Decisions
Capacity limits the rate of output possible. Poor capacity decisions which result in over and under capacity increase the operating costs. Capacity decisons often require long-term commitment of resources so that once they are implemented, it may be difficult to modify those decisions without incurring major costs.

13 Importance of Capacity Decisions
Capacity decisons are major determinant of initial costs. Capacity decisons affect competitiveness. Companies having appropriate capacity can deliver the products faster than competitors (delivery speed).

14 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.

15 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.

16 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.

17 Steps in the Capacity Planning Process
1. Estimate the capacity of the present facilities. 2. Forecast the long-range future capacity needs by taking into consideration demand patterns(i.e., trends, cycles). 3. Identify and analyze ways of changing long-range capacity For Capacity Expansion: Subcontract, Acquire other companies, Develop new sites, buy new equipment, Expand current sites, Reactivate standby facilities For Capacity Reduction: Sell off existing facilities, Sell inventories and Lay off employees 4. Select from among the alternative sources of capacity changing plans.

18 Measurements of Capacity
Output rate capacity - for a single product or a few homogeneous products (TV sets per month, number of cars per shift) Aggregate capacity - using a common unit of output if many different products are produced ( sales dollars per month, tons of steel per day) Input rate capacity - for service operations (hospitals use available beds per month, airlines use available seats per day)

19 Measurements of Capacity
Design Capacity: Maximum output that can possibly be attained under ideal conditions Effective Capacity: It is usually less than design capacity (it can not exceed design capacity) due to the realities of changing product mix, scheduling difficulties, periodic machine maintenance, lunch and coffee breaks Actual output: The rate of output actually achieved. It can not exceed effective capacity and is often less than effective capacity due to breakdowns, absenteesim, defective output, shortages of materials and so on. (These problems are outside the control of the operations managers)

20 Measurements of Capacity
These different measures of capacity are useful in defining two measures of system effectiveness: ---- efficiency ---- utilization Efficiency=Actual Output / Effective Cap. Utilization=Actual Output / Design Cap.

21 Measurements of Capacity
It is common for managers to focus exclusively on efficiency, but often this might be misleading. This happens when effective capacity is low compared with design capacity. In those cases, high efficiency would seem to indicate effective use of resources when it does not. The following example illustrates this point.

22 EXAMPLE Given the information below, compute the efficiency and utilization of the vehicle repair department: Design capacity = 50 trucks/day Effective capacity= 40 trucks/day Actual output = 36 trucks/day Efficiency= 36/40=90% Utilization= 36/50=72% When effective capacity is low compared with design capacity, to focus exclusively on efficiency can be misleading. And you should note that increasing utilization depends on being able to increase effective capacity. This requires a knowledge of what is constraing effective capacity.

23 Determinants of Effective Capacity
Facilities - Location (transportation cost, distance, labor supply) - Design (room for expansion) - Layout (material transfer, line balance) Product/service - Design (similar products standardization)

24 Determinants of Effective Capacity
Process - Quantitiy capabilities (productivity, using automated machines) - Quality capabilities (the more time spent for inspection and rework the less capacity) Human Factors - job content - training and experience - motivation - absenteeism and labor turnover

25 Determinants of Effective Capacity
Operational Factors - scheduling - materials management - quality assurance - maintenance policies - equipment breakdowns External Factors - Pollution control standards - Unions (limit the number of working hours)

26 Factors which influence the frequency of capacity decisions
Stability of demand The rate of technological change in equipment The rate of technological change in product design The rate of technological change in competitive factors

27 A Strategy For Demand Management: Capacity Cushion
Capacity cushion is an additional amount of capacity added onto the expected demand. Capacity cushion Helps to meet excess demand during peak demand seasons Lowers production costs Provides product and volume flexibility Improves quality of products and services

28 Developing Capacity Alternatives
Design flexibility into systems by taking into consideration of water lines, power hookups, waste disposal lines for future expansion Take a “big picture” approach to capacity changes (increasing number of rooms will lead to increasing demand for parking) 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.

29 4. Attempt to smooth out capacity requirements
Unevenness in capacity requirements also can create certain problems.

30 5. Take stage of life cycle into account

31 6. Identify the optimal operating level
Average Unit Cost of Output ($) Economies of Scale Diseconomies of Scale Best Operating Level Annual Volume (units)

32 Economies of Scale Best operating level - least average unit cost
Economies of scale - If the output rate is less than the optimal level, increasing output rate results in decreasing average unit costs. Declining costs up to the best operating level result from fixed costs, labor cost being spread over more units Average cost per unit decreases as the volume increases.

33 Diseconomies of scale Diseconomies of scale –
If the output rate is more than the optimal level, increasing the output rate results in increasing average unit costs. Average cost per unit increases as the volume increases due to scheduling problems, quality problems, reduced morale, increased use of overtime

34 Expanding capacity all at once or incrementally
Another important issue in capacity planning is: Choosing between expanding capacity all at once (better for mature products having stable and predictable demand) or incrementally (better for new products)

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

36 Planning Service Capacity
Three important factors in planning servive capacity are: Inability to store services Need to be near customers Capacity and location are closely tied Capacity must be matched with timing of demand Degree of volatility of demand Peak demand periods

37 Analyzing Capacity-Planning Decisions
Decision Tree Analysis Cost-Volume Analysis Present-Value Analysis Computer Simulation Waiting Line Analysis Linear Programming

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

39 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 The payoff table showing the profits for the three designs is on the next slide.

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

41 Example: Decision Tree Analysis
Expected Value Approach Calculate the expected value for each decision. The decision tree on the next slide can assist in this calculation. Here d1, d2, d3 represent the decision alternatives of designs A, B, C, and c1, c2, c3 represent the different average customer volumes (80, 100, and 120) that might occur.

42 Example: Decision Tree Analysis
Payoffs c1 .4 10,000 c2 .2 2 15,000 c3 .4 d1 14,000 c1 .4 8,000 d2 1 3 c2 .2 18,000 d3 c3 .4 12,000 c1 .4 6,000 4 c2 .2 16,000 c3 .4 21,000

43 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

44 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 is constant Revenue per unit exceeds variable cost per unit

45 Example 1: Cost-Volume Analysis
The owner of Old-Fashioned Berry Pies, S. Simon, is contemplating adding a new line of pies, which will require leasing new equipment for a monthly payment of $6000. Variable cost would be $2 per pie and pies would retail $7 each. a) How many pies must be sold in order to break even? b) What would the profit(loss) be if 1000 pies are made and sold in a month? c) How many pies must be sold to realize a profit of $4000?

46 Example 1 Q = FC/(p-v)=6000/(7-2)=1200 pies/month
Profit(or Loss)=7*1000-(6000+2*1000) = -$1000 (Loss) 4000 = 7Q – (6000+2Q) Q=2000 pies

47 Example 2: Cost-Volume Analysis
A manager has the option of purchasing one, two, or three machines. # of mach Tot. Annual FC Correspond. Output $ – 300 – 900 Variable cost is $10, revenue is $40 per unit. Determine the break-even poinf for each range. If projected demand is between 580 and 660 units, how many machines should the manager purchase?

48 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)= 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.

49 A Capacity Planning Strategy: Make or Buy
Once capacity requirements have been determined, the company must decide whether to produce the product or buy (outsource) it from another company. The company can purchase the product from an outside source for c1 dollar per unit, but can produce internally for a lower unit price , c2<c1. However in order to produce the product internally, the company invest $K to expand production capacity. Which strategy should the company adopt?

50 Make or Buy: Capacity Expansion Problem

51 The factors which affect make or buy decisions are:
Available capacity Expertise Quality considerations Nature of demand Cost Risk

52 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.

53 Example A large international computer manufacturer is designing a new model of personal computer and must decide whether to produce the keyboards internally or to purchase them from an outside supplier. The supplier is willing to sell the keyboards for $50 each, but the manufacturer estimates that his firm can produce the keyboards for $35 each. Management estimates that expanding the current plant and purchasing the necessary equipment to make the keyboards would cost $8 million. Should they undertake the expansion? The break-even quantity is: X= /(50-35)= So the company would have to sell at least keyboards in order to justify the $8 million investment required for expansion.

54 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


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