Managing Capacity

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 2 Capacity Decisions Defining and measuring capacity Strategic versus tactical capacity Evaluating capacity alternatives Advanced perspectives –Learning curves –Waiting lines

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 3 Measure of an organization’s ability to provide goods or services Jiffy Lube  Oil changes per hour Law firm  Billable hours College  Student hours per semester Defining and Measuring Capacity

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 4 Consider: Capacity for a PC Assembly Plant: (800 units/shift/line) × (% Good) × (# of lines) × (# of Shifts) 1 or 2 shifts? 2 or 3 lines? Employee training? Controllable Factors Uncontrollable Factors Supplier problems? 98% or 100% good?

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 5 Strategic versus Tactical Capacity Strategic: –One or more years out –“Bricks & Mortar” –Future technologies Tactical: –One year or sooner –Workforce level, inventory, etc.

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 6 Capacity Time Strategic Capacity Planning “Bricks & mortar” decisions High-level planning High risk Tactical Planning Workforce, inventory, subcontracting decisions Intermediate-level planning Moderate risk Planning & Control Limited ability to adjust capacity Detailed planning Lowest risk Days or weeks outMonths out Years out Capacity versus Time

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 7 Capacity Strategies: When, How Much, and How? Leader Laggard Demand Lost Business Excess Capacity

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 8 How? Make or Buy (e.g., subcontracting) One extreme: “Virtual” Business Walden Paddlers (Marketing) Hardigg Industries (Manufacturing) General Composites (Design) Independent Dealers (Direct Sales)

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 9 Evaluating Capacity Alternatives Economies of scale (EOS) Break-even points (BEP) Expected value analysis (EVA)

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 10 Economies of Scale Total Cost for Fictional Line: Fixed cost + (Variable unit cost)×(X) = $200,000 + $4X Cost per unit for X=1? X=10,000?

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 11 Fixed - Unit Cost Scenarios

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 12 Break-Even Point (BEP) Considers revenue and costs Suppose each unit sells for $100: BEP  $100X = $200,000 + $4X What is the breakeven volume, X?

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 10, Slide 13 Expected Value Analysis

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 14 Data Requirements Capacity cost structure (alternatives?) Expected demand (multiple scenarios?) Product and service requirements (e.g. time standards) EVA

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 15 Expected Value Analysis Pennington Cabinet Company 2000 jobs per year (20% likelihood) 5000 jobs per year (50%) 7000 jobs per year (30%) Each job = $1,200 revenue

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 16 We Know: Average job requires: 2 hours of machine time 3-1/3 hours of assembly team time Machines and teams work 2000 hours per year Each machine and team has yearly fixed cost = $200K 3 different capacity scenarios (see next page!)

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 17 Effective Capacity What is the effective capacity of each capacity alternative? Number of Machines and Teams Number of Hours Available Each Year Maximum Jobs per Year MachinesTeamsMachinesTeamsMachinesTeams Current356,00010,0003,000 Expanded5910,00018,0005,0005,400 New Site71214,00024,0007,0007,200

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 18 Alternate Demand Scenarios What is the expected contribution if demand = 5000 AND we decide to move to a new site? Why does revenue for current capacity max out at $3.6 million? Current LevelExpandedNew Site DemandRevenue Fixed ExpensesRevenue Fixed ExpensesRevenue Fixed Expenses 2,000$2,400,000$1,600,000$2,400,000$2,800,000$2,400,000$3,800,000 5,000$3,600,000$1,600,000$6,000,000$2,800,000$6,000,000$3,800,000 7,000$3,600,000$1,600,000$6,000,000$2,800,000$8,400,000$3,800,000

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 19 Net Revenue Table DemandCurrentExpandedNew Site 3,000$800,000$400,000$1,400,000 5,000$2,000,000$3,200,000$2,200,000 7,000$2,000,000$3,200,000$4,600,000

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 20 Expected Value of Each Capacity Alternative: Current capacity level (20%) × $800K +(50%) × $2000K +(30%) × $2000K =$1,760,000

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 21 Expanded capacity level (20%) × - 400K +(50%) × $3200K + (30%) × $3200K =$2,480,000

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 22 New Site capacity level (20%) × - $1400K +(50%) × $2200K +(30%) × $4600K =$2,200,000

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 23 Conclusions for Pennington Which alternative would you choose if you wanted to minimize the worst possible outcome (Maximin)? Maximize the best possible outcome (Maximax)? Why is it important to know effective capacity? How could this help future capacity decisions?

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 24 Self Test EBB Industries must decide whether to invest in a new machine which has a yearly fixed cost of $40,000 and a variable cost of $50 per unit. What is the break even point (BEP) if each unit sells for $200? What is the expected value, given the following demand probabilities: 250 units (25%), 300 units (50%), 350 units (25%)

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 10, Slide 25 Advanced Perspectives Learning curves Waiting lines

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 10, Slide 26 Question? How can capacity change, even when we do not hire new people or put in new equipment?

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 27 Learning Curves Recognize that people (and often equipment) become more productive over time due to learning. First observed in aircraft production during World War II Getting more emphasis as companies outsource more activities

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 28 A Formal Definition For every doubling of cumulative output, there will be a set percentage improvement in time per unit or some other measure of input Output Time per unit 10 hrs. 8 hrs. 6.4 hrs hrs hrs. 80% learning curve - Where does the name come from?

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 29 A Formal Definition (cont’d) Where:T n = time for the nth unit T 1 = time for the first unit b = ln × (learning percent) / ln2

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 30 Example Reservation clerk at Delta Airlines First call (while training) takes 8 minutes Second call takes 6 minutes What is the learning rate? How long would you expect the 4th call to take? The 16th? The 64th?

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 31 Key Points Quick improvements early on, followed by more and more gradual improvements The lower the percentage, the steeper the learning curve Practically speaking, there is a floor Estimates of effective capacity must consider learning effects!

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 10, Slide 32 Another Question... How could learning curves be used in long-term purchasing contracts?

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 33 Johnston Controls I Johnston Controls won a contract to produce 2 prototype units for a new type of computer. First unit took 5,000 hrs. to produce and $250K of materials Second unit took 3,500 hrs. to product and $200K of materials Labor costs are $30/hour

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 34 Johnston Controls II The customer has asked Johnston Controls to prepare a bid for an additional 10 units. What are Johnston’s expected costs?

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 35 Johnston Controls III Labor learning rate: 3500 hours / 5000 hours = 70% Materials learning rate: $200K / $250K = 80%

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 36 Johnston Controls IV “Additional 10 units” means the third through twelfth units. Total labor for units 3 through 12: =5,000 hours × (5.501 – 1.7) = 19,005 hrs is sum of n b for 12 units 1.7 is the sum of n b for the first two units

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 37 Johnston Controls V Total material for units 3 through 12: = $250,000 × (7.227 – 1.8) = $1,356,750

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 38 Johnston Controls (cont’d) Total cost for “additional 10 units”: = $30 × (19,005 hours) + $1,356,750 = $1,926,900 What if there is a significant delay before the second contract?

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 39 Self-Test Assume that there WILL BE a significant delay before Johnston Controls makes the next 10 units. Assuming that Johnston has to “start over” with regard to learning, estimate total cost for this additional 10 units.

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 40 Waiting Lines Waiting lines and services –Waiting and customer satisfaction –Factors affecting satisfaction Waiting Line Theory –Terminology and assumptions – Illustrative example

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 41 Waiting at Outback Steakhouse... Waiting to get food... Waiting to pay bill... Leaving restaurant Waiting outside or in bar

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 42 Key Points Waiting time DECREASES value- added experience On the other hand, adding serving capacity INCREASES costs Businesses must have a way to analyze the impact of capacity decisions in environments where waiting occurs

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 43 Waiting and Customer Satisfaction Cost of waiting Cost of service COST Waiting time Lost customers

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 44 Cost of Waiting = f(Satisfaction) Factors Affecting Satisfaction 1.Firm-related factors 2.Customer-related factors

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 45 Firm-Related Factors “Unfair” versus “fair” waits Uncomfortable versus comfortable waits Initial versus subsequent waits Capacity decisions

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 46 Waiting Line (Queuing) Theory Applied statistics to allow us to perform a detailed analysis of system –Utilization levels, line lengths, etc. Terminology and assumptions

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 47 Terminology and Assumptions I

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 48 Terminology and Assumptions II Single Channel Single Phase Multi-Channel Single Phase

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 49 Terminology and Assumptions III Complex service environment... How would you describe this?

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 50 Terminology and Assumptions IV Population: Infinite or Finite Arrival rates:Random or constant rate –Random rates typically defined by Poisson distribution for infinite population Service Rates: Random or constant –Random service rates typically described by exponential distribution Dispatching rules (aka “Queue Discipline”) Permissible queue length

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 51 Example A single drive-in window for Bank Arrival rate –15 per hour, on average Service rate –20 per hour, on average How many channels? Phases? What kinds of questions might we have?

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 52 Drive-In Bank = arrival rate = 15 cars per hour  = service rate =20 cars per hour Average number of cars being served:  =  = 0.75

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 53 Drive-In Bank Probability of n arrivals during period T is: E.g., probability of 4 arrivals during a 45 minute period is:

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 54 Drive-In Bank Average number of cars in the system: (waiting plus being served)

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 55 Drive-In Bank Average number of cars waiting:

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 56 Drive-In Bank Average time spent in the system: (waiting plus being served) (How do we know the answer is in hours?)

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 57 Drive-In Bank Average time spent in the line: (How do we know the answer is in hours?)

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 10, Slide 58 Question? What happens as the arrival rate approaches the service rate? Suppose is now 19 cars per hour

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 59 One Answer: Average number of cars waiting: Implications? What are we assuming here?

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 60 Other Types of Systems Single-channel, single-phase with constant service time –Example: Automatic car wash Multi-channel, multi-phase (hospital) –Usually best handled using simulation analysis

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 61 Self Test I Look back at the drive-in window example. How can we have an average line length > 1 while the average number of cars being served is < 1? Similarly, what happens as the arrival rate approaches the service rate? Suppose the teller at the drive-in window is given training and can now handle 25 cars an hour (a 25% increase). What happens to the average length of the line?

©2006 Pearson Prentice Hall — Introduction to Operations and Supply Chain Management — Bozarth & Handfield Chapter 8, Slide 62 Self Test II Look back at the Outback Steakhouse example. What kind of queuing system is it?