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1. Capacity and Constraint Management Lesson 3

2. LEARNING OUTCOMES: 1. Define capacity. 2. Determine design capacity, effective capacity and utilization. 3. Perform bottleneck analysis.

3. Capacity refers to an upper limit or ceiling on the load that an operating unit can handle. The load might be in terms of the number of physical units produced (e.g., bicycles assembled per hour) or the number of services performed (e.g., computers upgraded per hour).

4. The operating unit might be a plant, department, machine, store, or worker. Capacity needs include equipment, space, and employee skills.

5. Capacity planning is a key strategic component in designing the system.

6. The key questions in capacity planning are the following: 1. What kind of capacity is needed? 2. How much is needed to match demand? 3. When is it needed?

7. CAPACITY DECISIONS ARE STRATEGIC Capacity decisions have a real impact on the ability of the organization to meet future demands for products and services; capacity essentially limits the rate of output possible. Capacity decisions affect operating costs. Capacity is usually a major determinant of initial cost.

8. Capacity decisions often involve long-term commitment of resources and the fact that, once they are implemented, those decisions may be difficult or impossible to modify without incurring major costs. Capacity decisions can affect competitiveness. Capacity affects the ease of management; having appropriate capacity makes management easier than when capacity is mismatched.

9. Globalization has increased the importance and the complexity of capacity decisions. Because capacity decisions often involve substantial financial and other resources, it is necessary to plan for them far in advance.

10. DEFINING AND MEASURING CAPACITY T wo useful definitions of capacity: 1. Design capacity : The maximum output rate or service capacity an operation, process, or facility is designed for in a normal period under ideal conditions. - Normally expressed as a rate 2. Effective capacity : Design capacity minus allowances such as personal time, and maintenance. - The capacity a firm can expect to achieve, given its product mix, methods of scheduling, maintenance, and standards of quality. - Often lower than design capacity

11. Design and Effective Capacity TABLE S7.1 Capacity Measurements MEASURE DEFINITION EXAMPLE Design capacity Ideal conditions exist during the time that the system is available Machines a t Frito-Lay are designed to produce 1,000 bags of chips/hr., and the plant operates 16 hrs./day. Design Capacity = 1,000 bags/hr. × 16 hrs. = 16,000 bags/day

12. Design and Effective Capacity TABLE S7.1 Capacity Measurements MEASURE DEFINITION EXAMPLE Effective capacity Design capacity minus lost output because of planned resource unavailability (e.g., preventive maintenance, machine setups/changeovers, changes in product mix, scheduled breaks) Frito-Lay loses 3 hours of output per day (= 0.5 hrs./day on preventive maintenance, 1 hr./day on employee breaks, and 1.5 hrs./day setting up machines for different products). Effective Capacity = 16,000 bags/day – (1,000 bags/hr.) (3 hrs./day) = 16,000 bags/day – 3,000 bags/day = 13,000 bags/day

13. Design and Effective Capacity TABLE S7.1 Capacity Measurements MEASURE DEFINITION EXAMPLE Actual output Effective capacity minus lost output during unplanned resource idleness (e.g., absenteeism, machine breakdowns, unavailable parts, quality problems) On average, machines at Frito-Lay are not running 1 hr./day due to late parts and machine breakdowns. Actual Output = 13,000 bags/day – (1,000 bags/hr.) (1 hr./day) = 13,000 bags/day – 1,000 bags/day = 12,000 bags/day

14. The different measures of capacity are useful in defining two measures of system effectiveness: efficiency and utilization . Efficiency is the ratio of actual output to effective capacity. Capacity utilization is the ratio of actual output to design capacity .

15. Example

16. DETERMINING CAPACITY UTILIZATION AND EFFICIENCY - Bakery example Sara James Bakery has a plant for processing Deluxe breakfast rolls and wants to better understand its capability. Last week the facility produced 148,000 rolls. The effective capacity is 175,000 rolls. The production line operates 7 days per week, with three 8-hour shifts per day. The line was designed to process the nut-filled, cinnamon-flavored Deluxe roll at a rate of 1,200 per hour. Determine the design capacity, utilization, and efficiency for this plant when producing this Deluxe roll.

17. Bakery example

18. Bakery example

19. Bakery example

20. Bakery example

21. Bakery example: A New line of 75% efficiency was introduced

22. Bakery example: A New line of 75% efficiency was introduced

23. Capacity and Strategy Capacity decisions impact all 10 decisions of operations management as well as other functional areas of the organization Capacity decisions must be integrated into the organization’s mission and strategy

24. 10 OM Decisions Design of goods and services Managing quality Process and capacity strategy Location strategy Layout strategy Human resources and job design Supply chain management Inventory management Scheduling Maintenance

25. Capacity Considerations Forecast demand accurately Match technology increments and sales volume Find the optimum operating size (volume) Build for change

26. CONSTRAINT MANAGEMENT A constraint is something that limits the performance of a process or system in achieving its goals.

27. There are seven categories of constraints: Market: Insufficient demand. Resource: Too little of one or more resources (e.g., workers, equipment, and space) Material: Too little of one or more materials. Financial: Insufficient funds. Supplier: Unreliable, long lead time, substandard quality. Knowledge or competency: Needed knowledge or skills missing or incomplete. Policy: Laws or regulations interfere.

28. Service-Sector Demand and Capacity Management Demand management Appointment, reservations, FCFS rule Capacity management Full time, temporary, part-time staff

29. Bottleneck Analysis and the Theory of Constraints Each work area can have its own unique capacity Capacity analysis determines the throughput capacity of workstations in a system A bottleneck is a limiting factor or constraint A bottleneck has the lowest effective capacity in a system Process time - t he time to produce a unit or a specified batch size

30. Bottleneck Analysis and the Theory of Constraints The bottleneck time is the time of the slowest workstation (the one that takes the longest) in a production system The throughput time is the time it takes a unit to go through production from start to end, with no waiting, . It is the time of the longest path through the system. 2 min/unit 4 min/unit 3 min/unit A B C Figure S7.4

31. CAPACITY ANALYSIS WITH PARALLEL PROCESSES Sample problem: Howard Kraye’s sandwich shop provides healthy sandwiches for customers. Howard has two identical sandwich assembly lines. A customer first places an order, which takes 30 seconds. The order is then sent to one of the two assembly lines. Each assembly line has two workers and three operations: (1) assembly worker 1 retrieves and cuts the bread (15 seconds/sandwich), (2) assembly worker 2 adds ingredients and places the sandwich onto the toaster conveyor belt (20 seconds/sandwich), and (3) the toaster heats the sandwich (40 seconds/sandwich). Finally, another employee wraps the heated sandwich coming out of the toaster and delivers it to the customer (37.5 seconds/sandwich). A flowchart of the process is shown below. Howard wants to determine the bottleneck time and throughput time of this process. Wrap/ Deliver 37.5 sec/sandwich Order 30 sec/sandwich Bread Fill 15 sec/sandwich 20 sec/sandwich 40 sec/sandwich Bread Fill Toaster 15 sec/sandwich 20 sec/sandwich Toaster 40 sec/sandwich First assembly line Second assembly line

32. CAPACITY ANALYSIS WITH PARALLEL PROCESSES Two identical sandwich lines Lines have two workers and three operations All completed sandwiches are wrapped Wrap/ Deliver 37.5 sec/sandwich Order 30 sec/sandwich Bread Fill 15 sec/sandwich 20 sec/sandwich 40 sec/sandwich Bread Fill Toaster 15 sec/sandwich 20 sec/sandwich Toaster 40 sec/sandwich First assembly line Second assembly line

33. CAPACITY ANALYSIS WITH PARALLEL PROCESSES The two lines are identical, so parallel processing can occur At 40 seconds, the toaster has the longest processing time and is the bottleneck for each line At 40 seconds for two sandwiches, the bottleneck time of the combined lines = 20 seconds At 37.5 seconds, wrapping and delivery is the bottleneck for the entire operation Wrap 37.5 sec Order 30 sec Bread Fill 15 sec 20 sec 40 sec Bread Fill Toaster 15 sec 20 sec Toaster 40 sec

34. CAPACITY ANALYSIS WITH PARALLEL PROCESSES Capacity per hour is 3,600 seconds/37.5 seconds/sandwich = 96 sandwiches per hour Throughput time is 30 + 15 + 20 + 40 + 37.5 = 142.5 seconds Wrap 37.5 sec Order 30 sec Bread Fill 15 sec 20 sec 40 sec Bread Fill Toaster 15 sec 20 sec Toaster 40 sec

35. CAPACITY ANALYSIS WITH SIMULTANEOUS PROCESSES Sample Problem: Dr. Cynthia Knott’s dentistry practice has been cleaning customers’ teeth for decades. The process for a basic dental cleaning is relatively straightforward: (1) the customer checks in (2 minutes); (2) a lab technician takes and develops X-rays (2 and 4 minutes, respectively); (3) the dentist processes and examines the X-rays (5 minutes) while the hygienist cleans the teeth (24 minutes); (4) the dentist meets with the patient to poke at a few teeth, explain the X-ray results, and tell the patient to floss more often (8 minutes); and (5) the customer pays and books her next appointment (6 minutes). A flowchart of the customer visit is shown below. Dr. Knott wants to determine the bottleneck time and throughput time of this process.

36. CAPACITY ANALYSIS WITH SIMULTANEOUS PROCESSES Standard process for cleaning teeth Cleaning and examining X-rays can happen simultaneously Check out 6 min/unit Check in 2 min/unit Develops X-ray 4 min/unit 8 min/unit Dentist Takes X-ray 2 min/unit 5 min/unit X-ray exam Hygienist cleaning 24 min/unit

37. CAPACITY ANALYSIS WITH SIMULTANEOUS PROCESSES All possible paths must be compared Bottleneck is the hygienist at 24 minutes Hourly capacity is 60/24 = 2.5 patients X-ray exam path is 2 + 2 + 4 + 5 + 8 + 6 = 27 minutes Cleaning path is 2 + 2 + 4 + 24 + 8 + 6 = 46 minutes Longest path involves the hygienist cleaning the teeth, patient should complete in 46 minutes Check out 6 min/unit Check in 2 min/unit Develops X-ray 4 min/unit 8 min/unit Dentist Takes X-ray 2 min/unit 5 min/unit X-ray exam Hygienist cleaning 24 min/unit

38. CAPACITY ANALYSIS WITH SIMULTANEOUS PROCESSES To summarize: (1) the bottleneck is the operation with the longest (slowest) process time, after dividing by the number of parallel (redundant) operations (2) the system capacity is the inverse of the bottleneck time , and (3) the throughput time is the total time through the longest path in the system, assuming no waiting.

39. T echniques for evaluating capacity alternatives Cost–Volume Analysis Cost–volume analysis focuses on relationships between cost, revenue, and volume of output. The purpose of cost–volume analysis is to estimate the income of an organization under different operating conditions.

40. Cost–Volume Analysis Fixed costs tend to remain constant regardless of volume of output. Examples include rental costs, property taxes, equipment costs, heating and cooling expenses, and certain administrative costs. Variable costs vary directly with volume of output. The major components of variable costs are generally materials and labor costs.

41. Break-even point (BEP) Break-even point (BEP) The volume of output at which total cost and total revenue are equal. Total profit can be computed using the formula:

42. Example

43. Example

44. Profit corridor Loss corridor Break-Even Analysis Total revenue line Total cost line Variable cost Fixed cost Break-even point Total cost = Total revenue – 900 – 800 – 700 – 600 – 500 – 400 – 300 – 200 – 100 – | | | | | | | | | | | | 0 100 200 300 400 500 600 700 800 900 1000 1100 Cost in dollars Volume (units per period) Figure S7.5

45. Break-Even Analysis Costs and revenue are linear functions Generally not the case in the real world We actually know these costs Very difficult to verify Time value of money is often ignored Assumptions

46. Break-Even Analysis BEP x = break-even point in units BEP $ = break-even point in dollars P = price per unit (after all discounts) x = number of units produced TR = total revenue = Px F = fixed costs V = variable cost per unit TC = total costs = F + Vx TR = TC or Px = F + Vx Break-even point occurs when BEP x = F P – V

47. Break-Even Analysis BEP x = break-even point in units BEP $ = break-even point in dollars P = price per unit (after all discounts) x = number of units produced TR = total revenue = Px F = fixed costs V = variable cost per unit TC = total costs = F + Vx BEP $ = BEP x P = P = = F ( P – V )/ P F P – V F 1 – V / P Profit = TR - TC = Px – ( F + Vx ) = Px – F – Vx = ( P - V ) x – F

48. Break-Even Example Fixed costs = $10,000 Material = $.75/unit Direct labor = $1.50/unit Selling price = $4.00 per unit BEP $ = = F 1 – ( V / P ) $10,000 1 – [(1.50 + .75)/(4.00)] = = $22,857.14 $10,000 .4375

49. Break-Even Example Fixed costs = $10,000 Material = $.75/unit Direct labor = $1.50/unit Selling price = $4.00 per unit BEP $ = = F 1 – ( V / P ) $10,000 1 – [(1.50 + .75)/(4.00)] = = $22,857.14 $10,000 .4375 BEP x = = = 5,714 F P – V $10,000 4.00 – (1.50 + .75)

50. Break-Even Example 50,000 – 40,000 – 30,000 – 20,000 – 10,000 – | | | | | | 0 2,000 4,000 6,000 8,000 10,000 Dollars Units Fixed costs Total costs Revenue Break-even point