1. LSM733-PRODUCTION OPERATIONS MANAGEMENT By: OSMAN BIN SAIF LECTURE 29 1

2. Summary of last Session  Characteristics of a Waiting-Line System  Arrival Characteristics  Waiting-Line Characteristics  Service Characteristics  Measuring a Queue’s Performance  Queuing Costs 2

3. Summary of last Session (Contd.)  The Variety of Queuing Models  Model A(M/M/1): Single-Channel Queuing Model with Poisson Arrivals and Exponential Service Times  Model B(M/M/S): Multiple-Channel Queuing Model  Model C(M/D/1): Constant-Service-Time Model  Model D: Limited-Population Model 3

4. Summary of last Session (Contd.)  Other Queuing Approaches 4

5. Agenda for this Session  Capacity  Design and Effective Capacity  Capacity and Strategy  Capacity Considerations  Managing Demand  Demand and Capacity Management in the Service Sector 5

6. Agenda for this Session (Contd.)  Bottleneck Analysis and Theory of Constraints  Process Times for Stations, Systems, and Cycles  Theory of Constraints  Bottleneck Management  Break-Even Analysis  Single-Product Case 6

7. Agenda for this Session (Contd.)  Applying Expected Monetary Value to Capacity Decisions 7

8. ADDITIONAL CHAPTER: CAPACITY AND CONSTRAINT MANAGEMENT 8

9. Capacity  The throughput, or the number of units a facility can hold, receive, store, or produce in a period of time  Determines fixed costs  Determines if demand will be satisfied  If facilities remain idle 9

10. Planning Over a Time Horizon Figure S7.1 Modify capacityUse capacity Intermediate- range planning SubcontractAdd personnel Add equipmentBuild or use inventory Add shifts Short-range planning Schedule jobs Schedule personnel Allocate machinery * Long-range planning Add facilities Add long lead time equipment * * Difficult to adjust capacity as limited options exist Options for Adjusting Capacity 10

11. Design and Effective Capacity  Design capacity is the maximum theoretical output of a system  Normally expressed as a rate  Effective capacity is the capacity a firm expects to achieve given current operating constraints  Often lower than design capacity 11

12. Utilization and Efficiency Utilization is the percent of design capacity actually achieved Efficiency is the percent of effective capacity actually achieved Utilization = Actual output/Design capacity Efficiency = Actual output/Effective capacity 12

13. Bakery Example Actual production last week = 148,000 rolls Effective capacity = 175,000 rolls Design capacity = 1,200 rolls per hour Bakery operates 7 days/week, 3 - 8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls

14. Bakery Example Actual production last week = 148,000 rolls Effective capacity = 175,000 rolls Design capacity = 1,200 rolls per hour Bakery operates 7 days/week, 3 - 8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls

15. Bakery Example Actual production last week = 148,000 rolls Effective capacity = 175,000 rolls Design capacity = 1,200 rolls per hour Bakery operates 7 days/week, 3 - 8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls Utilization = 148,000/201,600 = 73.4%

16. Bakery Example Actual production last week = 148,000 rolls Effective capacity = 175,000 rolls Design capacity = 1,200 rolls per hour Bakery operates 7 days/week, 3 - 8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls Utilization = 148,000/201,600 = 73.4%

17. Bakery Example Actual production last week = 148,000 rolls Effective capacity = 175,000 rolls Design capacity = 1,200 rolls per hour Bakery operates 7 days/week, 3 - 8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls Utilization = 148,000/201,600 = 73.4% Efficiency = 148,000/175,000 = 84.6%

18. Bakery Example Actual production last week = 148,000 rolls Effective capacity = 175,000 rolls Design capacity = 1,200 rolls per hour Bakery operates 7 days/week, 3 - 8 hour shifts Design capacity = (7 x 3 x 8) x (1,200) = 201,600 rolls Utilization = 148,000/201,600 = 73.4% Efficiency = 148,000/175,000 = 84.6%

19. Bakery Example: Estimating Output of a New Facility They are considering adding a second production line and they plan to hire new employees and train them to operate this new line Effective capacity on this new line = 175,000 rolls which is the same on the first line However, due to new hires they expect that efficiency of this new line will be 75% rather than 84.6% Expected Output = (Effective Capacity)(Efficiency) = (175,000)(.75) = 131,250 rolls

20. 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

21. Important Issues in Capacity Planning 1.Forecast demand accurately 2.Understand the technology and capacity increments 3.Find the optimum operating level (volume) 4.Build for change 21

22. Economies and Diseconomies of Scale Economies of scale Diseconomies of scale 25 - room roadside motel 50 - room roadside motel 75 - room roadside motel Number of Rooms 255075 Average unit cost (dollars per room per night) Figure S7.2 22

23. Managing Demand  Demand exceeds capacity  Curtail demand by raising prices, scheduling longer lead time  Long term solution is to increase capacity  Capacity exceeds demand  Stimulate demand through price reductions  Product changes  Adjusting to seasonal demands  Produce products with complementary demand patterns 23

24. Complementary Demand Patterns 4,000 – 3,000 – 2,000 – 1,000 – J F M A M J J A S O N D J F M A M J J A S O N D J Sales in units Time (months) Jet ski engine sales Figure S7.3 24

25. Complementary Demand Patterns 4,000 – 3,000 – 2,000 – 1,000 – J F M A M J J A S O N D J F M A M J J A S O N D J Sales in units Time (months) Snowmobile motor sales Jet ski engine sales Figure S7.3 25

26. Complementary Demand Patterns 4,000 – 3,000 – 2,000 – 1,000 – J F M A M J J A S O N D J F M A M J J A S O N D J Sales in units Time (months) Combining both demand patterns reduces the variation Snowmobile motor sales Jet ski engine sales Figure S7.3 26

27. Tactics for Matching Capacity to Demand 1.Increasing/decreasing employees and shifts 2.Adjusting equipment  Purchasing additional machinery  Selling or leasing out existing equipment 3.Improving processes to increase throughput 4.Redesigning products to facilitate more throughput 5.Adding process flexibility to meet changing product preferences 6.Closing facilities 27

28. Demand and Capacity Management in the Service Sector  Demand management (scheduling customers)  Appointment, reservations, FCFS rule  Capacity management (scheduling workforce)  Full time, temporary, part-time staff 28

29. Bottleneck Analysis and Theory of Constraints  Capacity analysis determines the throughput capacity of workstations in a system  A bottleneck has the lowest effective capacity in a system  A bottleneck is a limiting factor or constraint 29

30. Theory of Constraints  Five-step process for recognizing and managing limitations Step 1: Step 1:Identify the constraint Step 2: Step 2:Develop a plan for overcoming the constraints Step 3: Step 3:Focus resources on accomplishing Step 2 Step 4: Step 4:Reduce the effects of constraints by offloading work or expanding capability Step 5: Step 5:Once overcome, go back to Step 1 and find new constraints 30

31. Bottleneck Management 1.Release work orders to the system at the pace of set by the bottleneck 2.Lost time at the bottleneck represents lost time for the whole system 3.Increasing the capacity of a non-bottleneck station is a mirage 4.Increasing the capacity of a bottleneck increases the capacity of the whole system 31

32. Process Times for Stations, Systems, and Cycles process time of a station  The process time of a station is the time to produce a unit at that single workstation process time of a system  The process time of a system is the time of the longest process in the system … the bottleneck system capacity  The system capacity is the inverse of the system process time process cycle time  The process cycle time is the total time through the longest path in the system 32

33. A Three-Station Assembly Line Process time of stations: 2, 4 and 3 min/unit Process time for the system: 4 min/unit Process Cycle Time= 2 + 4 + 3 = 9 min/unit System Capacity = ¼*60(min)= 15 units/hour Figure S7.4 2 min/unit4 min/unit3 min/unit ABC 33

34. Capacity Analysis EXAMPLE  Two identical sandwich lines  Lines have two workers and three operations  All completed sandwiches are wrapped Wrap 37.5 sec/sandwich Order 30 sec/sandwich BreadFillToast 15 sec/sandwich 20 sec/sandwich 40 sec/sandwich BreadFillToast 15 sec/sandwich20 sec/sandwich40 sec/sandwich 34

35. Capacity Analysis Wrap 37.5 sec Order 30 sec BreadFillToast 15 sec 20 sec 40 sec BreadFillToast 15 sec20 sec40 sec  It seems that the toast work station has the longest processing time – 40 seconds, but the two lines work in parallel and each deliver a sandwich every 40 seconds so the process time of the toast work station is 40/2 = 20 seconds. So process time of five stations are 30, 15, 20, 40 and 37.5 sec., respectively.  With 37.5 seconds, wrapping station has the longest processing time and it is the bottleneck. So process time of the system is 37.5 sec.  System capacity per hour is (1/37.5)*3,600 seconds = 96 sandwiches per hour  Process cycle time is 30 + 15 + 20 + 40 + 37.5 = 142.5 seconds 35

36. Capacity Analysis Example  Standard process for cleaning teeth  Cleaning and examining X-rays can happen simultaneously Customer pays 6 min/unit Customer Checks in 2 min/unit A Lab Ass Develops X-ray 4 min/unit8 min/unit Dentist re-processes A Lab Ass. Takes X-ray 2 min/unit 5 min/unit Dentist Examines X-ray and processes Hygienist Cleans the teeth 24 min/unit 36

37. Capacity Analysis  All possible paths must be compared  Cleaning path is 2 + 2 + 4 + 24 + 8 + 6 = 46 minutes, X-ray exam path is 2 + 2 + 4 + 5 + 8 + 6 = 27 minutes  Longest path involves the hygienist cleaning the teeth, so the process cycle time is 46 min. The patient will be out of door after 46 min.  Bottleneck is the hygienist at 24 minutes which is the process time of the system  System capacity is (1/24)*60 min = 2.5 patients/per hour 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 Cleaning 24 min/unit 37

38. Break-Even Analysis  Technique for evaluating process and equipment alternatives  Objective is to find the break-even point in dollars and in units at which cost equals revenue  Requires estimation of fixed costs, variable costs, and revenue 38

39. Break-Even Analysis  Fixed costs are costs that continue even if no units are produced  Depreciation, taxes, debt, mortgage payments  Variable costs are costs that vary with the volume of units produced  Labor, materials, portion of utilities  Contribution is the difference between selling price and variable cost 39

40. 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 40

41. 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 – – |||||||||||| 010020030040050060070080090010001100 Cost in dollars Volume (units per period) Figure S7.5 41

42. 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 42

43. 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 43

44. 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)] 44

45. 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) 45

46. Break-Even Example 50,000 – 40,000 – 30,000 – 20,000 – 10,000 – – |||||| 02,0004,0006,0008,00010,000 Dollars Units Fixed costs Total costs Revenue Break-even point 46

47. Expected Monetary Value (EMV) and Capacity Decisions  Determine states of nature  Future demand  Market favorability  Analyzed using decision trees  Hospital supply company  Four alternatives for capacity expansion 47

48. Expected Monetary Value (EMV) and Capacity Decisions -$90,000 Market unfavorable (.6) Market favorable (.4) $100,000 Large plant Market favorable (.4) Market unfavorable (.6) $60,000 -$10,000 Medium plant Market favorable (.4) Market unfavorable (.6) $40,000 -$5,000 Small plant $0 Do nothing 48

49. Expected Monetary Value (EMV) and Capacity Decisions -$90,000 Market unfavorable (.6) Market favorable (.4) $100,000 Large plant Market favorable (.4) Market unfavorable (.6) $60,000 -$10,000 Medium plant Market favorable (.4) Market unfavorable (.6) $40,000 -$5,000 Small plant $0 Do nothing EMV =(.4)($100,000) + (.6)(-$90,000) Large Plant EMV = -$14,000 49

50. Expected Monetary Value (EMV) and Capacity Decisions -$90,000 Market unfavorable (.6) Market favorable (.4) $100,000 Large plant Market favorable (.4) Market unfavorable (.6) $60,000 -$10,000 Medium plant Market favorable (.4) Market unfavorable (.6) $40,000 -$5,000 Small plant $0 Do nothing -$14,000 $13,000$18,000 50

51. Summary of the Session  Capacity  Design and Effective Capacity  Capacity and Strategy  Capacity Considerations  Managing Demand  Demand and Capacity Management in the Service Sector 51

52. Summary of the Session(Contd.)  Bottleneck Analysis and Theory of Constraints  Process Times for Stations, Systems, and Cycles  Theory of Constraints  Bottleneck Management  Break-Even Analysis  Single-Product Case 52

53. Summary of the Session (Contd.)  Applying Expected Monetary Value to Capacity Decisions 53

54. THANK YOU 54