1. Review for Exam III This exam will be administered Wednesday, July 31, 2013, beginning at 10 a.m. – 11:50 a.m.

2. Exam Format  40-50 multiple choice  2 - 3 problems  Closed-book  Closed-notes  Closed-neighbor  BRING---pencil, calculator, scantron sheet

3. Exam Coverage  Chapters 12, 13, 14 and 16 in that order  An overview of MRP in Chap 15  No details  No algorithms  NO CHAPTER SUPPLEMENTS  No simulation

4. Typical problems—  Forecasting with error calc  Inventory calculations involving: EOQ, reorder point, TC, safety stock, price discounting  Lean concepts  Calculation of the number of kanbans

5. FORECASTING--Two basic categories of approaches What are they??

6. Smoothing Effects 150 150 – 125 125 – 100 100 – 75 75 – 50 50 – 25 25 – 0 0 – ||||||||||| JanFebMarAprMayJuneJulyAugSeptOctNov Actual Orders Month 5-month 3-month

7. Weighted Moving Average WMA n = i = 1  Wi DiWi DiWi DiWi Di where W i = the weight for period i, between 0 and 100 percent  W i = 1.00  Adjusts moving average method to more closely reflect data fluctuations

8. Weighted Moving Average Example MONTH WEIGHT DATA August 17%130 September 33%110 October 50%90 WMA 3 = 3 i = 1  Wi DiWi DiWi DiWi Di = (0.50)(90) + (0.33)(110) + (0.17)(130) = 103.4 orders November Forecast

9.  Averaging method  Weights most recent data more strongly  Reacts more to recent changes  Widely used, accurate method Exponential Smoothing

10. F t +1 =  D t + (1 -  )F t where: F t +1 =forecast for next period D t =actual demand for present period F t =previously determined forecast for present period  =weighting factor, smoothing constant Exponential Smoothing (cont.)

11. Effect of Smoothing Constant 0.0  1.0 If  = 0.20, then F t +1 = 0.20  D t + 0.80 F t If  = 0, then F t +1 = 0  D t + 1 F t 0 = F t Forecast does not reflect recent data If  = 1, then F t +1 = 1  D t + 0 F t =  D t Forecast based only on most recent data

12. F 2 =  D 1 + (1 -  )F 1 = (0.30)(37) + (0.70)(37) = 37 F 3 =  D 2 + (1 -  )F 2 = (0.30)(40) + (0.70)(37) = 37.9 F 13 =  D 12 + (1 -  )F 12 = (0.30)(54) + (0.70)(50.84) = 51.79 Exponential Smoothing (α=0.30) PERIODMONTHDEMAND 1Jan37 2Feb40 3Mar41 4Apr37 5May 45 6Jun50 7Jul 43 8Aug 47 9Sep 56 10Oct52 11Nov55 12Dec 54

13. FORECAST, F t + 1 PERIODMONTHDEMAND(  = 0.3)(  = 0.5) 1Jan37–– 2Feb4037.0037.00 3Mar4137.9038.50 4Apr3738.8339.75 5May 4538.2838.37 6Jun5040.2941.68 7Jul 4343.2045.84 8Aug 4743.1444.42 9Sep 5644.3045.71 10Oct5247.8150.85 11Nov5549.0651.42 12Dec 5450.8453.21 13Jan–51.7953.61 Exponential Smoothing (cont.)

14. 70 70 – 60 60 – 50 50 – 40 40 – 30 30 – 20 20 – 10 10 – 0 0 – ||||||||||||| 12345678910111213 Actual Orders Month Exponential Smoothing (cont.)  = 0.50  = 0.30

15. AF t +1 = F t +1 + T t +1 where T = an exponentially smoothed trend factor T t +1 =  (F t +1 - F t ) + (1 -  ) T t where T t = the last period trend factor  = a smoothing constant for trend Adjusted Exponential Smoothing

16. Adjusted Exponential Smoothing (β=0.30) PERIODMONTHDEMAND 1Jan37 2Feb40 3Mar41 4Apr37 5May 45 6Jun50 7Jul 43 8Aug 47 9Sep 56 10Oct52 11Nov55 12Dec 54 T 3 =  (F 3 - F 2 ) + (1 -  ) T 2 = (0.30)(38.5 - 37.0) + (0.70)(0) = 0.45 AF 3 = F 3 + T 3 = 38.5 + 0.45 = 38.95 T 13 =  (F 13 - F 12 ) + (1 -  ) T 12 = (0.30)(53.61 - 53.21) + (0.70)(1.77) = 1.36 AF 13 = F 13 + T 13 = 53.61 + 1.36 = 54.96

17. Adjusted Exponential Smoothing: Example FORECASTTRENDADJUSTED PERIODMONTHDEMANDF t +1 T t +1 FORECAST AF t +1 1Jan3737.00–– 2Feb4037.000.0037.00 3Mar4138.500.4538.95 4Apr3739.750.6940.44 5May 4538.370.0738.44 6Jun5038.370.0738.44 7Jul 4345.841.9747.82 8Aug 4744.420.9545.37 9Sep 5645.711.0546.76 10Oct5250.852.2858.13 11Nov5551.421.7653.19 12Dec 5453.211.7754.98 13Jan–53.611.3654.96

18. Adjusted Exponential Smoothing Forecasts 70 70 – 60 60 – 50 50 – 40 40 – 30 30 – 20 20 – 10 10 – 0 0 – ||||||||||||| 12345678910111213 Actual Demand Period Forecast (  = 0.50) Adjusted forecast (  = 0.30)

19. y = a + bx where a = intercept b = slope of the line x = time period y = forecast for demand for period x Linear Trend Line b = a = y - b x where n =number of periods x == mean of the x values y == mean of the y values  xy - nxy  x 2 - nx 2  x n  y n

20. Least Squares Example x (PERIOD) y (DEMAND) xyx 2 173371 240804 3411239 43714816 54522525 65030036 74330149 84737664 95650481 1052520100 1155605121 1254648144 785573867650

21. x = = 6.5 y = = 46.42 b = = =1.72 a = y - bx = 46.42 - (1.72)(6.5) = 35.2 3867 - (12)(6.5)(46.42) 650 - 12(6.5) 2  xy - nxy  x 2 - nx 2 78 12 557 12 Least Squares Example (cont.)

22. Linear trend line y = 35.2 + 1.72 x Forecast for period 13 y = 35.2 + 1.72(13)= 57.56 units 70 70 – 60 60 – 50 50 – 40 40 – 30 30 – 20 20 – 10 10 – 0 0 – ||||||||||||| 12345678910111213 Actual Demand Period Linear trend line

23. Seasonal Adjustments  Repetitive increase/ decrease in demand  Use seasonal factor to adjust forecast Seasonal factor = S i = DiDiDDDiDiDD

24. Seasonal Adjustment (cont.) 2002 12.68.66.317.545.0 2003 14.110.37.518.250.1 2004 15.310.68.119.653.6 Total 42.029.521.955.3148.7 DEMAND (1000’S PER QUARTER) YEAR1234Total S 1 = = = 0.28 D1D1DDD1D1DD 42.0148.7 S 2 = = = 0.20 D2D2DDD2D2DD 29.5148.7 S 4 = = = 0.37 D4D4DDD4D4DD 55.3148.7 S 3 = = = 0.15 D3D3DDD3D3DD 21.9148.7

25. Seasonal Adjustment (cont.) SF 1 = (S 1 ) (F 5 ) = (0.28)(58.17) = 16.28 SF 2 = (S 2 ) (F 5 ) = (0.20)(58.17) = 11.63 SF 3 = (S 3 ) (F 5 ) = (0.15)(58.17) = 8.73 SF 4 = (S 4 ) (F 5 ) = (0.37)(58.17) = 21.53 y = 40.97 + 4.30 x = 40.97 + 4.30(4) = 58.17 For 2005

26. Forecast Accuracy  Forecast error  difference between forecast and actual demand  MAD  mean absolute deviation  MAPD  mean absolute percent deviation  Cumulative error  Average error or bias

27. Mean Absolute Deviation (MAD) where t = period number t = period number D t = demand in period t D t = demand in period t F t = forecast for period t F t = forecast for period t n = total number of periods n = total number of periods  = absolute value  D t - F t  n MAD =

28. MAD Example 13737.00–– 24037.003.003.00 34137.903.103.10 43738.83-1.831.83 54538.286.726.72 65040.299.699.69 74343.20-0.200.20 84743.143.863.86 95644.3011.7011.70 105247.814.194.19 115549.065.945.94 125450.843.153.15 55749.3153.39 PERIODDEMAND, D t F t (  =0.3)(D t - F t ) |D t - F t |  D t - F t  n MAD= = = 4.85 53.39 11

29. Other Accuracy Measures Mean absolute percent deviation (MAPD) MAPD =  |D t - F t |  D t Cumulative error E =  e t Average error E = etetnnetetnnn

30. Comparison of Forecasts FORECASTMADMAPDE(E) Exponential smoothing (  = 0.30)4.859.6%49.314.48 Exponential smoothing (  = 0.50)4.048.5%33.213.02 Adjusted exponential smoothing3.817.5%21.141.92 (  = 0.50,  = 0.30) Linear trend line2.294.9%––

31. Forecast Control  Tracking signal  monitors the forecast to see if it is biased high or low  1 MAD ≈ 0.8 б  Control limits of 2 to 5 MADs are used most frequently Tracking signal = =  (D t - F t ) MADEMAD

32. Tracking Signal Values 13737.00––– 24037.003.003.003.00 34137.903.106.103.05 43738.83-1.834.272.64 54538.286.7210.993.66 65040.299.6920.684.87 74343.20-0.2020.484.09 84743.143.8624.344.06 95644.3011.7036.045.01 105247.814.1940.234.92 115549.065.9446.175.02 125450.843.1549.324.85 DEMANDFORECAST,ERROR  E = PERIODD t F t D t - F t  (D t - F t )MAD TS 3 = = 2.00 6.10 3.05 Tracking signal for period 3 –1.002.001.623.004.255.016.007.198.189.2010.17TRACKINGSIGNAL

33. Tracking Signal Plot 3  3  – 2  2  – 1  1  – 0  0  – -1  -1  – -2  -2  – -3  -3  – ||||||||||||| 0123456789101112 Tracking signal (MAD) Period Exponential smoothing (  = 0.30) Linear trend line

34. Statistical Control Charts  = = = =  (D t - F t ) 2 n - 1  Using  we can calculate statistical control limits for the forecast error  Control limits are typically set at  3 

35. Statistical Control Charts Errors 18.39 18.39 – 12.24 12.24 – 6.12 6.12 – 0 0 – -6.12 -6.12 – -12.24 -12.24 – -18.39 -18.39 – ||||||||||||| 0123456789101112 Period UCL = +3  LCL = -3 

36. Regression? Correlation?  Neither will be on the exam  Regression is just the linear trend line in which the independent variables are other than time  There will not be exam questions on either regression or correlation  But you will see LINEAR TREND LINE

37. Inventory for Independent Demand – Chapter 13  EOQ = Economic Order Quantityu  Assumes

38. Carrying costs  Rent  Lighting/heating  Security  Interest (on borrowed capital tied up in inventory)  Taxes  Shrink/obsolescence/theft Can also be expressed as a % of product cost A rule of thumb is 30%

39. Ordering costs—costs related to Transportation Shipping Receiving Inspection

40. Shortage costs  This is an opportunity cost  Is ignored in the simple EOQ models you will be using, by assuming that there are no shortages  Consideration is given to shortages when we add safety stock to a Reorder Point, R = d*L + safety stock

41. Back-order costs  Will assume impatient customers who must have the product they wish to buy NOW.  So back-ordering is not considered in the simple models we looked at

42. Continuous Inventory Systems  Constant order amount, called the EOQ  EOQ = Economic Order Quantity  Fixed annual deterministic demand  Minimizes  Holding (carrying) costs  Ordering costs  Uses re-order point to determine when to order  Time between orders is not fixed

43. EOQ models also have  No shortages/back-ordering  Constant lead time  Instantaneous or finite replenishment  Can take into consideration price discounting  When doing so, three costs are minimized jointly: Ordering costs, holding costs and purchase costs taken over a year’s time

44. If the quantity ordered is less than the EOQ, then  Ordering costs will be greater than holding (carrying) costs

45. ABC Classification—what is the point??  To concentrate, focus on the those items in inventory that constitute the highest dollar value to the firm  Class A items constitute 5-15% of the items and 70 to 80% of the total dollar value to the firm  Class B items constitute 30% of the inventory items but only 15% of the dollar value  Class C items constitute 50 to 60% of the items but only 5 to 10% of the dollar value

46. ABC Classification..  Class A items are tightly controlled  Class B items less so  Class C items even less  Dollar values are computed by multiplying the unit cost by the annual demand for the item  This technique is used in all auto parts inventory control systems and has been for 15 years

47. Periodic inventory systems are….  Fixed Time period systems  NOT  EOQ Models  The time between orders is fixed, the re-order point is fixed, but the order amount is not

48. Which gives you lowest holding cost?  Instantaneous replenishment  Finite (non-instantaneous) replenishment  Quantity discounts  WHICH OF THE ABOVE GIVES YOU LOWEST TOTAL ORDERING COST?

49. How do we calculate a re- order point?  Lead time in days times the daily demand plus the safety stock  Safety stock equals the service level (usually 3 for z) times the standard deviation of daily demand times the sq. rt. of lead time.  (You will be given the formulas)

50. How do we calculate…  Time between orders?  Production days in a year / # of orders  Run length  EOQ or order quantity / daily Production rate

51. How do we calculate…  Time between orders?  Production days in a year / # of orders  Run length  EOQ or order quantity / daily Production rate

52. Safety Stocks and Service Levels  Safety stock = Z value * std. dev. of daily demand * sqrt(lead time)  For 95% service level, use Z value of 1.65  For 99% service level, use Z value of 3

53. Inventory Terms  ABC system  Carrying costs  Continuous inventory system  Dependent demand  EOQ  Fixed-order quantity system  Fixed time period system  Capacity  Independent demand  Inventory  In-process inventory  Non-instantaneous receipt  Order cycle  Quantity discount  Stockout  Service level  Efficiency

54. Chapter 14 –S&OP

55. Copyright 2009 John Wiley & Sons, Inc.14-55 Sales and Operations Planning – Chapter 14  Determines the resource capacity needed to meet demand over an intermediate time horizon  Aggregate refers to sales and operations planning for product lines or families  Sales and Operations planning (S&OP) matches supply and demand  Objectives  Establish a company wide game plan for allocating resources  Develop an economic strategy for meeting demand

56. Copyright 2009 John Wiley & Sons, Inc.14-56 Sales and Operations Planning Process

57. What are the inputs to the aggregate planning system??  Demand forecasts  Capacity constraints  Strategic objectives  Company policies  Financial constraints  NOT…  Size of workforce  Inventory levels  Units subcontracted  Overtime scheduled

58. Copyright 2009 John Wiley & Sons, Inc.14-58 The Monthly S&OP Planning Process

59. Copyright 2009 John Wiley & Sons, Inc.14-59 Meeting Demand Strategies  Adjusting capacity  Resources necessary to meet demand are acquired and maintained over the time horizon of the plan  Minor variations in demand are handled with overtime or under-time  Managing demand  Proactive demand management

60. Copyright 2009 John Wiley & Sons, Inc.14-60 Strategies for Adjusting Capacity  Level production  Producing at a constant rate and using inventory to absorb fluctuations in demand  Chase demand  Hiring and firing workers to match demand  Peak demand  Maintaining resources for high-demand levels  Overtime and under-time  Increasing or decreasing working hours  Subcontracting  Let outside companies complete the work  Part-time workers  Hiring part time workers to complete the work  Backordering  Providing the service or product at a later time period

61. Copyright 2009 John Wiley & Sons, Inc.14-61 Strategies for Adjusting Capacity  Level production  Producing at a constant rate and using inventory to absorb fluctuations in demand  Chase demand  Hiring and firing workers to match demand  Peak demand  Maintaining resources for high-demand levels  Overtime and under-time  Increasing or decreasing working hours  Subcontracting  Let outside companies complete the work  Part-time workers  Hiring part time workers to complete the work  Backordering  Providing the service or product at a later time period

62. Copyright 2009 John Wiley & Sons, Inc.14-62 Level Production Demand Units Time Production

63. Copyright 2009 John Wiley & Sons, Inc.14-63 Chase Demand Demand Units Time Production

64. Copyright 2009 John Wiley & Sons, Inc.14-64 Strategies for Managing Demand  Shifting demand into other time periods  Incentives  Sales promotions  Advertising campaigns  Offering products or services with counter- cyclical demand patterns  Partnering with suppliers to reduce information distortion along the supply chain

65. Copyright 2009 John Wiley & Sons, Inc.14-65 Quantitative Techniques For AP  Pure Strategies  Mixed Strategies  Linear Programming  Transportation Method  Other Quantitative Techniques

66. Copyright 2009 John Wiley & Sons, Inc.14-66 Pure Strategies Hiring cost= $100 per worker Firing cost= $500 per worker Inventory carrying cost= $0.50 pound per quarter Inventory carrying cost= $0.50 pound per quarter Regular production cost per pound= $2.00 Regular production cost per pound= $2.00 Production per employee= 1,000 pounds per quarter Production per employee= 1,000 pounds per quarter Beginning work force= 100 workers Beginning work force= 100 workers QUARTERSALES FORECAST (LB) Spring80,000 Summer50,000 Fall120,000 Winter150,000 Example:

67. Copyright 2009 John Wiley & Sons, Inc.14-67 Level Production Strategy Level production = 100,000 pounds (50,000 + 120,000 + 150,000 + 80,000) 4 Spring80,000100,00020,000 Summer50,000100,00070,000 Fall120,000100,00050,000 Winter150,000100,0000 400,000140,000 Cost of Level Production Strategy (400,000 X $2.00) + (140,00 X $.50) = $870,000 SALESPRODUCTION QUARTERFORECASTPLANINVENTORY

68. Copyright 2009 John Wiley & Sons, Inc.14-68 Chase Demand Strategy Spring80,00080,00080020 Summer50,00050,00050030 Fall120,000120,000120700 Winter150,000150,000150300 10050 SALESPRODUCTIONWORKERSWORKERSWORKERS SALESPRODUCTIONWORKERSWORKERSWORKERS QUARTERFORECASTPLANNEEDEDHIREDFIRED Cost of Chase Demand Strategy (400,000 X $2.00) + (100 x $100) + (50 x $500) = $835,000

69. Copyright 2009 John Wiley & Sons, Inc.14-69 Items Product lines or families Individual products Components Manufacturing operations Resource Level Plants Individual machines Critical work centers Production Planning Capacity Planning Resource requirements plan Rough-cut capacity plan Capacity requirements plan Input/ output control Sales and Operations Plan Master production schedule Material requirements plan Shop floor schedule All work centers Hierarchical Nature of Planning  Disaggregation: process of breaking an aggregate plan into more detailed plans

70. Copyright 2009 John Wiley & Sons, Inc.14-70 Collaborative Planning  Sharing information and synchronizing production across supply chain  Part of CPFR (collaborative planning, forecasting, and replenishment)  involves selecting products to be jointly managed, creating a single forecast of customer demand, and synchronizing production across supply chain

71. Copyright 2009 John Wiley & Sons, Inc.14-71 Available-to-Promise (ATP)  Quantity of items that can be promised to customer  Difference between planned production and customer orders already received  Capable-to-promise  quantity of items that can be produced and made available at a later date ATP in period 1 = (On-hand quantity + MPS in period 1) – (CO until the next period of planned production) ATP in period n = (MPS in period n ) – (CO until the next period of planned production)

72. Copyright 2009 John Wiley & Sons, Inc.14-72 ATP: Example

73. Copyright 2009 John Wiley & Sons, Inc.14-73 ATP: Example (cont.)

74. Copyright 2009 John Wiley & Sons, Inc.14-74 ATP: Example (cont.) ATP in April = (10+100) – 70 = 40 ATP in May = 100 – 110 = -10 ATP in June = 100 – 50 = 50 = 30 = 0 Take excess units from April

75. Chapter 15 – ERP & Material Requirements Planning  Inventory for Dependent Demand

76. MRP is applied mostly to  Project operations  Batch operations  Assembly line operations  Continuous operations

77. What is the relationship between MRP and LEAN (JIT—Kanbans)?  There is no relationship  MRP is used by older manufacturing firms  MRP is used for execution, LEAN for planning  MRP is used for planning, LEAN for execution

78. Material requirements planning is a system for  Computing EOQ’s  Determining when to release orders  Computing safety stocks  Determining service levels WHICH????

79. MRP consists of four steps— which is not one of the four? 1. Exploding the BOM 2. Netting out inventory 3. Checking to insure sufficient capacity exists 4. Lot sizing 5. Time-phasing requirements

80. Formulas/Rules  Projected on-hand = prev projected on-hand + scheduled receipts + planned order receipts – gross requirements  Is really the on-hand amount at the end of the period  If less than zero, set to zero  Net requirements = gross requirements – prev projected on-hand - scheduled receipts  If less than zero, set to zero  Planned order receipts must be sufficient to accommodate the net requirements  Why don’t we just use net requirements for this??  Planned order releases are the same in amount as planned order receipts, just offset one or more periods by the lead time

81. MRP led to….. MRP II, which led to…. which led to…. which led to which is where we are today

82. Lean Production – Chapter 16  Doing more with less inventory, fewer workers, less space  Just-in-time (JIT)  Muda  waste, anything other than that which adds value to the product or service

83. Waste in Operations

84. Waste in Operations (cont.)

86. Basic Elements 1. Flexible resources 2. Cellular layouts 3. Pull production system 4. Kanban production control 5. Small lot production 6. Quick setups 7. Uniform production levels 8. Total productive maintenance 9. Supplier networks

87. Flexible Resources  Multifunctional workers  perform more than one job  general-purpose machines perform several basic functions  Cycle time  time required for the worker to complete one pass through the operations assigned  Takt time  paces production to customer demand

88. Standard Operating Routine for a Worker

89. Cellular Layouts  Manufacturing cells  comprised of dissimilar machines brought together to manufacture a family of parts  Cycle time is adjusted to match takt time by changing worker paths

90. Cells with Worker Routes

91. Worker Routes Lengthen as Volume Decreases

92. Pull System  Material is pulled through the system when needed  Reversal of traditional push system where material is pushed according to a schedule  Forces cooperation  Prevent over and underproduction  While push systems rely on a predetermined schedule, pull systems rely on customer requests

93. Kanbans  Card which indicates standard quantity of production  Derived from two-bin inventory system  Maintain discipline of pull production  Authorize production and movement of goods

94. Sample Kanban

95. Origin of Kanban a) Two-bin inventory systemb) Kanban inventory system Reordercard Bin 1 Bin 2 Q - R Kanban R R Q = order quantity R = reorder point - demand during lead time

96. Types of Kanban  Production kanban  authorizes production of goods  Withdrawal kanban  authorizes movement of goods  Kanban square  a marked area designated to hold items  Signal kanban  a triangular kanban used to signal production at the previous workstation  Material kanban  used to order material in advance of a process  Supplier kanban  rotates between the factory and suppliers

100. The End

102. Ignore what follows

103. ERP  Large caps have been there and done that  Mid and small caps are getting there  The road to implementation has been rough

104. ERP Modules  Sales & distribution  Production & Materials Management  Quality management  Human resource management  Project management  Accounting and controlling/finance

105. Terms  Capacity  Efficiency  Bill of Material  Product structure File  Master Production File  Explosion  Expediting  Netting

106. More terms  Load profile  MRP II  CRP  ERP  Modular BOM  Utilization  Time bucket  Time fence  Order splitting

107. Errors 18.39 18.39 – 12.24 12.24 – 6.12 6.12 – 0 0 – -6.12 -6.12 – -12.24 -12.24 – -18.39 -18.39 – ||||||||||||| 0123456789101112 Period UCL = +3  LCL = -3 

109. Sales and Operations Planning: Capacity Planning and Aggregate Production Planning  Long Range Planning  Medium Range Planning  Aggregate Production Planning

110. What are the inputs to the aggregate planning system??  Demand forecasts  Capacity constraints  Strategic objectives  Company policies  Financial constraints  NOT…  Size of workforce  Inventory levels  Units subcontracted  Overtime scheduled

111. Capacity planning is….  Long-term strategic decision-making  What facilities located where, built exactly when????  NOT Capacity requirements planning

112. Aggregate Production Planning Strategies are….  Pure (Trial-and-error)  Chase Demand  Level production  Mixed (optimal)  Linear programming  Simulation

113. Which of the following strategies matches production to demand by hiring and firing workers?  Chase demand strategies  Level production strategies  Strategies that use subcontracting and overtime

114. Which of the following is not a strategy for managing demand  Shifting demand into other time periods with incentives, sales promotions and advertising campaigns  Offering products or services with counter- cyclical demand patterns  Partnering with suppliers to reduce information distortion along the supply chain  Increasing inventories and laying off workers when demand is soft

115. Aggregate production planning provides input to which of the other planning processes?  Input/Output Control  Shop flow schedule  Material requirements plan  Forecasting  Capacity requirements plan

116. The planned order releases are outputs from what planning process ?  Input/Output Control  Shop flow schedule  Material requirements plan  Forecasting  Capacity requirements plan