2. © 2011 Pearson Education, Inc. publishing as Prentice Hall Aggregate Planning The objective of aggregate planning is to meet forecasted demand while minimizing cost over the planning period

3. © 2011 Pearson Education, Inc. publishing as Prentice Hall The Planning Process  Objective is to minimize cost over the planning period by adjusting  Production rates  Labor levels  Inventory levels  Overtime work  Subcontracting rates  Other controllable variables Determine the quantity and timing of production for the intermediate future

4. © 2011 Pearson Education, Inc. publishing as Prentice Hall Aggregate Planning  A logical overall unit for measuring sales and output  A forecast of demand for an intermediate planning period in these aggregate terms  A method for determining costs  A model that combines forecasts and costs so that scheduling decisions can be made for the planning period Required for aggregate planning

5. © 2011 Pearson Education, Inc. publishing as Prentice Hall Planning Horizons Figure 13.1 Long-range plans (over one year) Research and Development New product plans Capital investments Facility location/expansion Intermediate-range plans (3 to 18 months) Sales planning Production planning and budgeting Setting employment, inventory, subcontracting levels Analyzing operating plans Short-range plans (up to 3 months) Job assignments Ordering Job scheduling Dispatching Overtime Part-time help Top executives Operations managers Operations managers, supervisors, foremen ResponsibilityPlanning tasks and horizon

6. © 2011 Pearson Education, Inc. publishing as Prentice Hall Aggregate Planning Quarter 1 JanFebMar 150,000120,000110,000 Quarter 2 AprMayJun 100,000130,000150,000 Quarter 3 JulAugSep 180,000150,000140,000

7. © 2011 Pearson Education, Inc. publishing as Prentice Hall Aggregate Planning Figure 13.2

8. © 2011 Pearson Education, Inc. publishing as Prentice Hall Aggregate Planning  Combines appropriate resources into general terms  Part of a larger production planning system  Disaggregation breaks the plan down into greater detail  Disaggregation results in a master production schedule

9. © 2011 Pearson Education, Inc. publishing as Prentice Hall Aggregate Planning Strategies 1.Use inventories to absorb changes in demand 2.Accommodate changes by varying workforce size 3.Use part-timers, overtime, or idle time to absorb changes 4.Use subcontractors and maintain a stable workforce 5.Change prices or other factors to influence demand

10. © 2011 Pearson Education, Inc. publishing as Prentice Hall Aggregate Planning Options Table 13.1 OptionAdvantagesDisadvantagesSome Comments Changing inventory levels Changes in human resources are gradual or none; no abrupt production changes. Inventory holding cost may increase. Shortages may result in lost sales. Applies mainly to production, not service, operations. Varying workforce size by hiring or layoffs Avoids the costs of other alternatives. Hiring, layoff, and training costs may be significant. Used where size of labor pool is large.

11. © 2011 Pearson Education, Inc. publishing as Prentice Hall Aggregate Planning Options Table 13.1 OptionAdvantagesDisadvantagesSome Comments Varying production rates through overtime or idle time Matches seasonal fluctuations without hiring/ training costs. Overtime premiums; tired workers; may not meet demand. Allows flexibility within the aggregate plan. Sub- contracting Permits flexibility and smoothing of the firm’s output. Loss of quality control; reduced profits; loss of future business. Applies mainly in production settings.

12. © 2011 Pearson Education, Inc. publishing as Prentice Hall Aggregate Planning Options Table 13.1 OptionAdvantagesDisadvantagesSome Comments Using part- time workers Is less costly and more flexible than full-time workers. High turnover/ training costs; quality suffers; scheduling difficult. Good for unskilled jobs in areas with large temporary labor pools. Influencing demand Tries to use excess capacity. Discounts draw new customers. Uncertainty in demand. Hard to match demand to supply exactly. Creates marketing ideas. Overbooking used in some businesses.

13. © 2011 Pearson Education, Inc. publishing as Prentice Hall Aggregate Planning Options Table 13.1 OptionAdvantagesDisadvantagesSome Comments Back ordering during high- demand periods May avoid overtime. Keeps capacity constant. Customer must be willing to wait, but goodwill is lost. Many companies back order. Counter- seasonal product and service mixing Fully utilizes resources; allows stable workforce. May require skills or equipment outside the firm’s areas of expertise. Risky finding products or services with opposite demand patterns.

14. © 2011 Pearson Education, Inc. publishing as Prentice Hall Methods for Aggregate Planning  A mixed strategy may be the best way to achieve minimum costs  There are many possible mixed strategies  Finding the optimal plan is not always possible

15. © 2011 Pearson Education, Inc. publishing as Prentice Hall Mixing Options to Develop a Plan  Chase strategy  Match output rates to demand forecast for each period  Vary workforce levels or vary production rate  Favored by many service organizations

16. © 2011 Pearson Education, Inc. publishing as Prentice Hall Mixing Options to Develop a Plan  Level strategy  Daily production is uniform  Use inventory or idle time as buffer  Stable production leads to better quality and productivity  Some combination of capacity options, a mixed strategy, might be the best solution

17. © 2011 Pearson Education, Inc. publishing as Prentice Hall Graphical Methods  Popular techniques  Easy to understand and use  Trial-and-error approaches that do not guarantee an optimal solution  Require only limited computations

18. © 2011 Pearson Education, Inc. publishing as Prentice Hall Graphical Methods 1.Determine the demand for each period 2.Determine the capacity for regular time, overtime, and subcontracting each period 3.Find labor costs, hiring and layoff costs, and inventory holding costs 4.Consider company policy on workers and stock levels 5.Develop alternative plans and examine their total costs

19. © 2011 Pearson Education, Inc. publishing as Prentice Hall Roofing Supplier Example 1 Table 13.2 MonthExpected Demand Production Days Demand Per Day (computed) Jan9002241 Feb7001839 Mar8002138 Apr1,2002157 May1,5002268 June1,100 2055 6,200124 = = 50 units per day 6,200 124 Average requirement = Total expected demand Number of production days

20. © 2011 Pearson Education, Inc. publishing as Prentice Hall Roofing Supplier Example 1 Figure 13.3 70 – 60 – 50 – 40 – 30 – 0 – JanFebMarAprMayJune=Month  221821212220=Number of working days Production rate per working day Level production using average monthly forecast demand Forecast demand

21. © 2011 Pearson Education, Inc. publishing as Prentice Hall Mathematical Approaches  Useful for generating strategies  Transportation Method of Linear Programming  Produces an optimal plan  Management Coefficients Model  Model built around manager’s experience and performance  Other Models  Linear Decision Rule  Simulation

22. © 2011 Pearson Education, Inc. publishing as Prentice Hall Summary of Aggregate Planning Methods Techniques Solution ApproachesImportant Aspects Graphical methods Trial and error Simple to understand and easy to use. Many solutions; one chosen may not be optimal. Transportation method of linear programming OptimizationLP software available; permits sensitivity analysis and new constraints; linear functions may not be realistic. Table 13.8

23. © 2011 Pearson Education, Inc. publishing as Prentice Hall Summary of Aggregate Planning Methods Techniques Solution ApproachesImportant Aspects Management coefficients model HeuristicSimple, easy to implement; tries to mimic manager’s decision process; uses regression. SimulationChange parameters Complex; may be difficult to build and for managers to understand. Table 13.8

24. © 2011 Pearson Education, Inc. publishing as Prentice Hall Aggregate Planning in Services Controlling the cost of labor is critical 1.Accurate scheduling of labor-hours to assure quick response to customer demand 2.An on-call labor resource to cover unexpected demand 3.Flexibility of individual worker skills 4.Flexibility in rate of output or hours of work

25. © 2011 Pearson Education, Inc. publishing as Prentice Hall Five Service Scenarios  Restaurants  Smoothing the production process  Determining the optimal workforce size  Hospitals  Responding to patient demand

26. © 2011 Pearson Education, Inc. publishing as Prentice Hall Five Service Scenarios  National Chains of Small Service Firms  Planning done at national level and at local level  Miscellaneous Services  Plan human resource requirements  Manage demand

27. © 2011 Pearson Education, Inc. publishing as Prentice Hall Law Firm Example Table 13.9 Labor-Hours Required Capacity Constraints (2)(3)(4)(5)(6) (1)ForecastsMaximumNumber of Category ofBest LikelyWorstDemand inQualified Legal Business(hours)(hours)(hours)PeoplePersonnel Trial work1,8001,5001,2003.64 Legal research4,5004,0003,5009.032 Corporate law8,0007,0006,50016.015 Real estate law1,7001,5001,3003.46 Criminal law3,5003,0002,5007.012 Total hours19,50017,00015,000 Lawyers needed393430

28. © 2011 Pearson Education, Inc. publishing as Prentice Hall Five Service Scenarios  Airline industry  Extremely complex planning problem  Involves number of flights, number of passengers, air and ground personnel, allocation of seats to fare classes  Resources spread through the entire system

29. © 2011 Pearson Education, Inc. publishing as Prentice Hall Yield Management Allocating resources to customers at prices that will maximize yield or revenue 1.Service or product can be sold in advance of consumption 2.Demand fluctuates 3.Capacity is relatively fixed 4.Demand can be segmented 5.Variable costs are low and fixed costs are high

30. © 2011 Pearson Education, Inc. publishing as Prentice Hall Demand Curve Yield Management Example Figure 13.5 Passed-up contribution Money left on the table Potential customers exist who are willing to pay more than the $15 variable cost of the room, but not $150 Some customers who paid $150 were actually willing to pay more for the room Total $ contribution =(Price) x (50 rooms) =($150 - $15) x (50) =$6,750 Price Room sales 100 50 $150 Price charged for room $15 Variable cost of room

31. © 2011 Pearson Education, Inc. publishing as Prentice Hall Total $ contribution = (1st price) x 30 rooms + (2nd price) x 30 rooms = ($100 - $15) x 30 + ($200 - $15) x 30 = $2,550 + $5,550 = $8,100 Demand Curve Yield Management Example Figure 13.6 Price Room sales 100 60 30 $100 Price 1 for room $200 Price 2 for room $15 Variable cost of room

32. © 2011 Pearson Education, Inc. publishing as Prentice Hall Yield Management Matrix Duration of useTend to be Uncertainpredictable Price Tend to be fixedTend to be variable Quadrant 1:Quadrant 2: MoviesHotels Stadiums/arenasAirlines Convention centersRental cars Hotel meeting spaceCruise lines Quadrant 3:Quadrant 4: RestaurantsContinuing care Golf courseshospitals Internet service providers Figure 13.7

33. © 2011 Pearson Education, Inc. publishing as Prentice Hall Making Yield Management Work 1.Multiple pricing structures must be feasible and appear logical to the customer 2.Forecasts of the use and duration of use 3.Changes in demand

34. © 2011 Pearson Education, Inc. publishing as Prentice Hall Figure 14.1 Change production plan? Master production schedule Management Return on investment Capital Engineering Design completion Aggregate production plan Procurement Supplier performance Human resources Manpower planning Production Capacity Inventory Marketing Customer demand Finance Cash flow The Planning Process

35. © 2011 Pearson Education, Inc. publishing as Prentice Hall The Planning Process Figure 14.1 Is capacity plan being met? Is execution meeting the plan? Change master production schedule? Change capacity? Change requirements? No Execute material plans Execute capacity plans Yes Realistic? Capacity requirements plan Material requirements plan Master production schedule

36. © 2011 Pearson Education, Inc. publishing as Prentice Hall Dependent Demand For any product for which a schedule can be established, dependent demand techniques should be used

37. © 2011 Pearson Education, Inc. publishing as Prentice Hall Dependent Demand Benefits of MRP 1.Better response to customer orders 2.Faster response to market changes 3.Improved utilization of facilities and labor 4.Reduced inventory levels

38. © 2011 Pearson Education, Inc. publishing as Prentice Hall Dependent Demand  The demand for one item is related to the demand for another item  Given a quantity for the end item, the demand for all parts and components can be calculated  In general, used whenever a schedule can be established for an item  MRP is the common technique

39. © 2011 Pearson Education, Inc. publishing as Prentice Hall Dependent Demand 1.Master production schedule 2.Specifications or bill of material 3.Inventory availability 4.Purchase orders outstanding 5.Lead times Effective use of dependent demand inventory models requires the following

40. © 2011 Pearson Education, Inc. publishing as Prentice Hall Master Production Schedule (MPS)  Specifies what is to be made and when  Must be in accordance with the aggregate production plan  Inputs from financial plans, customer demand, engineering, supplier performance  As the process moves from planning to execution, each step must be tested for feasibility  The MPS is the result of the production planning process

41. © 2011 Pearson Education, Inc. publishing as Prentice Hall Master Production Schedule (MPS)  MPS is established in terms of specific products  Schedule must be followed for a reasonable length of time  The MPS is quite often fixed or frozen in the near term part of the plan  The MPS is a rolling schedule  The MPS is a statement of what is to be produced, not a forecast of demand

42. © 2011 Pearson Education, Inc. publishing as Prentice Hall Aggregate Production Plan MonthsJanuaryFebruary Aggregate Production Plan1,5001,200 (Shows the total quantity of amplifiers) Weeks12345678 Master Production Schedule (Shows the specific type and quantity of amplifier to be produced 240-watt amplifier100100100100 150-watt amplifier500500450450 75-watt amplifier300100 Figure 14.2

43. © 2011 Pearson Education, Inc. publishing as Prentice Hall Master Production Schedule (MPS) 1.A customer order in a job shop (make-to- order) company 2.Modules in a repetitive (assemble-to-order or forecast) company 3.An end item in a continuous (stock-to- forecast) company Can be expressed in any of the following terms:

44. © 2011 Pearson Education, Inc. publishing as Prentice Hall Focus for Different Process Strategies Stock to Forecast (Product Focus) Schedule finished product Assemble to Order or Forecast (Repetitive) Schedule modules Make to Order (Process Focus) Schedule orders Examples:Print shopMotorcyclesSteel, Beer, Bread Machine shopAutos, TVsLightbulbs Fine-dining restaurantFast-food restaurantPaper Typical focus of the master production schedule Number of inputs Number of end items Figure 14.3

45. © 2011 Pearson Education, Inc. publishing as Prentice Hall MRP Structure Figure 14.5 Output Reports MRP by period report MRP by date report Planned order report Purchase advice Exception reports Order early or late or not needed Order quantity too small or too large Data Files Purchasing data BOM Lead times (Item master file) Inventory data Master production schedule Material requirement planning programs (computer and software)

46. © 2011 Pearson Education, Inc. publishing as Prentice Hall MRP in Services  Some services or service items are directly linked to demand for other services  These can be treated as dependent demand services or items  Restaurants  Hospitals  Hotels

47. © 2011 Pearson Education, Inc. publishing as Prentice Hall Uncooked linguini #30004 Sauce #30006 Veal #30005 MRP in Services Chef; Work Center #1 Helper one; Work Center #2 Asst. Chef; Work Center #3 Cooked linguini #20002 Spinach #20004 Prepared veal and sauce #20003 (a) PRODUCT STRUCTURE TREE Veal picante #10001 Figure 14.10

48. © 2011 Pearson Education, Inc. publishing as Prentice Hall MRP in Services (b) BILL OF MATERIALS Part NumberDescriptionQuantity Unit of Measure Unit cost 10001Veal picante1Serving— 20002Cooked linguini1Serving— 20003Prepared veal and sauce1Serving— 20004Spinach0.1Bag0.94 30004Uncooked linguini0.5Pound— 30005Veal1Serving2.15 30006Sauce1Serving0.80

49. © 2011 Pearson Education, Inc. publishing as Prentice Hall MRP in Services (c) BILL OF LABOR FOR VEAL PICANTE LaborHours Work CenterOperationLabor TypeSetup TimeRun Time 1Assemble dishChef.0069.0041 2Cook linguiniHelper one.0005.0022 3Cook veal and sauce Assistant Chef.0125.0500

50. © 2011 Pearson Education, Inc. publishing as Prentice Hall Short-Term Scheduling Short-term schedules translate capacity decisions, aggregate planning, and master schedules into job sequences and specific assignments of personnel, materials, and machinery

51. © 2011 Pearson Education, Inc. publishing as Prentice Hall Importance of Short-Term Scheduling  Effective and efficient scheduling can be a competitive advantage  Faster movement of goods through a facility means better use of assets and lower costs  Additional capacity resulting from faster throughput improves customer service through faster delivery  Good schedules result in more dependable deliveries

52. © 2011 Pearson Education, Inc. publishing as Prentice Hall Scheduling Issues  Scheduling deals with the timing of operations  The task is the allocation and prioritization of demand  Significant issues are  The type of scheduling, forward or backward  The criteria for priorities

53. © 2011 Pearson Education, Inc. publishing as Prentice Hall Scheduling Decisions OrganizationManagers Must Schedule the Following Arnold Palmer Hospital Operating room use Patient admissions Nursing, security, maintenance staffs Outpatient treatments University of Missouri Classrooms and audiovisual equipment Student and instructor schedules Graduate and undergraduate courses Lockheed Martin factory Production of goods Purchases of materials Workers Hard Rock CafeChef, waiters, bartenders Delivery of fresh foods Entertainers Opening of dining areas Delta Air LinesMaintenance of aircraft Departure timetables Flight crews, catering, gate, ticketing personnel Table 15.1

54. © 2011 Pearson Education, Inc. publishing as Prentice Hall Figure 15.1 Scheduling Flow

55. © 2011 Pearson Education, Inc. publishing as Prentice Hall Forward and Backward Scheduling  Forward scheduling starts as soon as the requirements are known  Produces a feasible schedule though it may not meet due dates  Frequently results in buildup of work-in- process inventory Due Date Now

56. © 2011 Pearson Education, Inc. publishing as Prentice Hall Forward and Backward Scheduling  Backward scheduling begins with the due date and schedules the final operation first  Schedule is produced by working backwards though the processes  Resources may not be available to accomplish the schedule Due Date Now

57. © 2011 Pearson Education, Inc. publishing as Prentice Hall Forward and Backward Scheduling  Backward scheduling begins with the due date and schedules the final operation first  Schedule is produced by working backwards though the processes  Resources may not be available to accomplish the schedule Due Date Now Often these approaches are combined to develop a trade-off between a feasible schedule and customer due dates

58. © 2011 Pearson Education, Inc. publishing as Prentice Hall Different Processes/ Different Approaches Process-focused facilities Forward-looking schedules MRP due dates Finite capacity scheduling Work cellsForward-looking schedules MRP due dates Detailed schedule done using work cell priority rules Repetitive facilitiesForward-looking schedule with a balanced line Pull techniques for scheduling Product-focused facilities Forward-looking schedule with stable demand and fixed capacity Capacity, set-up, and run times known Capacity limited by long-term capital investment Table 15.2

59. © 2011 Pearson Education, Inc. publishing as Prentice Hall Scheduling Criteria 1.Minimize completion time 2.Maximize utilization of facilities 3.Minimize work-in-process (WIP) inventory 4.Minimize customer waiting time Optimize the use of resources so that production objectives are met

60. © 2011 Pearson Education, Inc. publishing as Prentice Hall Scheduling Process-Focused Facilities  Schedule incoming orders without violating capacity constraints  Check availability of tools and materials before releasing an order  Establish due dates for each job and check progress  Check work in progress  Provide feedback  Provide work efficiency statistics and monitor times

61. © 2011 Pearson Education, Inc. publishing as Prentice Hall Planning and Control Files 1.An item master file contains information about each component 2.A routing file indicates each component’s flow through the shop 3.A work-center master file contains information about the work center Planning Files Control Files Track the actual progress made against the plan

62. © 2011 Pearson Education, Inc. publishing as Prentice Hall Loading Jobs  Assign jobs so that costs, idle time, or completion time are minimized  Two forms of loading  Capacity oriented  Assigning specific jobs to work centers

63. © 2011 Pearson Education, Inc. publishing as Prentice Hall Input-Output Control  Identifies overloading and underloading conditions  Prompts managerial action to resolve scheduling problems  Can be maintained using ConWIP cards that control the scheduling of batches

64. © 2011 Pearson Education, Inc. publishing as Prentice Hall Input-Output Control Example Week Ending6/66/136/206/277/47/11 Planned Input280 Actual Input270250280285280 Cumulative Deviation–10–40 –35 Planned Output320 Actual Output270 Cumulative Deviation–50–100–150–200 Cumulative Change in Backlog 0–20–10+5 Figure 15.2 Work Center DNC Milling (in standard hours)

65. © 2011 Pearson Education, Inc. publishing as Prentice Hall Input-Output Control Example Work Center DNC Milling (in standard hours) Week Ending6/66/136/206/277/47/11 Planned Input280 Actual Input270250280285280 Cumulative Deviation–10–40 –35 Planned Output320 Actual Output270 Cumulative Deviation–50–100–150–200 Cumulative Change in Backlog 0–20–10+5 Explanation: 270 input, 270 output implies 0 change Explanation: 250 input, 270 output implies –20 change Figure 15.2

66. © 2011 Pearson Education, Inc. publishing as Prentice Hall Input-Output Control Example Options available to operations personnel include: 1.Correcting performances 2.Increasing capacity 3.Increasing or reducing input to the work center

67. © 2011 Pearson Education, Inc. publishing as Prentice Hall Gantt Charts  Load chart shows the loading and idle times of departments, machines, or facilities  Displays relative workloads over time  Schedule chart monitors jobs in process  All Gantt charts need to be updated frequently to account for changes

68. © 2011 Pearson Education, Inc. publishing as Prentice Hall Gantt Load Chart Example Figure 15.3 Day MondayTuesdayWednesdayThursdayFriday Work Center Metalworks Mechanical Electronics Painting Job 349 Job 408 ProcessingUnscheduledCenter not available Job 350 Job 349 Job 295

69. © 2011 Pearson Education, Inc. publishing as Prentice Hall Gantt Schedule Chart Example Figure 15.4 Job Day 1 Day 2 Day 3 Day 4 Day 5 Day 6 Day 7 Day 8 A B C Now Maintenance Start of an activity End of an activity Scheduled activity time allowed Actual work progress Nonproduction time Point in time when chart is reviewed

70. © 2011 Pearson Education, Inc. publishing as Prentice Hall Assignment Method  A special class of linear programming models that assigns tasks or jobs to resources  Objective is to minimize cost or time  Only one job (or worker) is assigned to one machine (or project)

71. © 2011 Pearson Education, Inc. publishing as Prentice Hall Assignment Method  Build a table of costs or time associated with particular assignments Typesetter JobABC R-34$11$14$ 6 S-66$ 8$10$11 T-50$ 9$12$ 7