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MS 401 Production and Service Systems Operations Spring 2009-2010

MS 401 Production and Service Systems Operations Spring 2009-2010. Master Production Scheduling (MPS) Slide Set #9. The MPC Framework. Sales and operations planning (Aggregate planning). Resource planning. Demand management. Rough-cut capacity planning. Front End.

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MS 401 Production and Service Systems Operations Spring 2009-2010

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  1. MS 401 Production and Service Systems Operations Spring 2009-2010 Master Production Scheduling (MPS) Slide Set #9

  2. The MPC Framework Sales and operations planning (Aggregate planning) Resource planning Demand management Rough-cut capacity planning Front End Master production scheduling (MPS) Detailed capacity planning Detailed material planning (using MRP) Engine Material and capacity plans Shop floor systems Supplier systems Back End

  3. The MPS Activity • MPS converts the disaggregated APP into a specific manufacturing schedule • specifying quantities and timing • Provides the information by which sales and manufacturing are coordinated • tool for agreement between marketing and operations • allows proactive control of the ability to deliver goods to customers • MPS is not a forecast. It specifies products to be completed. Different from forecast, MPS considers

  4. Links between APP and MPS • MPS is the translation of the APP into producible products with their quantities and timing determined • APP: Balance supply and demand volume • MPS: Specify the mix and volume of output Month January February March Output 200 300 400 APP January (weeks) 1 2 3 4 Model-RX 25 25 25 25 Model-TX 35 40 Model-SX 12 13 MPS

  5. Three Production Environments • Make-to-Stock: MPS stated in end-item terms. Products wait customer order in finished goods inventory. • Assemble-to-Order: MPS stated in an some average end item, product module or option. Components are manufactured and placed into inventory, then assembled when the order is received. • Make-to-Order: MPS stated in specific customer orders. Production begins after the customer order is received.

  6. Three Production Environments MTS ATO MTO # final products # subassemblies # raw materials / basic components MPS FAS MPS FAS FAS: Final Assembly Schedule

  7. Developing an MPS

  8. Inputs & Outputs • Required inputs: • forecast and customer orders (quantity, due dates) • beginning inventories (balances and planned receipts) • lot sizes and lead times • production capacity (output rate, planned downtime) • Outputs: (time phased) • projected inventory • the timing and size of MPS quantities • available-to-promise inventory (uncommitted inventory)

  9. The Time-Phased Record • Consistent with MRP format • “Forecasts” originate from disaggregation of APP • Why maintain inventory? • forecast error • MPS is only a plan which may not be achieved • Available = Available from previous period + MPS - Forecast

  10. Example 1: Level Strategy • Total demand forecast for the planning horizon is 164 units • The company wishes to have 10 units in inventory at the end of the planning horizon • Level production = (164 + 10 - 30) / 8 = 18 units/week

  11. Example 1: Level Strategy • Total demand forecast for the planning horizon is 164 units. • The company wishes to have 10 units in inventory at the end of the planning horizon • Level production = (164 + 10 - 30) / 8 = 18 units/week

  12. Example 1: Level Strategy • Total demand forecast for the planning horizon is 164 units. • The company wishes to have 10 units in inventory at the end of the planning horizon • Level production = (164 + 10 - 30) / 8 = 18 units/week

  13. Example 2: Stock-out Problem • Total demand the same as Example 1, however, this time high demand occurs in the earlier weeks

  14. Example 2: Stock-out Problem • Level strategy causes stock-outs in weeks 5 and 6

  15. Example 3: Chase Strategy • Chase strategy: Chase the demand • Same data as Example 1 • The company wishes at least 10 items to be available at the end of each week

  16. Example 3: Chase Strategy • Same data as Example 1 • The company wishes at least 10 items to be available at the end of each week

  17. Example 3: Chase Strategy • Same data as Example 1 • The company wishes at least 10 items to be available at the end of each week

  18. Example 4: Lot Sizing • Lot Sizing with Q = 48, Reorder Level = 15

  19. Example 4: Lot Sizing • Lot Sizing with Q=48, Reorder Level = 15 • Available inventory would drop below 15 at the end of week 2

  20. Example 4: Lot Sizing • Lot Sizing with Q=48, Reorder Level = 15 • Available inventory would drop below 15 at the end of week 2 • produce Q=48 units in week 2

  21. Example 4: Lot Sizing • Lot Sizing with Q=48, Reorder Level = 15 • Available inventory would drop below 15 at the end of week 4

  22. Example 4: Lot Sizing • Lot Sizing with Q=48, Reorder Level = 15 • Available inventory would drop below 15 at the end of week 4 • produce Q=48 units in week 4

  23. Example 5: Updating the MPS • Refer to the ordering schedule of Example 4 • Assume that week 1 demand realizes as 20 units • rather than the original forecast of 15 units • Furthermore, forecasts for weeks 2 thru 8 were revised and a forecast for week 9 was issued • The current MPS (without update) result in:

  24. Example 5: Updating the MPS • Revise the current schedule • shift the MPS of 48 in week 6 to week 5 • include other MPS of 48 in weeks 7 and 9 • In real life: Capacity constraints and costs of changing the production schedule should also be considered

  25. Order Promising

  26. Order Promising • Using the MPS for processing customer orders • determine when shipments can be made for customer orders • the company can buffer uncertainties in demand by delivery date promises • The “available” row (under order promising) is updated as Available = • Available-to-Promise (ATP): Calculated for the current period and for each period that has an MPS quantity Current period ATP = Subsequent periods’ ATP (in which there is MPS) =

  27. Example 6: Order Promising • Refer to Example 4 • Orders row: Backlog of orders at the beginning of the week • that is, promises for shipment (promise already made, not a forecast) • Available row: Expected ending inventory

  28. Example 6: Order Promising • ATP(1) = 30 -14 = 16 • ATP(2) = 48 - (8 + 7) = 33 • Note that the “forecast” and “available” rows are not used in ATP calculation (except the current period)

  29. Example 7: ATP and MPS Updating • Refer to Examples 5 & 6 • Additional orders were received during week 1: 6 units for week 1, 2 units for week 2, 3 units for week 3, 6 units for week 4 • Week 1 is now over, proceed to the beginning of week 2 • Forecasts, available values and MPSs have been updated • Available (at the beginning of week 2) = 30 – (14 + 6) = 10 • ATP(2) = (48 + 10) - (10 + 10) = 38

  30. Example 8: ATP and MPS Updating • Refer to Example 7 • Assume that an order of 55 units was booked for week 7 • This example illustrates how the ATP calculations need to be modified when ATP in a period is not sufficient to cover orders • First, update the availability levels

  31. Example 8: ATP and MPS Updating • Because the availability levels are below 15 in week 8, we update the MPS and availability levels for this week • a new MPS value of 48 is scheduled for week 8 and week 9 MPS is cancelled (Recall that the replenishment rule was to produce Q=48 units when the ending inventory in a week falls below R=15)

  32. Example 8: ATP and MPS Updating • Next, update the ATP values. Out of the ordered quantity 55, 48 will be satisfied from week 7 ATP. Hence ATP(7) is updated to be 0 • The rest of the order (55-48=7 units) will be satisfied from ATP(5) and hence, ATP(5) = 48 - (55 - 48) = 41 • Note that the “later” customer orders are covered starting with the “later” ATPs (week 7) to preserve the flexibility of early promises

  33. Example 9: Considering a Set of Orders • Refer to Example 7 (not to Example 8 !!) Can we accept the following set of customer orders, received in the following sequence? • Order #1 • Order #2 • Order #3 • Order #4

  34. Example 9: Considering a Set of Orders For this example, assume that we do not react to availability levels falling below 15 (and hence, we do not update the MPS) • Accept Orders #1, #2, and #3 and update the ATPs • ATP(2) = 10+48 –(35+10)- (56 - 48) = 5 < 10 (Order #4) • Hence,

  35. Example 9: Considering a Set of Orders • Assume the customer who placed Order #4 will not accept partial shipment and we were able to negotiate for delivery in week 5 • If no more orders were received in week 2 and a forecast of 25 for week 10 was issued, the time-phased record at the beginning of week 3 will look like: ATP(3) = 23 - 10 - (56 - 48) = 5

  36. MPS Stability • Trade-off between • too many changes: reduced productivity • too few changes: poor customer service and increased inventory • Strike a balance where stability is monitored and managed • Three techniques to achieve MPS stability • firm planned order treatment • an order that the MPS system does not automatically change in timing or in quantity. • changed only by the responsible person’s (planner’s) action • frozen time periods • time fencing

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