1. Rough-Cut Capacity Planning in SCM EGN 5623 Enterprise Systems Optimization (Professional MSEM) Fall, 2012

2. Rough-Cut Capacity Planning in SCM Theories & Concepts EGN 5623 Enterprise Systems Optimization (Professional MSEM) Fall, 2012

3. Hierarchical Planning Framework (review) Procurement Production DistributionSales Long term -Material programs - Supplier selection - Cooperation - Plant location - Production systems - Subcontractors - Physical distribution structure - Transportation strategy - Product program - Strategic sales planning -- Personnel training -- Contracts -- Material Requirements Planning -- Master production Scheduling -- Capacity planning-- Distribution planning-- Mid-term sales planning Mid term -- Personnel scheduling -- Material ordering -- lot-sizing - operations scheduling - shop floor control - Warehouse replenishment - Transportation planning-- Mid-term sales planning Short term EXECUTION InformationFeedback Flow of goods

4. The APICS-Standard Planning Framework (review)

5. Production Process (review) Requirements for Production Planning: to meet the demand to consider the resource capacities and the material availabilities to improve utilisation of the resources to lower the setup time to minimize the stock, and to minimize the work in process (WIP) to improve stability of the plan

6. Rough-cut Capacity Planning The main goal in rough-cut capacity planning is to identify where overloading or under-loading of production capacity occurs and revise the MPS as required. Overloading means that too much production of products has been planned in the facility and insufficient capacity exists to produce planned quantities of products required in MPS. Under-loading means that not enough production of products has been planned to fully load the facility.

7. Rough-Cut Capacity Planning in APO-SNP

8. Order Life Cycle for Make-to-Stock

9. Order Life Cycle for Make-to-Order

10. Forecast Consumption Mode and Horizon (Backword consumption of 4 days and a forward consumption of 3 days)

11. Transactional Data for Transferring Starting from a demand plan, SNP checks the resource capacities and delivers a medium/long-term plan for the estimated sales volumes. The plan includes the quantities to be transported between locations (e.g., DC-customer, or plant-DC) and the quantities to be produced (and procured), taking available capacity into consideration. SNP creates planned orders, purchase requisitions, and stock transfers that can be transferred directly to the connected OLTP systems.

12. Capacity Levelling Capacity leveling supports the following resource categories: Production resources Transportation resources Capacity levelling supports the following resource types: Bucket resources Single-mixed resources Multi-mixed resources Transportation resources

13. Capacity Levelling The planner can use the following methods to adjust the plan: Backward scheduling of the capacity load to fulfill demand using high priorities without due date violations. This rescheduling does not create any orders in the production horizon. Forward scheduling of the capacity load for lower priority demand and use of demand priorities to minimize due date violations A combination of backward and forward scheduling of the capacity load.

14. Capacity Levelling Profile The main settings in the capacity leveling profile are scheduling direction, prioritization, and method. Scheduling Direction controls whether Forward, Backward or Combined scheduling is used. Prioritization for the heuristic run defines how leveling determines the sequence of orders. The two possible choices for prioritization (to be sorted by ascending or descending order) are by order size or by product priority. The three Method choices are Heuristic, Optimizer or Badi (Business Aided-in).

15. Time-based Capacity Levelling

16. Capacity Levelling

17. Heuristics-based Capacity Levelling Heuristic-based capacity leveling compares, period by period, the capacity load on a resource with the requested load, either from the beginning or from the end of the planning horizon – depending on which scheduling direction is selected (forward or backward scheduling). If the resource is found overloaded, the system first selects all the activities or orders that cause the overload in this period. It then sorts these orders according to the priority that is defined and shifts orders or partial orders, one by one into subsequent or previous periods until the required maximum resource utilization is reached.

18. Heuristics-based Capacity Levelling For forward scheduling, the system moves the orders so far that the first activity using the resource to be leveled only begins after the overloaded period. For backward scheduling, the system moves the orders so far that the last activity using the resource to be leveled actually ends before the overloaded period. The system takes the lot sizes and rounding values defined in the master data into account when moving the orders.

19. SNP Heuristic as Location, Network, and Multi-Level Heuristic

20. Scheduling in SNP Heuristic

21. Period Factor

22. Production Scheduling for Multiple BOM Levels

23. Scheduling in CTM

24. Heuristics-based Capacity Levelling Only orders that cause overloads are changed. This proves advantageous when a lot of orders exist but only some of them overload the resource. Prioritization is done by product or by product quantity. Select “Capacity Leveling” from the menu to balance the required work loads.

25. Benefits of SNP with SCM The benefits of Supply Network Planning with SAP SCM are as follows: 1.Cross-plant medium-term rough-cut planning 2.Cross-plant optimization of resource utilization Simultaneous planning of procurement, production and distribution Simultaneous material planning and finite capacity scheduling of production, storage, and transportation resources 3.Planning of critical components and bottleneck resources 4.Prioritization of demands and receipts 5.Collaborative supply planning over the Internet

26. Linear Programming (LP) EGN 5623 Enterprise Systems Optimization (Professional MSEM) Fall, 2012 Linear Programming (LP) EGN 5623 Enterprise Systems Optimization (Professional MSEM) Fall, 2012

27. Operation Research (OR) Operation research refers to the application of quantitative methods and techniques to business problems in order to best utilize a company’s resources. OR is used by many leading companies in recent years to optimize their limited resources in order to maximize their profits or minimize their costs. Linear programming (LP) is one of the most important tools of operation research.

28. Linear Programming (LP) Five common types of LP problems: Product mixed Ingredient mix Transportation Production plan Assignment

29. Five common types of LP problems

30. Five common types of LP problems Five common types of LP problems

31. Steps in Formulating LP Problems 1.Define the objective 2.Define the decision variables 3.Write the mathematical function for the objective (objective function) 4.Write a one- or two-word description of each constraints 5.Write the right-hand side (RHS) of each constraint, including the unit of measure. 6.Write = for each equation 7.Write all the decision variables on the left-hand side of each constraints 8.Write the coefficient for each decision variable in each constraint.

32. Formulating LP

34. Formulation LP

35. Formulation of Problem

36. Objective and Constraints

37. Steps in Graphical Solution Method

38. Graphical Solution

42. Transportation (Network) Problem

43. Requirement Assumption

44. Feasible Solutions Property

45. Cost Assumption

46. Parameter Table for Transportation Problem Supply S 1 S 2. S m

47. Transportation Problem Model Any problems (whether involving transportation or not) fits the model for a transportation problem if it can be described completely in term of a parameter table like Table 8.5 and it satisfies both the requirements assumption and cost assumption. The objective is to minimize the total cost of distributing the units. All the parameters of the model are included in this parameter table.

48. Objective Function & Constraints

49. Rough-Cut Planning in SCM SAP Implementation EGN 5623 Enterprise Systems Optimization (Professional MSEM) Fall, 2012 Rough-Cut Planning in SCM SAP Implementation EGN 5623 Enterprise Systems Optimization (Professional MSEM) Fall, 2012

50. Planning Book and Views

51. Capacity Check view Now switch to the CAPACITY CHECK view. In the Selection profile section double click on ## RESOURCES. Double click on the work center (plant ##A1). Switch the TB Profile to 12MONTH. We appear to have enough capacity in the work center at the aggregated monthly level. Now change the TB Profile to 180 DAYS. We are overloaded in the first couple days as SCM has tried to produce all that is needed to satisfy safety stock in those days.

52. Capacity Levelling Scroll over to the next capacity usage. We are also overloaded in those periods. Multilevel Heuristic does not take capacity into consideration. Select

53. Key Figures and Category Group in SNP Standard Planning Book

54. 1. Please solve the following LP problem. Objective:Min Z = 10,000 X 1 + 15,000 X 2 S.T. X 1 + 2X 2 >= 4 X 1 + X 2 >= 2.5 1) Draw a graph 2) Plot the constraint function 3) Outline the feasible solution 4) Circle the optimal solution point. HW 6: Exercises:

55. 2. The Green Up Fertilizer Company ships fertilizer from three manufacturing plants to four distribution centers (DC). The shipping cost per truckload of fertilizer from each plant to each DC is: PlantDistribution Center (DC) ABCD 1$464$513$654$867 2$352$416$690$791 3$995$682$388$685 Plant 1 has a monthly capacity of 75 truckload, Plant 2 has a monthly capacity of 125 truckload, and the Plant 3 has a monthly capacity of 100 truckload. The monthly DC demand is A = 80 truckload, B = 65 truckload, C = 70 truckload, and D = 85 truckload. Please formulate an LP problem to determine how much truckload of fertilizer should be shipped from each plant to each DC per month to minimize monthly shipping cost. 1) Define the objective. 2) Define the decision variables. 3) Write the mathematical function for the objective. 4) Write the constraints. 5) Solve the LP problem