| Planning without iterations, an example |  |
| This example explains how item master plans are simulated when material and/or capacity constraints are considered and no iterations are used. Overview A chair is manufactured from a metal frame and a leather seat. The frame is manufactured from two metal pipes. In the planning, items with the following item codes are used: CHAIR FRAME METAL PIPE The frame and the metal pipe are defined as constraints. Initial situation In this example, a single plan period is considered. The following assumptions apply: The projected inventory of the previous plan period is zero for each item. The lead-time offsets involved are zero. The inventory plan for each item is zero. The Starting Point WLC field in the Work Load Control Parameters (cpwlc2101m000) session has been set to Current Master Plan. A previous simulation resulted in the following master plan data:
CHAIR
Demand (forecast) | 50
Production plan | 50
Projected inventory | 0
FRAME
Dependent demand | 50
Production plan | 50
Projected inventory | 0
METAL PIPE
Dependent demand | 100
Production plan | 100
Projected inventory | 0
Simulating the master plan Suppose that the actual demand for CHAIR turns out to be 60, thus surpassing the demand forecast. Moreover, the resource where METAL PIPE is produced is overloaded, so that actually only 80 pipes can be produced. Suppose further that the master plan is simulated while considering material and capacity constraints, but without using iterations. The simulation consists of a normal planning pass, in order of increasing phase number (this means: first the end item, then the component). The following table shows the results of the simulation run. The left column contains the existing master plan values; the right column shows the result of the simulation.
CHAIR | Old | New
Demand (forecast) | 50 | 50
Demand (actual) | 0 | 60
Production plan | 50 | 50
Projected inventory | 0 | -10
FRAME | Old | New
Dependent demand | 50 | 50
Production plan | 50 | 50
Projected inventory | 0 | 0
METAL PIPE | Old | New
Dependent demand | 100 | 100
Production plan | 100 | 80
Projected inventory | 0 | -20
Explanation: In the new simulation, the actual demand for CHAIR is used instead of the demand forecast (because the actual demand is higher). According to this higher demand, the production plan of CHAIR should be increased from 50 to 60. However, FRAME is a constraint in the planning of CHAIR, and because the projected inventory for FRAME is 0, the production plan for CHAIR is not increased. Because the production plan of CHAIR remains the same, the dependent demand for FRAME is not raised either. METAL PIPE is a constraint in the planning of FRAME. However, because the existing projected inventory for METAL PIPE is zero, the production plan for FRAME is not reduced. The limited production capacity for METAL PIPE only plays a role in the production plan for METAL PIPE. At the higher levels (which are planned earlier), the planning algorithm is not aware of the constraint posed on metal pipe production. The main advantage of not using iterations is that it makes the planning process relatively fast. However, as this example shows, constraint-based planning without iterations clearly has its limits. In some situations it can work well, especially if the following conditions apply: The structure of the bills of critical materials (BCMs) involved is fairly simple (not many levels, and usually only one critical component per item). The current master plan is used as the starting point for the workload-control algorithm. The master-plan data is updated regularly. Especially when the planning situation becomes more complicated (complex BCM structures, a high number of interdependencies between plan items), full optimization of the planning requires the use of iterations. For an explanation of the use of iterations, see Planning with iterations; for an example, see Planning with iterations, an example. Related topics Workload control Workload control, to plan against constraints Planning with iterations Planning with iterations, an example Workload control, to compute planning priorities |