Integral Logistics Management — Operations Management and Supply Chain Management Within and Across Companies

5.2.3 Master Scheduling and Rough-Cut Capacity Planning

Intended learning outcomes: Produce an overview on master scheduling and planning time fence. Present in detail the master production schedule (MPS) as a disaggregated version of the production plan. Explain the tasks for establishing a master production schedule. Describe the process of rough-cut capacity planning (RCCP).



Sales and operations planning works mainly with product families, that is, at an aggregate level of information. However, there will be a need for more specific information for individual products.

The corresponding planning process at the level of the individual product is called master scheduling.[note 513]

The most important output of master scheduling is the master production schedule.

A master production schedule (MPS) is the disaggregated version of a production plan, expressed in specific products, configurations, quantities, and dates.

Figure 5.2.3.1 shows an example of an MPS as derived from a production plan (shown here only for the first four months of a year).

Fig. 5.2.3.1        The MPS as a disaggregated version of the production plan (an example of a product family P with three different products, P1, P2, P3).

As the figure shows, the MPS is not only more detailed for individual products rather than product families, but it also yields much more detail for the time period for which the quantities are aggregated. It is thus a link between the production plan, which is relatively close to the sales plan, and the products the manufacturing department will actually build. The MPS is the input to all planning actions in the shorter term.

The planning time fence corresponds to the point in time denoted in the planning horizon of the master scheduling process that marks a boundary inside of which changes to the schedule may adversely affect customer deliveries, component schedules, capacity plans, and cost ([APIC16]).[note 514]

Planned orders outside the planning time fence can be changed automati­cally by the planning logic of a software. Inside the time fence, the master scheduler, that is the person charged with the responsibility of managing the master schedule for select items, must deal with changes manually.

Establishing a master production schedule entails a number of tasks:

First task: Selection of the master schedule items, that is, the items managed by the master scheduler and not by the computer. Taking the example in Figure 5.2.3.1, if the difference between the products of the family P is due to three different variants of a subassembly (namely, V1, V2, and V3) and if the delivery lead time allows assembling to customer order, then the best choice for the (customer) order penetration point (OPP) is the subassembly level. The final products P1, P2, and P3 are then produced to customer order, according to the final assembly schedule (FAS) (see Section 7.1.5). If the usage quantity is 2 for each variant, then Figure 5.2.3.2 shows the MPS corresponding to the production plan.

Fig. 5.2.3.2        The MPS on the level of subassemblies V1, V2, and V3.

Second task: Break down the production plan quantity for a product family into quantity for each product of the family. We often do not know the exact percentage for splitting the total product family demand into individual product or variant demands. To cover this uncertainty, we increase the percentage of each variant. This percentage is called the option percentage (see here Section 10.5.3). This procedure results in overplanning, which yields protection in the form of safety demand. Figure 5.2.3.3 shows example overplanning in the MPS, assuming an uncertainty of 20 %.

Fig. 5.2.3.3        The MPS for the first four weeks on the level of subassemblies V1, V2, V3, including overplanning due to variant uncertainty.

This safety demand is in effect safety stock, or reserved stock, for the entire planning horizon to be covered. For details, see Section 10.5.4. The safety demand has to be planned at the beginning of the planning horizon. If the forecast indicates a large demand in one of the subsequent periods, the additional safety demand can be planned for that planning period. Figure 5.2.3.4 shows the first overplanning for January. An additional overplanning takes place for March, but only for the part that is not already overplanned in January.

Fig. 5.2.3.4        The MPS on the level of subassemblies V1, V2, and V3, including safety demand (due to variant uncertainty) during the planning horizon.

For the rest of the planning period, the safety stock in the system corresponds to the safety demand for the maximal monthly demand. Because of the general uncertainty in the system, it is sometimes easier to plan the whole quantity at the start of the planning period. A coordinated final assembly schedule (FAS, see Section 7.1.5) maintains the service level at 100 %, meaning that consumption of the subassemblies stays within the limits of the safety stock. For more details, the reader may refer to Section 7.2, where it is also explained that this kind of master scheduling is valid only as long as the number of variants to be planned in the MPS is significantly lower than the total demand quantity for the product family. Other­wise, a (customer) order penetration point (OPP) more upstream must be chosen.

Third task: Verify the feasibility of the MPS by rough-cut capacity planning.

Rough-cut capacity planning (RCCP) is the process of converting the master production schedule into required capacity, that is, capacity of (key) resources to produce the desired output in the particular periods. Comparison to available or demonstrated capacity (with regard to feasibility) is usually done for each key resource ([APIC16]).

As the planning is more detailed, RCCP yields more precise information on the work centers and the capacities to be used than does resource requirements planning (RRP). It therefore allows more precise control of the feasibility of the production plan. Figure 5.2.3.5 shows the (average) load of the MPS in comparison to the weekly (average) capacity of a work center called WC-A.

Fig. 5.2.3.5        RCCP on the level of subassemblies V1, V2, and V3: load and capacity on work center WC-A.

For balancing load with capacity, the following strategies are possible:

  • The chase production method maintains a stable inventory level that corresponds to load. To do this, (quantitatively) flexible capacity — as is the case in Figure 5.2.3.5 — is a must.
  • The level production method maintains a level schedule (a master production schedule that generates a load that is spread out more evenly over the time period) corresponding to capacity. This can go as a far as requiring linearity, or the production of a constant quanti­ty (or the consumption of a constant quantity of resources) in every period (such as daily). Figure 5.2.3.6 shows a possible solution.

Fig. 5.2.3.6        RCCP on the level of subassemblies V1, V2, and V3: load and capacity on work center WC-A, load leveled.

  • Hybrid production method: Companies can combine chase and level production methods.
  • It is a question of an overstated master production schedule. The quantities are greater than the ability to produce, given current capacity and material availability (cf. [APIC16]). The MPS has to be modified.

Figure 5.2.3.6 shows that load leveling is a time-consuming procedure even for just one work center. Finite loading algorithms, often developed within operations research (such as linear program­ming), have to be used. In the face of the degree of uncertainty of the (mostly forecast-based) production plan as well as of the demand breakdown from the family level to the level of individual products, it is often not worth putting too much effort into more detailed calculation. If there is (as in our example) a 20 % uncertainty in the distribution of the demand of the family among the single products or subassemblies, a deviation of 10 % of the average capacity (as in Figure 5.2.3.5) is probably precise enough. Investing great efforts in detailed calculation will often be useless at this level of planning. In contrast, the importance of investing in (quantitatively) flexible capacities increases with a growing degree of variability of the product concept.

In more complicated cases, the MPS must divide the production plan into individual production or procurement lots. Then, just as in medium-term planning, net requirements planning over the time axis, rather than gross requirements planning, is needed. An example of this is long-term planning that aims explicitly to achieve high-capacity utilization, particularly in the process industry. In that case, RCCP (rough-cut capacity planning) seems to be a good solution:

  • Quick calculation of alternative order quantities or sub­divisions in part orders with shifted completion dates is possible.
  • The number of planning variables is small, and sometimes the whole plan can be displayed on a large monitor. This provides ex­cel­lent support to the human ability to make situation-appropriate decisions intuitively even when the data are incom­plete and imprecise. These intuitive decisions take into account a multitude of nonquantifiable factors and implicit knowledge. This is a very important aspect of future-oriented forecasting techniques. Knowledge about the development of a forecast can influence our evalua­tion of planning results, particularly interpretations of capacity overload and underload.

See Section 14.4 for a detailed description of rough-cut capacity planning techniques.




Course section 5.2: Subsections and their intended learning outcomes

  • 5.2 Master Planning — Long-Term Planning

    Intended learning outcomes: Describe demand management, sales and operations planning as well as resource requirements planning. Explain master scheduling and rough-cut capacity planning. Disclose supplier scheduling: blanket order processing, release, and coordination.

  • 5.2.1 Demand Management: Bid and Customer Blanket Order Processing and Demand Forecasting

    Intended learning outcomes:: Describe demand management, customer bid, order success probability and customer blanket order. Present some aspects of demand forecasting.

  • 5.2.2 Sales and Operations Planning and Resource Requirements Planning

    Intended learning outcomes: Present the concepts of sales plan, production plan, procurement plan, inventory policy, inventory plan, and aggregate plan. Explain sales and operations planning as an iterative master planning process. Disclose an example of iterative planning by comparing three production plans, with zero, two or four changes in production rhythm per year.

  • 5.2.3 Master Scheduling and Rough-Cut Capacity Planning

    Intended learning outcomes: Produce an overview on master scheduling and planning time fence. Present in detail the master production schedule (MPS) as a disaggregated version of the production plan. Explain the tasks for establishing a master production schedule. Describe the process of rough-cut capacity planning (RCCP).