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

5.2.3c Rough-Cut Capacity Planning (RCCP)

Intended learning outcomes: Describe the third task for establishing a master production schedule, which is the process of rough-cut capacity planning (RCCP).

Continuation from previous subsection (5.2.3b)

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 ([ASCM22]).

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 shows the (average) load of the MPS in comparison to the weekly (average) capacity of a work center called WC-A.

Fig.        RCCP on the level of assemblies 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, flexible capacity — as is the case in Figure — 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 shows a possible solution.

Fig.        RCCP on the level of assemblies 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. [ASCM22]). The MPS has to be modified.

Figure 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 assemblies, a deviation of 10 % of the average capacity (as in Figure 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 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