Intended learning outcomes: Explain an example of order-oriented finite loading. Present an evaluation of the technique. Identify its limitations and typical areas of application.
Continuation from previous subsection (14.3.2)
Figure 14.3.2.2 shows the results of order-oriented finite loading after the first iteration, using exception rule (c). This example uses the same orders as in Figures 14.2.1.1 and 14.3.1.2, specifically P1, . . . , P6, and the same work centers, namely, work center A and work center B. Priority was assigned in ascending order by order ID. Again, “preload” represents operations for orders that were loaded before orders P1, . . . , P6.
Fig. 14.3.2.2 Example of order-oriented finite loading, exception rule (c): unloading.
Exception rule (b) would have produced results similar to those in Figure 14.3.1.2, that is, similar to operations-oriented finite loading. The more that exception rule (a) is applied or capacities are increased in the last step, the more infinite loading is obtained.
The following prerequisites must be met to use this planning technique:
- Capacities and loads must be sufficiently reliable, that is, the planning data and reported work progress must “tally.” Errors can accumulate very rapidly in the calculated dates if this is not the case.
- Due dates must be sufficiently flexible — especially for exception rule (b). The order completion date results randomly on the basis of the existing utilization of production capacity. Lead times can sometimes be much longer than normal.
- Exception rules (a) and (c) are suitable for order due dates that are relatively inflexible. For these, however, the capacities must have some flexibility; otherwise, the administrative effort needed to regularly change dates would become unmanageable or so imprecise that capacities would be poorly utilized.
This creates the following limitations:
- The farther we plan into the future, the smaller our chances that the planning forecasts will prove correct. For this reason, the technique is only sufficiently exact for short planning horizons, and it must be repeated at regular intervals.
- In long-term planning, the technique calculates a permissible plan, in the full knowledge that it will change in the short term. Regular and efficient replanning is thus needed as the term becomes shorter.
- In short-term planning, for exception rule (b), any scheduled operations must once again be completed during this period. The technique does not allow local, reactive replanning. Exception rules (a) and (c) do, however, allow some potential degrees of freedom for reaction if capacity is not fully utilized.
- Exception rule (b) leads to the best possible utilization of capacity. As with operations-oriented finite loading, long queues may arise. Goods in process then tie up capital and even hold up the entire production plant. Choosing a “neutral” priority rule will distribute the delay more or less evenly among all the orders.
- Exception rule (c) loads production only with the orders that it is capable of processing. It thus results in lower levels of work-in-process and shorter lead times. Successfully planned orders are completed on time. Exception rule (c) essentially uses the model of the queue presented in Section 13.2.1, that is, the reservoir or open funnel model. If the funnel does not overflow, the production plant will not be held up. Thus, if further processing of an order is delayed excessively (e.g., over at least one time period), it should be rejected, rather than loaded.
- With inflexible capacity, on the other hand, exception rule (c) leads to lower utilization of capacity as soon as completion dates have to be deferred. This is because the load that would have been caused by operations earlier along the time axis is now missing. If there are no other orders, the capacity is wasted. Deferred orders will have long delays, and it may even become impossible to accept new orders.
- If the time between the earliest start date and the latest completion date is longer than the required lead time, then a start date and an end date that falls between these two extremes may be more suitable for the overall mix of orders. It is worth considering the load-oriented order release and capacity-oriented materials management (Corma) techniques outlined in Sections 15.1.2 and 15.1.3. Load-oriented order release, in particular, can actually be regarded as a generalization of order-oriented finite loading with exception rule (c).
- Interactive planning, that is, order by order, is only efficient if relatively little effort is needed to load an order compared to its value added. In addition, we need continuous knowledge of the total load on the work center resulting from previous orders, so that a very fast database is required. We also have to keep load totals for each time period. To create sufficiently simple and rapid algorithms, the length of the time periods for each work center and along the time axis must then be defined as fixed.
Typical areas of application are as follows:
- As with operations-oriented finite loading, exception rule (b) is suitable for batch production over a long period or in a monopoly situation or seller’s market. Typical industries here are chemical and food processing industries and niche capital goods markets.
- Exception rules (a) and (c) are suitable for many discrete manufacturing industries, wherever there is the minimum required level of flexible capacity. This is more often the case than we might at first suppose, even in short-term planning.
- For short-term planning and control. For this planning range, the technique provides, firstly, with exception rule (b), an actual work program for the next few days, and, secondly, with exception rules (a) and (c), an acceptable work program that also allows a degree of situational planning. The horizontal bar chart provides a rapid overview of all work centers and all orders, as it requires little space. It corresponds to the familiar planning board in production control. Individual orders can often be replanned very efficiently — in the case of the electronic control board (Leitstand), through the click of the mouse.
- For long-term planning of few orders with high value-added and regular planning and replanning. For replanning individual orders, the advantages are again the clear display and ease of manipulation mentioned above.
Course section 14.3: Subsections and their intended learning outcomes
14.3 Finite Loading
Intended learning outcomes: Explain operations-oriented, order-oriented, and constraint-oriented finite loading.
14.3.1 Operations-Oriented Finite Loading, or Operations Sequencing
Intended learning outcomes: Produce an overview on the technique (the algorithm) for operations-oriented finite loading, also called operations sequencing. Describe various priority rules.
14.3.1b Operations-Oriented Finite Loading — Example and Evaluation
Intended learning outcomes: Explain an example of operations-oriented finite loading. Present an evaluation of the technique. Identify its limitations and typical areas of application.
14.3.2 Order-Oriented Finite Loading
Intended learning outcomes: Produce an overview on the technique (the algorithm) for order-oriented finite loading. Describe various priority rules as well as dealing with exceptions.
14.3.2b Order-Oriented Finite Loading — Example and Evaluation
Intended learning outcomes: Explain an example of order-oriented finite loading. Present an evaluation of the technique. Identify its limitations and typical areas of application.
14.3.3 Constraint-Oriented Finite Loading
Intended learning outcomes: Identify bottleneck capacities and the drum-buffer-rope technique. Describe the drum, the buffer, and the rope. Present an evaluation of the technique. Identify its limitations and typical areas of application.
