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

15.1.2b Load-Oriented Order Release: Example and Evaluation

Intended learning outcomes: Explain the steps of load-oriented order release. Present an evaluation of the technique. Identify its limitations and typical areas of application.

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Continuation from previous subsection (15.1.2)

Figure 15.1.2.2 illustrates the steps using an example taken from [Wien95]. Assume that there are 5 orders to be added to an existing workload.

Fig. 15.1.2.2       Steps of load-oriented order release. (From: [Wien95]).

  • In step 1 (“scheduling”), these 5 orders are shown together with their operations on the time axis. Each operation bears the work center (A, B, C, D, respectively) that is intended to execute the operation. Each order has its scheduled start date. The time filter of Loor (in fact a time limit, calculated by a given anticipation horizon) eliminates each order where the start date of the first opera­tion is later than the time limit. In the example, the filter eliminates order 5, de­clared as not urgent. All other orders are declared as urgent and passed to step 2.
  • In step 2 (“conversion”), the load of subsequent operations is converted progressive­ly by the conversion factor, which in this example is 50%. That means that the load of the first operation is taken into consideration with 100%, the load of the second operation only with 50%, the load of the third operation only with 25%, and so on.[note 1502] In the graph, every order is now shown by its load profile (original and converted). The operations do not appear in the sequence of their execution, but in the sequence of the work center. This is done in preparation for the next step.
    Take — as an example — order 2. In Figure 15.1.2.2, the load of this order is shown with vertical shading (not only in step 2, but also in step 3). From step 1 we know that the first operation will be executed at work center B. Therefore, the load is shown in step 2, converted by 100% (that is, the full load). Again, step 1 shows that the second operation will be executed at work center C. Therefore, the load is shown in step 2, converted by 50% (that is, half the load). The empty load in the pillar (that is without shadings) corresponds to the other 50% of the load, which will not be taken into account for step 3. Again, step 1 shows that the second operation will be executed at work center C. Therefore, the load is shown in step 2, converted by 50% (that is, half the load). The empty “load” (that is, without shadings) corresponds to the other 50% of the load, which will not have been taken into account for step 3.
  • Step 3 (“release”) shows first the existing (pre-)load of all workstations before loa­ding the four new orders. This preload stems from different periods on the time axis. This is why it can be greater than the scheduled output capacity for one time period. Arbitrarily, then, a loading percentage of 200% is chosen.[note 1503] This yields the load limit for every work center. The orders are then loaded in the sequence of their start date.[note 1504] The load of every operation is added to the preload. As soon as an opera­tion has to be loaded on an already overloaded work center, the whole order is unloaded. Thus, the load limit has the effect of a load filter.
    In the example, the load filter accepts first orders 1 and 2, with order 2 overloading work center B slightly (the algorithm accepts the first overload for each work center. But work center B is now declared to be unavailable for all subsequent orders). It then eliminates and unloads order 3 because of already fully loaded capacity at work center B by order 2. Finally, the load filter accepts order 4, for which work center B is not used.[note 1505] Orders 1, 2, and 4 can thus be released, whereas Order 3 is non-feasible and becomes an item for a further step, when exceptions are dealt with.

There is no relationship between the conversion factor and the loading percentage, and the values should not be linked. However, in the original literature on Loor, these values often appear to be reciprocal. Furthermore, in practice, the values chosen for anticipation horizon, loading percentage, and the conversion factor are often based on experience or are arbitrary.

Case example: The Siemens Electronics Plant in Amberg, Germany, manufactures electro­nic components in customer-independent production to stock. The comprehensive range of components allows the customer to obtain the optimal configuration of programmable SIMATIC control and monitoring operator panels for automated systems. Approximately 500 components are manufactured and available for 24-hour delivery from stock. One production order consists of 10 to 20 operations. The number of machines in the area of load-oriented order release is 20. The main objective in implementing Loor was to limit work-in-process inventory, thus reducing lead times and releasing no orders for production for which capacity was not available. The Amberg Electronic Plant itself took over the task of programming the algorithm. Implementing Loor has brought the expected advantages.

Evaluation of the technique and organizational aspects:

  • The debate over this technique is highly polarized. Perhaps, this arises because Loor is too readily presented as generally valid and scientific, as if it were a statistical technique. Thus, the conversion factor is often compared to a probability measure. Critics can easily take this to the point of absurdity. They construct an extreme case in which Loor loads operations that have an execution probability of 0 (zero), but does not release more urgent operations. However, Loor is not an analytical techni­que; it is a simple heuristic, limited to just a few control parameters. As with every heuristic technique, its applicability will depend on an organization’s strategies.

For implementation of the Loor technique, the following prerequisites must be met:

  • Order due dates must be at least somewhat flexible to provide the scope for dealing with exceptions.
  • Capacities must be at least somewhat flexible. Other­wise, the administrative effort to make the numerous deadline alterations will be prohibitive, or the calculations so imprecise that the capacities are only poorly loaded.
  • It must be possible to determine the parameters of anticipation horizon, load percentage, and conversion factor in every organization empirically — in some cases through the aid of simulations. The parameters are dependent on the desired work level and the size of the chosen planning period.

The following limitations result:

  • Orders that fall outside the load limit are generally moved beyond the anticipation horizon, which may result in an unacceptable delay. Releases based on additional information (such as high external priority, rejections due to capacity overloads very far in the future, or similar information) are generally not provided for.
  • In the medium term, the available capacity or the capacity that has been made available must be at least as large as the load. Other­wise, more and more orders will fall outside the load limit.
  • Loor only loads production with orders that can be processed. It thus leads to low levels of work in process and to short lead times. Scheduled orders are finished on time. However, if the capacity is not flexible, the technique leads to low loading of capacity where completion dates must be pushed back in time. This is because the load that would have occurred far along on the time axis is now missing. If there are no other orders in line, the capacity is missed out (see also [Knol92]). In cases of underload, the parameter “anticipation horizon” must not be altered to make the best use of the available capacity. Other­wise, it will result in too early completion dates and possibly unneeded warehouse stocks.

The following areas lend themselves to application of the Loor technique:

  • in branches of discrete manufacturing, particularly when there is a need for simpli­city and robust­ness in the face of errors in planning dates or changes in order levels.
  • in short-term planning and control, load-oriented order release provides a reliable work program that permits a considerable degree of situational planning on the spot.
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Course section 15.1: Subsections and their intended learning outcomes

  • 15.1 Order Release
    15.1 Order Release

    Intended learning outcomes: Describe order proposals for production and procurement as well as order release. Explain load-oriented order release (Loor) and capacity-oriented materials management (Corma).

  • 15.1.1 Order Proposals, Order Release for Procurement and Production
    15.1.1 Order Proposals, Order Release for Procurement and Production

    Intended learning outcomes: Describe the reasons for order proposals for production or procurement. Differentiate between the dealing of order proposals for C items and of other items. Explain purchase order release. Explain production order release and describe the availability test of resources.

  • 15.1.1b Production Order Release: Allocation, Staging, Accompanying Documents and Container Logistics
    15.1.1b Production Order Release: Allocation, Staging, Accompanying Documents and Container Logistics

    Intended learning outcomes: Disclose issues linked with allocation and staging. Identify accompanying documents such as the traveling card and container logistics such as the two-bin inventory system.

  • 15.1.2 Loor — Load-Oriented Order Release
    15.1.2 Loor — Load-Oriented Order Release

    Intended learning outcomes: Produce an overview on the principle of the technique and the planning strategy. Describe the regulator analogy for load-oriented order release. Differentiate between time filter and load filter.

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