Intended learning outcomes: Describe the analysis of the load profile. Explain possible strategies for capacity planning, in case of a trend toward persistent overload or underload, or in case of frequent and infrequent self-compensating fluctuations. Differentiate between adapting capacity to load and load leveling. Present an evaluation of the technique. Identify its limitations and typical areas of application.
The cumulative illustration of loads and capacities along the time axis presented in Figure 14.2.3.1 is also suitable for analyzing the load profile. We can see the overload or underload along the vertical axis, between the curves for capacity and load. The maximum possible movement of the load in one or the other direction can also be seen along the horizontal axis.
Fig. 14.2.3.1 Analysis of the load profile.
The load profile displays easily, directly, and accurately the overload and underload that would arise if our scheduling assumptions were totally accurate. Everything covered up to this point is not capacity planning, strictly speaking. However, the farther into the future we can identify the overload or underload, the less it need occur in reality, since the calculated operation start dates may be incorrect as a result of upstream bottleneck capacities, unplanned reworking, or unplanned operations due to rush orders, for example.
In the simplest case, one response would be to (manually) plan to increase or reduce capacity. Figure 14.2.3.2 shows possible methods.
| 1 | Frequent self-compensating fluctuations, meaning that the interoperation times are longer than or roughly equal to the fluctuation frequency. No action is required. The time buffer can absorb these fluctuations without jeopardizing dates. | |
| 2 | Trend toward persistent overload: | |
| 2a | Long-term action (in the master planning): acquire additional production infrastructure (workers or machines) in good time. Other typical long-term responses are blanket orders to subcontractors, that is, sending production work outside the company (“extended workbench” or “outsourcing” principle) or arrangements with employment agencies (temporary workers). | |
| 2b | Short-term action: arrange overtime or implement long-term blanket agreements as mentioned above. | |
| 3 | Trend toward persistent underload: in principle, the action required is the opposite of that described under point 2. | |
| 3a | Long-term action: cut back production infrastructure or reduce blanket agreements (insourcing). | |
| 3b | Short-term action: cancel overtime, arrange short-time working, or cancel outsourced work. | |
| 4 | Infrequent self-compensating fluctuations, meaning that the interoperation times are shorter than the fluctuation frequency: | |
| 4a | Flexibly adapt capacity to load, alternating the steps described under points 2 and 3. For example, in the short-term case, this could mean arranging for and then cutting back on overtime. | |
| 4b | Load leveling, that is, spreading orders over time so that the amount of work tends to be distributed evenly, resulting in a level schedule. This measure is associated with inflexible capacity, however, and thus actually belongs to finite loading. With a computerized system, we can move an operation forward or back and immediately see the consequences in a revised load profile. However, we must also take into account the work centers for the upstream and downstream operations for the order. Overload situations may now arise at other work centers precisely because the order was moved. Since the completion date is not flexible, this may require considerable manual replanning, order by order. See also Section 14.2.4. |
Fig. 14.2.3.2 Infinite loading: methods for adapting capacity to load.
Finally, a list of available work supports analysis of the individual operations as well as priority control, that is, the communication of start and completion dates for execution in the shop floor.
Available work or work on hand or load traceability for a work center is a list of the operations to be carried out at that work center over a given time period.
This list is sorted according to a suitable strategy, which should also mirror the order in which the operations are carried out. Possible strategies include:
- Anticipated start date for the operation
- Operation time (SPT, shortest processing time rule)
- Order urgency (SLK, shortest slack time rule; see also Section 13.3.6)
- Order priority, that is, the preferred status of the customer
Evaluation of the technique: The following prerequisites must be satisfied before we can use planning methods for infinite loading:
- Capacities must be quantitatively flexible. Loads occur randomly according to the order situation. Replanning orders is time consuming and far too expensive given the often limited value-added.
- The technique only delivers good results if the collected shop floor data tracks work progress precisely. Also, no large load should lie in the past; otherwise, the backlog will be so great in the first period that the load profile no longer makes sense.
The following limitations also apply:
- The further we plan into the future, the lower the likelihood that the planning forecasts will be accurate; unforeseen breakdowns or variance in actual quantities will already affect accuracy. The technique merely predicts the probable capacity utilization so that sufficient capacity can be made available.
- The less that we know about the actual progress of the order, the more that actual control will have to be ad hoc on-site in response to the constantly changing dates and the mix of the orders.
The following are typical areas of application:
- For customer order production or where the mix of orders fluctuates, that is, in a buyer’s market. Today, this is typically the case in the manufacture of capital goods or in discrete production and services in almost any industry.
- For all planning periods, particularly the long term. For execution and control of operations, this does not provide a precise program of work, but rather acts as a basis for situational planning of capacities and priorities at the work floor level.
Course section 14.2: Subsections and their intended learning outcomes
14.2 Infinite Loading
Intended learning outcomes: Present load profile calculation and problems associated with algorithms for load profile calculation. Explain methods of balancing capacity and load. Describe order-wise infinite loading.
14.2.1 Load Profile Calculation
Intended learning outcomes: Explain an example of a work-center-load profile. Present an example of a load profile known as an overload or underload curve along the time axis.
14.2.2 Problems Associated with Algorithms for Load Profile Calculation
Intended learning outcomes: Describe the problem of calculating capacity per load period. Explain the problem of load assignment for one operation during the load periods. Present the issue of calculating the load in a given time period when various operations occur only partly within the time period.
14.2.3 Methods of Balancing Capacity and Load: Adapting Capacity to Load Rather Than Load Leveling
Intended learning outcomes: Describe the analysis of the load profile. Explain possible strategies for capacity planning, in case of a trend toward persistent overload or underload, or in case of frequent and infrequent self-compensating fluctuations. Differentiate between adapting capacity to load and load leveling. Present an evaluation of the technique. Identify its limitations and typical areas of application.
14.2.4 Order-Wise Infinite Loading
Intended learning outcomes: Describe order-wise infinite loading. Identify the suitability of order-wise infinite loading.
