Demand profile

The aggregated scheduling problem is subject to uncertainties in the following parameters (1) the capacity of the polymerization stage, i.e., a possibly reduced availability of polymerization reactors due to equipment failures, and (2) the demand profiles. 

Identify demand profiles for qualitative personnel planning... 

The utilisation and the on/off cycles of a CHP system affect its potential benefit. Furthermore, higher overall efficiency leads to lower fuel consumption, while longer lifetimes lead to lower annualised capital costs. Concerning the relative influence of the demand profile, the nominal electric capacity, the efficiency and the lifetime of AFC, PAFC, PEMFC and SOFC systems, target costs were found to lie in a rather wide range. 

The Application of Near-Term Fossil Technologies to the Energy Sup-ply/Demand Profiles of U.S. States and Regions", U.S. Department of Energy, January 1977, FE/2442. 

This technique is useful for analyzing workload, allocating tasks, and determining human and system performance requirements. When the resource requirements for each lower-level task are mapped to the timeline, the result is a dynamic task-demand profile. 

As already described for phytic acid, also adding amino acids to feed has an economical as well as an ecological impact. The most relevant feed plants are soy and corn. Their profile of essential amino acids - and that of other plant materials as well - does not meet exactly the livestock s essential amino acid demand profile. Since the animals eat feed-protein until the demand of the most limited amino acid is filled the remaining overflow of other amino acids cannot be transformed into body mass. It is excreted. Consequently liquid manure of... 

In order to set up a data session between two terminals, some CSCF must be traversed by call session requests and answers. As a consequence, the number of sessions handled by a single CSCF server per time unit is chosen as a performance measure of a signalling network. The problem of meeting typical requirements for a telecommunication network in terms of service availability is faced by adopting parallel redundancy technique for network elements, given a demand profile. 

Field in logistics- Position- Tasks- Demand Profile requirement... 

In figure 4 the different power demand profiles (15-minute integration values) of each of these days are shown. Almost the same quantity of raw meal was produced (namely 7 000 tons a day) during each of the two days. But, as a matter of fact, on the 11th of April the raw mill consumed US 835 more energy than on the 29th of April. (US 835 is based on an average cost of 5 cents per KWh). 

Figure 5 shows how much energy is consmned when production is zero. This graph shows the demand profiles of three of snch zero-production days. For better comparison, the same power scale as in the graphs of figure 4 is chosen. 

To quantify via these theories the improvement in expected pfd for a diverse safety system, one would need to specify both the difficulty for every demand, and the demand profile. Difficulty functions will normally be impossible to estimate for real projects (although a posteriori difficulty estimates have been obtained [1, 15] for some toy applications where many different versions were developed [12]). In addition, if the safety system is used in different operational contexts, the demand profile might also be different and this can change the expectedpfds. 

In this paper we examine an approach for a more modest, but still useful, goal of estimating the worst case improvement in average pfd, by deriving a worst case demand profile that only requires knowledge about two points on the difficulty function rather that characterizing the whole function. 

The mean pfd% of a single program pfdi) and of common failure for a pair of diverse programs (pfdf) depend on the difficulty function x) and the demand profile p x). For a difficulty function x), the expected pfd of a single program version is ... 

Clearly the mean pfd depends upon the demand profile p x) as well as the demand difficulty 6 x). In the next section we use this dependence on the demand profile to derive the worst case value of pfd2 for a given value of pfd. ... 

We compare the expected pfd for this system with that of a single-version (i.e., non-diverse) system used in the same function (hence with the same demand profile). 

Here, we examine demand profile and competitive profile as drivers of logistics strategy ... 

Demand profile. Usually, high volume products are associated with comparatively low variety (few skus) and low demand variability and uncertainty. Examples are washing powders in retail, and volume cars like Ford and VW s big sellers. Note that demand variability can be created by means of promotions. Low volume, high variety products - such as most automotive spare parts, and many health and beauty products - tend to have the opposite demand profiles. 

Observe that monthly production remains the same, but both inventories and stockouts (backlogs) go up compared to the aggregate plan in Table 8-4 for the demand profile in Table 8-2. The cost of meeting the new demand profile in Table 8-5 is higher, at 433,080 (compared to 422,660 for the previous demand profile in Table 8-2). 

An advantage of reasoning with claims of fault-freeness is that they define lower bounds on long-term reliability, irrespective of the use (demand profile) to which the item will be subjected. 

With the inclusion of in Equation 5.15, the economic feasibility of the BTS in aU potential scenarios is assessed. Each fraction of occurrence represents the time fraction of which a scenario occurs. This time fraction is calculated by dividing the duration of a scenario s with the total duration (time horizon) considered. Thus, the sum of these fractions must equal to one as shown in Equation 5.16. Note that the duration of scenario s is dependent on the raw material supply and energy demand profiles. For instance, if the raw material supply and energy demand profiles are uniform in terms of duration (e.g. hourly, weekly, monthly basis, etc.), the time fraction of occurrence for scenario s can be obtained as shown in Figure 5.2a. As for dynamic profiles where supply and demand profiles are not uniform, the duration of scenario s can be broken down to smaller intervals and obtained as shown in Figure 5.2b. With this consideration, optimization constraints between scenarios can be established. Such feature is useful when deahng with seasonal variations. In practice, these fractions can be estimated subjectively based on the historical and projected information in variations of raw material supply, energy demand, product prices, etc. 

---