Demand variations

Note that the mean /i (8) has a proportional influence on the standard deviation of the total ordered amount. The tendency is intuitive The formula means that only a few large orders require more safety stock to cover random demand variations than many small orders. It is therefore a good idea to measure the mean and the variance of demands twice. First in the usual way as mean and variance of a sequence of, say weekly, figures and then by analyzing the orders of a historic period and applying Eq. (6.6). The comparison of the two results obtained often provides insight in the independence and the randomness of the historic demand. If the deviation of the two mean values and/or two variances is large then the demand can not be considered as a random sum. A reason could be, for example, that the demand... 

As a second case, we study the 5/ and 5f 6d manifolds of l/ -doped Cs2ZrCl6, with two open-shell electrons [58]. Now, the manifolds contain a large number of electronic states and the general problems that will be faced all over the actinide series appear here. In particular, MS-CASPT2 methods will be used for dynamic correlation instead of demanding variational Cl based methods such as ACPF [82,83]. The calculations suggest several reassignments of the 5f-> 5f experimental spectrum [84,85], predict the 5f 6d levels, and support the... 

Electricity has a relatively low MES of capacity, especially since the advent of combined cycle gas turbines which are viable at levels of 250 MW (for example, compared with total UK installed capacity of around 78,000 MW (National Grid, 2007)). Annual demand variation is also much lower than for industrial commodities since a large part of demand is relatively insensitive to the state of the economy (heating, lighting, domestic use). 

It is common accepted knowledge that inventory hedges from price, availability, and demand variations, and their impact on the profitability of the operations. It is also known that maintaining such inventory has a cost, both capital and operative. That risk is automatically reduced is not necessarily true unless risk is managed specifically as is briefly shown next. Contrary to the assumption that operating at zero inventory (produce to order) always increases profit, it will be also shown that inventories do not represent a reduction in expected profit. 

An important part of external uncertainty is caused by customer demands. However, in basic chemical industry almost all final chemicals are produced to stock and, thus, are decoupled from direct market demands. Hence, variations of the customer demand do not affect the upstream production network immediately. Due to the exceptionally high re-start and changeover costs for plants, demand variations are mostly reflected by stock increases or sales price declines. The adaptation of production capacities by means... 

This example illustrates the benefit of thinking outside the box as defined by Industrial Chemicals and examining the root causes for order variation, i.e., the supply chain structure. But it also means moving to a bigger box, i.e., including more entities in the supply chain. The new perspective considers the link between demand variation and truck capacity driven by existing coordination agreements (backhaul discounts). The case shows the benefit... 

If the temporal demand levels can be forecast, then a dynamic adjustment of capacity to synchronize with demands may enable performance improvement without a significant increase in capacity levels. As an illustration, allocating employees to temporally sta ered shifts can be a mechanism to manage the impact of demand variation. 

Understand the business in order to read market signals and identify demand variations. 

As seen from Table 4, apparently the Ratio Rule and the LP Rule perform much better than the Nearest Rule. In addition, the relative performance of the heuristic rules seems insensitive to the variation of demand rate, although the system delivery cost does increase as the variation increases. In other words, demand variation will cause delivery costs to increase, but it will not necessarily cause poor transshipment decisions. Hence, our two new proposed heuristic rules appear robust. 

We find that the Nearest Rule, which is widely used, is not a wise approach for transshipment decision making. The LP Rule may be best for rare nonrealistic cost matrices. The Ratio Rule as we suggest is generally a much better substitute for the Nearest Rule. In addition, the performance of the Ratio Rule is robust to demand variation. 

The second level of control is a model predictive optimisation-based scheme that considers the entire network dynamics, embedding the inventory controllers of the first layer and a stochastic model for demand variation. 

Blowers, or positive-displacement fans, have the same common failure modes as rotary pumps and compressors. Table 13.4 lists the failure modes that most often affect blowers and fluidizers. In particular, blower failures occur due to process instability, caused by start/stop operation and demand variations, and mechanical failures due to close tolerances. 

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