Major cost variables

For most experiments, there seems to be no particular advantage in restricting the changes in system variables so that system performances can always be compared at equal values of power input in many cases there is not a clear relation between power input and performance. The major controllable variables are such factors as impeller and vessel diameter, and impeller speed it is the relation between these and system performance which must be discovered. Eventually, the power requirement becomes a factor in the usual engineering balance of cost versus level of performance. The experience of manufacturers of mixing equipment can be helpful when it is desired to know the power requirements for a system operating under specified conditions of size, impeller speed, etc. 

For on-site separation/purification of recovered solvent it is necessary to consider the number and complexity of distillations needed to obtain materials which are suitably pure for reuse. Where mixtures must be separated into individual solvents this can require several distillations, particularly where the solvents form azeotropes - this can significantly add to costs. The major costs associated with solvent purification are normally the capital required for distillation columns, energy and the additional staffing needs to oversee the operation. Where azeotropic distillations are required the cost of distillation columns can be greater than the capital cost of the recovery unit itself and staffing costs can be a significant variable cost (particularly if batch distillation is required). 

Table 1 shows that the major cost is for toluene. The overall conversion-of toluene in the base case is 99.3%, allowing a potential savings in toluene cost of approximately 140,000 per year. This savings would have only a minor inpact (approx. 0.003 per kg) on the differential break-even price of benzene therefore, the overall conversion of toluene is not considered a variable in the cases studied here. However, the hydrogen cost can be reduced significandy if a suitable separation technique can be found to purify the recycle gas. Streams 5 and 7. Of the remaining costs, the steam, fuel gas, and equipment are the most significant. 

Feed represents the major cost in any intensive system of animal production. Therefore, it is imperative to supply a diet adequate in terms of palatability and nutritional value, and one that prevents feed waste and reduces costs. Feed efficiency can be improved by as much as 10% to 20% by using the right method of grain processing. There is a wide array of processing methods used to affect these important variables. By far, milling is the most universal way to process cereals for animal feeds. 

These items are highly site specific. Power cost is low because the salinity removed by the selected plant is low. The quality of the feed water, its sahnity, turbidity, and concentration of problematic ionic and fouhng solutes, is a major variable in pretreatment and in conver-... 

The economics of such a system are very complex, and there are many variables that must be considered. Some of the major considerations are total installed cost, the load factor or capacity factor, the... 

To understand the mathematics, consider a large empty space into which a number of production units are to be placed, and assume that the major variable to be optimized is the cost of transporting materials between them. If the manufacturing process is essentially a flow-line operation, then the order in which units should be placed is clear (from the point of view of transport costs), and the problem is simply to fit them into the space available. In a job-shop, where materials are flowing between many or all the production units, the decision is more difficult. All the potential combinations of units and locations... 

There are methods to manipulate the backbones of polymers in several areas that include control of microstructures such as crystallinity, precise control of molecular weight, copolymerization of additives (flame retardants), antioxidants, stabilizers, etc.), and direct attachment of pigments. A major development with all this type action has been to provide significant reduction in the variability of plastic performances, more processes can run at room temperature and atmospheric pressure, and 80% energy cost reductions. 

Both techniques have their advantages and their limitations with respect to process time, process temperatures, and process costs. However, the crucial question is How much does crosslinking contribute to the desired properties of the material The performance of the final product is, of course, the major issue. A lot of information on crosslinked polymers is available in the literature. There have been several attempts in the past [1-7], and also more recently [8-10], to sort out this accumulation of scientific data. Yet, it is neither simple nor particularly rewarding to undertake such a venture due to the multitude of variables which make direct comparisons difficult, and to the incidence of apparent contradictions. 

The methods just presented can be used for any number of variables. However, optimizing all the possible variables of a plant in one massive optimization is a Herculean task. The usual approach is to reduce the number of variables to those that strongly affect the performance index. For instance, in the polystyrene example the cost of electricity is almost insignificant and can be ignored. However, the amount of water added to the reactor may be very important. An optimization is made for the major variables. Then the effects of the minor variables are considered either in groups or separately. 

The dilemmas raised by the genetics of the work are also considerable and are discussed elsewhere [4], A major difficulty is the choice of the appropriate genetic polymorphisms to associate to drug response. A statistical conundrum is created by the need to assess multiple variables that are partially related to one another (without a priori knowledge of the exact nature of such interactions) and that contribute to small effects in clinical trials that are highly costly and often cannot be as large as desired. 

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