Cost-performance trade-off

Cost-Performance ratio Once a system is designed and capacity is planned, a cost model can be developed. From the performance evaluation and the cost model, we can make an analysis regarding cost-performance trade-offs. 

In addition, when selecting a material, it is important not simply to select the material with the lowest dielectric constant or dissipation factor, since there are typically cost-performance trade-offs to be made. In general, the lower the dielectric constant and dissipation factor, the more costly the material, and very often the more difficult it is to process. 

PLASTEC has also been heavily involved in standardization activities. In recent years, PLASTEC has been permitted to serve private industry. The significant difference between a library and technical evaluation center is the quality of the information provided to the user. PLASTEC uses its database library as a means to an end to provide succinct and timely information which has been carefully evaluated and analyzed. Examples of the activity include recommendation of materials, counseling on designs, and performing trade-off studies between various materials, performance requirements, and costs. Applications are examined consistent with current manufacturing capabilities, and the market availability of new and old materials alike is considered. PLASTEC specialists can reduce raw data to the user s specifications and supplement them with unpublished information that updates and refines published data. 

For the axis topology, the symmetric triaxial topology is particularly advantageous in the downhole environment due to the ease of differentiating between installation- and sensor-related noise (see Symmetric Triaxial Seismometers ). The four leveling methods each have cost and performance trade-offs which are summarized in Table 1. 

Increasingly, maintenance engineers think in terms of the performance and maintenance of equipment over the whole life of the field. This is often at the centre of the decision on capex-opex trade-offs for example spending higher capex on a more reliable piece of equipment in anticipation of less maintenance costs later in the life of the equipment. 

The process of updating the schedule is basically the same as that used in planning the shutdown. It is simply based on new information and deals only with the remaining portion of the shutdown. In some very large shutdowns, it may be desirable to perform time-cost trade-off analysis, resource leveling, etc., each time the shutdown CPM is updated. In many cases, however, the update will involve only the basic forward, backward and slack computations. These calculations will allow for development of a revised schedule. They will also identify the critical path that is likely to change over the course of the shutdown. 

Figure 9.3. The speed-accuracy trade-off (SATO) curve on performance of tasks with elements of both reaction time and accuracy. The black line shows that performance tends to be either slow and accurate or fast and error-prone. The dotted line depicts an impairement in performance as a shift in SATO this can be observed as a cost in either (a) both speed and accuracy, (b) predominantly speed or (c) predominantly accuracy.

Optimization pervades the fields of science, engineering, and business. In physics, many different optimal principles have been enunciated, describing natural phenomena in the fields of optics and classical mechanics. The field of statistics treats various principles termed maximum likelihood, minimum loss, and least squares, and business makes use of maximum profit, minimum cost, maximum use of resources, minimum effort, in its efforts to increase profits. A typical engineering problem can be posed as follows A process can be represented by some equations or perhaps solely by experimental data. You have a single performance criterion in mind such as minimum cost. The goal of optimization is to find the values of the variables in the process that yield the best value of the performance criterion. A trade-off usually exists between capital and operating costs. The described factors—process or model and the performance criterion—constitute the optimization problem. ... 

Fuel cell pressurization is typical of many optimization issues, in that there are many interrelated factors that can complicate the question of whether to pressurize the fuel cell. Pressurization improves process performance at the cost of providing the pressurization. Fundamentally, the question of pressurization is a trade-off between the improved performance (and/or reduced cell area) and the reduced piping volume, insulation, and heat loss compared to the increased parasitic load and capital cost of the compressor and pressure-rated equipment. However, other factors can further complicate the issue. To address this issue in more detail, pressurization for an MCFC system will be examined. 

Although it is difficult to determine the quantitative requirements of plate and plate materials appropriately for various fuel cells and different applications in a development phase, such a target would be helpful to direct the development effort and make necessary trade-offs. The cascaded performance requirement targets in 2010 and 2015 for bipolar plates of fuel cells in transportation applications were set by the U.S. DoE (Department of Energy) according to functions of the plate mentioned before and overall requirements of performance, reliability, manufacturability, and cost of a stack, as shown in Table 5.1 [7]. The technical target in the DoE s multiyear research, development, and demonstration plan has been popularly and worldwide... 

Remark 2 In Figure 8.20 we have discussed the optimization loop of HRAT. Specifying a value of H RAT allows the calculation of the minimum utility loads using the LP transshipment model, The optimization loop of HRAT had to be introduced so as to determine the optimal value of HRAT that gives the trade-off of operating and investment cost. Note, however, that in the approach of this section, in which we perform no decomposition at all, we do not specify the H RAT, but we treat the hot and cold utility loads as explicit unknown optimization variables. As a result, there is no need for the optimization loop of HRAT since we will determine directly the utility loads. 

Additionally, if cost differences between alternatives exist that were not considered in the network design phase, potential trade-offs between quantitative and qualitative performance of the alternatives should be analyzed. 

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