Equipment Performance Assumptions

The list of equipment performance assumptions is presented in Table 9-5. 

The assumption of independence between hazards and safety instrumented function failures seems very realistic. (NOTE If control functions and safety functions are performed by the same equipment, the assumption may not be valid Detailed analysis must be done to insure safety in such situations, and it is best to avoid such designs completely.) When hazards and equipment are independent, it is realized that a hazard may come at any time. Therefore, international standards have specified that PFDavg is an appropriate metric for measuring the effectiveness of a safety instrumented function. 

When conducting for example a model-based risk analysis of a complex operation there are several assumptions made regarding the patient s reaction to the operation, its consequences, equipment performance, the team s competence etc. Some of these assumptions are typically built into models used in the analysis, while others can be controlled by the person conducting the analysis. The analysis produces numbers that depend on these assumptions. But some of these assumptions may turn out to be wrong, and consequently there are uncertainties that extend beyond the probability numbers. Important uncertainty factors can be hidden in the background knowledge K. 

There are many other assumptions made in the following analysis (these are stated where they are introduced) but despite their often obvious oversimplicity the final results give a reasonable estimate of equipment performance. The analysis is made for a simple tubular centrifuge but the same approach, with slight modifications, may be used for other types of sedimenting centrifuges. An attempt is first made to derive the whole grade efficiency... 

The physical description of the process described above is based on material balances and equipment performance equations, which incorporate the following key assumptions ... 

Many industrial crystallizers operate in a weU-mixed or nearly weU-mixed manner, and the equations derived above can be used to describe their performance. Furthermore, the simplicity of the equations describing an MSMPR crystallizer make experimental equipment configured to meet the assumptions lea ding to equation 44 useful in determining nucleation and growth kinetics in systems of interest. 

Clearly, the turboexpander is one of several key components in a process plant and liquid production is related to the performance of all components of the plant, not the turboexpander alone. It has previously been assumed that changes in the normal design conditions of turboexpanders have not adversely affected other equipment in the plant because adverse impact on other equipment, if any, would further reduce liquid production. This simplifies the assumptions, but does not affect the general validity of the findings. 

As Tribus, 1969, says, all probabilities are conditional. In the example of the dree, the probabilities are conditioned on the assumption that the dice are perfect and the method of throwing has no effect on the outcome. Some writers (e.g., deMorgan, 1847) say, probability refers to the belief by a mind having uncertain knowledge. This is the interpretation of probability in the Zion-Indian Point (ZIP) and some other PSAs. IVobabiiity in this sense attempts to include all information e.g., QA that could affect the performance of a piece of equipment. Such information may be conveyed as a distribution whose height is proportional to confidence in the belief and who.se width reflects uncertainty (refer to Section 2.6). 

As the cost of testing vast quantities of equipment would be too great and take too long, qualification tests, particularly on hardware, are usually performed on a small sample. The test levels are varied to take account of design assumptions, variations in production processes and the operating environment. 

The technical use of PCM in any application is based on the assumption that the PCM will perform as expected for the life time of the application. Therefore, reproducibility in the phase change properties of the PCM has to be tested. This is performed using any equipment that allows to cycle the PCM around its melting temperature (usually between 10 and 15 °C), but ensuring that the material is totally melted (Figure 154). 

Effects. For each identified failure mode, the PrHA team should describe the anticipated effects of the failure on the overall system or process. The key to performing a consistent FMEA is to assure that all equipment failures are analyzed using a common basis. Typically, analysts evaluate effects on a worst-case basis, assuming that existing safety levels do not work. However, more optimistic assumptions may be satisfactory as long as all equipment failure modes are analyzed on the same basis. 

In much of the early theory used to describe adsorption in different kinds of equipment, it was assumed that equilibrium was achieved instantly between the concentrations of adsorbate in the fluid and in the adsorbed phases. Whilst it may be useful to make this assumption because it leads to relatively straightforward solutions and shows the interrelationship between system parameters, it is seldom true in practice. In large-scale plant particularly, performance may fall well short of that predicted by the equilibrium theory. 

Based on results of a study conducted by ARDEC, LaJeunesse et al. estimated the equipment cost of a pilot-scale SCWO research facility to be 615,000. They stated that construction and installation costs would increase the total cost by a factor of 2 or more. These 1994 estimates were based on the performance of a bench-scale Sandia unit with an average flow rate of 1.0 to 1.5 g/sec. For this study, the following assumptions were used ... 

Intermediate Precision. Intermediate precision expresses within-laboratory variation and is generally performed on different days using different analysts, equipment, and sample preparations. This test may not be applicable if the laboratory has only one workstation. Additionally, this test may not be appropriate for automated workstations that are operating under the same environment and controls within a laboratory. This assumption is made on the basis that the automated workstations are identical (i.e., same configuration, same software and hardware) and that they have been suitably qualified and maintained to a consistent standard and operate under a similar climatic environment. The influence of the analyst is reduced to the preparation of solvents, and this should be covered by the robustness studies. 

Like all models, there are underlying assumptions. The main ones for analytical method validation include the areas of equipment qualification and the integrity of the calibration model chosen. If the raw analytical data are produced by equipment that has not been calibrated or not shown to perform reliably under the conditions of use, measurement integrity may be severely compromised. Equally, if the calibration model and its associated calculation methods chosen do not adequately describe the data generated then it is inappropriate to use it. These two areas are considered in some detail in Chapter 8. 

Recipe management refers to the assumption of such duties by the control system. Each batch of product is tracked throughout its production, which may involve multiple processing operations on various pieces of processing equipment. Recipe management ensures that all actions specified in the product recipe are performed on each batch of product made in accordance with that recipe. As the batch proceeds from one piece of processing equipment to the next, recipe management... 

The aim of crystallization is to separate the observed component into higher quality crystals. The crystal size and probability density distribution of its size become very important factors for the product or the following processes. Although multi-phase mixing is fairly common in industries, there have been few investigations on the mixing performance of operations/equipment. In crystallization operation, the assumption of MSMPR has been used to design a crystallizer without a detailed discussion. Therefore, the assumption of MSMPR must be studied quantitatively. 

Troubleshoot and improve the operation as needed. Once a unit is operational, carefully measure the material balance and characterize mass-transfer performance. If performance does not meet expectations, look for defects in the equipment installation. If none are found, revisit the scale-up methodology and its assumptions. 

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