Accuracy required of engineering data

The accuracy needed depends on the use to which the data will be put. Before spending time and money searching for the most accurate value or arranging for special measurements to be made, the designer must decide what accuracy is required this will depend on several factors  

The level of design Less accuracy is obviously needed for rough screening calculations made to sort out possible alternative designs than in the final stages of design, when money will be committed to purchase equipment. 

The reliability of the design methods If there is some uncertainty in the techniques to be used, it is clearly a waste of time to search out highly accurate physical property data that will add little or nothing to the reliability of the final design. 

The sensitivity to the particular property How much will a small error in the property affect the design calculation For example, it was shown in Chapter 5 that the estimation of the optimum pipe diameter is insensitive to viscosity. The sensitivity of a design method to errors in physical properties and other data can be checked by repeating the calculation using slightly altered values. 

Consider the accuracy of the equilibrium data required to calculate the number of equilibrium stages needed for the separation of a mixture of acetone and water by distillation (see Chapter II, Example 11.2). Several investigators have published vapor-liquid equilibrium data for this system Othmer et al. (1952), York and Holmes (1942), Kojima et al. (1968), Reinders and De Minjer (1947). 

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Applications of geodesy to engineering - until the lUGG-Congress in Vienna 1991 not formally represented in the lAG - have recently undergone a rapid development with respect to complexity of tasks involved, accuracy requirements, measurement techniques, data processing and modelling. 

Probably the weight loss coupon approach is one of the must reliable methods and is widely used. The accuracy of the data is highly dependent on good techniques and on the statistical significance of the tests. The engineering quality data produced require the efforts of many people over a period of several weeks or months, which makes this information quite costly. However, it is the technique of first choice of many processors. 

The accurate calculation of thermodynamic properties for construction of a table or diagram is an exacting task, seldom required of an engineer. However engineers do make practical use of thermodynamic properties, and an understand ing of the methods used for their calculation leads to an appreciation that some, uncertainty is associated with every property value. There are two major reasons for inaccuracy. First, the experimental data are difficult to measure and are subject to error. Moreover, data are frequently incomplete, and are extended by interpolation and extrapolation. Second, even when reliable PVT data are available, a loss of accuracy occurs in the differentiation process required in the calculation of derived properties. This accounts for the fact that data of a high order of accuracy are required to produce enthalpy and entropy values suitable for engineering calculations. 

Texts [1-5] with computer programs and sometimes with supplied software are now available for scientists and engineers. They must fit a function or functions to measure data that fluctuate, which result from random error of measurement. If the number of data points equals the order of the polynomial plus one, we can exactly fit a polynomial to the data points. Fitting a function to a set of data requires more data than the order of a polynomial. The accuracy of the fitted curve depends on the large number of experimental data. In this chapter, we will develop... 

Medical reverse engineering (MRE) Aim Medical application development and research. It is normally involved in using patient data or biomedical objects to reconstmct 3D models of anatomical structures and objects of interest for the development of different medical products, applications, and biomedical research Accuracy (depending on specific applications) For the personalised cranio-maxillofacial implants, bio-models and training models, the accuracy requirement is not very stringent compared to industrial RE, i.e. it is up to hundred(s) of microns For surgical tools and functional Implants such as spine, hip and knee implants, the accuracy requirement is very stringent... 

They fall into two groups - those derived from regression analysis of historical process data and first-principle types which rely on engineering calculations. First-principle techniques still require some historical data to calibrate the model and to check its accuracy. While the vendors of first-principle techniques might argue that the volume of data required is less, the key to the success of both techniques is the quality of the data. The use of routinely collected data, for example from a plant history database, can often cause inaccuracies in the end result. 

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