Developing data processing procedure

Consistent Data-Recording Procedures. Clear procedures for recording all pertinent data from the experiment must be developed and documented, and unambiguous data recording forms estabUshed. These should include provisions not only for recording the values of the measured responses and the desired experimental conditions, but also the conditions that resulted, if these differ from those plaimed. It is generally preferable to use the values of the actual conditions in the statistical analysis of the experimental results. For example, if a test was supposed to have been conducted at 150°C but was mn at 148.3°C, the actual temperature would be used in the analysis. In experimentation with industrial processes, process equiUbrium should be reached before the responses are measured. This is particularly important when complex chemical reactions are involved. 

Beyond specific polarographic techniques variations of these methods have been developed aiming at simplified and fast evaluation using modified measurement procedures and data processing. Oldham and... 

In the previous development it was assumed that only random, normally distributed measurement errors, with zero mean and known covariance, are present in the data. In practice, process data may also contain other types of errors, which are caused by nonrandom events. For instance, instruments may not be adequately compensated, measuring devices may malfunction, or process leaks may be present. These biases are usually referred as gross errors. The presence of gross errors invalidates the statistical basis of data reconciliation procedures. It is also impossible, for example, to prepare an adequate process model on the basis of erroneous measurements or to assess production accounting correctly. In order to avoid these shortcomings we need to check for the presence of gross systematic errors in the measurement data. 

The mentioned simple data processing, suitable for perfect or almost perfect chromatograms, is not optimal in case of difficult chromatograms. More advanced data and signal processing procedures are developed, resulting in lower systematic and random errors. 

Scaling Up from Laboratory Data Laboratory experimental techniques offer an efficient and cost-effective route to develop commercial absorption designs. For example, Ouwerkerk (Hydrocarbon Process., April 1978, 89-94) revealed that both laboratory and small-scale pilot plant data were employed as the basis for the design of an 8.5-m (28-ft) diameter commercial Shell Claus off-gas treating (SCOT) tray-type absorber. Ouwerkerk claimed that the cost of developing comprehensive design procedures can be minimized, especially in the development of a new process, by the use of these modern techniques. 

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