Management process sample analysis

In several chapters we discussed how the quality of the analytical result defines the amount of information which is obtained on a sampled system. Obvious quality criteria are accuracy and precision. An equally important criterion is the analysis time. This is particularly true when dynamic systems are analyzed. For instance a relationship exists between the measurability and the sampling rate, analysis time and precision (see Chapter 20). The monitoring of environmental and chemical processes are typical examples where the management of the analysis time is... 

Data reduction, verification, and reporting are always a combined effort of the personnel working in different laboratory sections, their supervisors, and the Data Management Section. Sample preparation technicians and analysts performing analysis are responsible for the correctness of their computerized and manual calculations and for proper reporting of the obtained results. Supervisors verify the correctness of these calculations during data review and approval process. The Data Management Section staff is responsible for the correct conversion of the data entered by hand or transmitted from the data acquisition computers into the LIMS and the production of finished laboratory reports prepared to client s specifications. 

The information structure of sample data and results affects the usability of the systems and the possibility to readily retrieve required sample data. An effective sample organization ensures that sample analysis is available and is understandable for end-users and auditors. Specific functions include statistical processing and trending, reporting, and management of fault cases (exceptions). 

Automation of analyses involving liquid samples is facilitated by their usually adequate homogeneity and easy mechanical handling by use of peristaltic or piston pumps, or some other liquid management devices, i.e. a liquid driver. Nonetheless, this is not the case when dealing with solid samples, analysis of which frequently involves their prior conversion into liquids by dissolution. The dissolution step is the bottleneck of analytical processes involving solid samples, as it is frequently slow and must be performed manually. 

Monte Carlo sampling, 26 999, 1001—1004 in control systems, 26 1046 future trends in, 26 1047-1048 HSGA algorithm and, 26 1032 in process scheduling, 26 1042-1043 in process synthesis and design, 26 1041 quasi-Monte Carlo sampling and, 26 1011-1016 for risk analysis, 26 1045 in supply chain management, 26 1043-1044... 

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