Instrument reliability

The specific results of well over 1 year of continued monitoring will be discussed in a second paper. It is pointed out here that the AEBIL monitoring system installed in the power plant for the above monitoring purposes has efficiently and continuedly performed during this time interval, with no instrumentation reliability problems. 

Overall instrumental reliability (subtechniques, interfaces, Teaks )... 

This study demonstrates that the nonlinear optimization approach to parameter estimation is a flexible and effective method. Although computationally intensive, this method lends itself to a wide variety of process model formulations and can provide an assessment of the uncertainty of the parameter estimates. Other factors, such as measurement error distributions and instrumentation reliability can also be integrated into the estimation procedure if they are known. The methods presented in the crystallization literature do not have this flexibility in model formulation and typically do not address the parameter reliability issue. 

The robustness of a sample preparation technique is characterized by the reliability of the instrumentation used and the variability (precision) of the information obtained in the subsequent sample analysis. Thus, variations in controlled parameters and sequences are to be avoided. In sample preparation methods employing supercritical fluids as the extracting solvents, it has been our experience that minimal variations in efficient analyte recoveries are possible using a fully automated extraction system. The extraction solvent operating parameters under automated control are temperature, pressure (thus density), composition and flow rate through the sample. The precision of the technique will be discussed by presenting replicability, repeatability, and reproducibility data for the extraction of various analytes from such matrices as sands and soils, river sediment, and plant and animal tissue. Censored data will be presented as an indicator of instrumental reliability. 

The main purpose of this paper is to explore the robustness of SFE as an analytical technique. To do this, we have used guidelines published by the AOAC (14), Association of Official Analytical Chemists, as a way to define and measure contributors to method robustness. In particular, method robustness can be characterized by the reliability of the analytical instrumentation employed and the precision (variability) of the results. In the "Results and Discussion" section, anecdotal information will be presented as an indication of instrumentation reliability and many studies will be summarized to provide precision data for the factors of replicability, repeatability, and reproducibility. 

Reliability in analytical chemistry requires a mathematical definition, which is given as a complex function of the sample reliability (Rs), method reliability (RM), instrument reliability (R,), and data-processing reliability... 

By considering that standards are also samples, which act as a glue between the standard methods and the instrument, reliability increases. 

The number of instrument QC checks typically represents about 5% of the total number of measurements made for a set of samples. The QC data and records of problems and responses should be kept accessible for the fife of the instrument, and possibly beyond, to indicate the extent of instrument reliability. Changes in values may be examined for periodic patterns related to parameters such as temperature or airborne radon concentrations to consider remedial measures. 

Chemical education researchers are typically asked to demonstrate that the test instruments used in their studies are valid and reliable. Validity is the extent to which a question measures what it purports to measure. There are several forms of validity (face validity, content validity, construct validity, etc.), and different forms become relevant for different test instruments. Reliability, on the other hand, is the extent to which the question is stable over time, i.e., if the instrument were administered to similar groups of students at two different times. 

For example, with the recent interest in fiber-related illnesses, the techniques to measure levels of fibers such as cotton dust, wood dust, enzyme dust, and asbestos have been improved. Efforts have been concentrated on developing membrane filters and on developing techniques that will yield reproducible results (79, 22, 44, 66, 121). Similarly, a new chlorine gas concentration monitor was developed that is portable and does not rely on mechanical pumps for air sampling, which could be critical in the event of a power failure (72). Another new technique involves the use of porous polymer beads to sample for organics followed by gas-chromatographic/mass-spectrographic analysis 32). These developments are only illustrative of the types of advances that are being achieved as instrument reliability and detector sensitivity are increased. 

Taylor, E. F, The Effect of Medical Test Instrument Reliability on Patient Risks, Proceedings of the Annual Symposium on Reliability, 1969, pp. 328-330. 

With respect to the majority of procedures discussed for the different commodities, and the instruments used, it is necessary to accumulate data from widely different sources to evaluate the natural variability of the commodity, the usefulness of the procedure selected as a criterion for delimiting a color grade, and finally the instrumental reliability under operating conditions, whether it be in the laboratory or in the inspection service in the field. 

One trade-off for the use of smaller devices for monitoring of toxic materials in the environment is in the fact that small, cheaper devices can be used in greater abundance than larger, more costly instruments. Reliability in response data, i.e., some freedom from false analytical information, can be generated by a significant redundancy in detector devices. This use scenario allows for an appreciation of a distribution of contamination when the contamination is widespread. 

A considerable catalyst to the advancement of corrosion inspection and monitoring technology has therefore been the exploitation of oil and gas resources in extreme environmental conditions. Many techniques that have been accepted in the oil and gas industries for years are only now beginning to be applied in other industries such as transportation, mining, and construction. Work in these conditions has necessitated enhanced instrument reliability and the automation of many tasks, including inspection. 

Compiling performance criteria helps make clear the right techniques for the task. The field should now be narrowed down to establish a set of practical criteria, which might eliminate some of the less suitable techniques for a particular application. Some of these criteria will include (but not be limited to) detection limits, precision requirements, quality of data, sample throughput capability, ease of use, instrument reliability, operator training needs, or availability of application material. 

To a certain degree, instrument reliability is impacted by routine maintenance issues and the types of samples being analyzed, but it is generally considered more of a reflection of the design of an instrument. Most manufacturers will guarantee a minimum percentage uptime for their instrument, but this number (which is typically -95%) is almost meaningless unless you really understand how it is calculated. Even... 

When we talk about instrument reliability, it is important to understand whether it is related to the samples being analyzed, the lack of expertise of the person operating the instrument, an umeliable component, or an inherent weakness in the design of the instrument. For example, how does the instrument handle highly corrosive chemicals such as concentrated mineral acids Some sample introduction systems and interfaces will be more rugged than others and require less maintenance in this area. On the other hand, if the operator is not aware of the dissolved solids limitation... 

The question of speed is related to the reliability of the instrumentation. Reliable methods with low operating costs can readily be automated and can left unattended, e.g. overnight. In those circumstances, speed may be a secondary consideration. XRF methods come into this category. For methods that are more prone to problems during running (and so cannot be left unattended) or that use expensive consumables (e.g. argon for ICP methods), speed is usually of the essence. 

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