Diagnostic chart

Matzen, P., Mdchow-Moller, A., Hilden, J., Thomsen, C., Svendsen, L.B., Gammelgaard, E., Juhl, E. Differential diagnosis of jaundice a pocket diagnostic chart. Liver 1984 4 360-371... 

Figure 2.7. Diagnostic chart of dryer air exit temperature based on the implicit level parameter.

Diagnostic charts for automobile and appliance repair are essentially FMEA charts. FMEA emphasizes conditions, not events. FMEA analyzes equipment or components. It relates conditions of components to conditions of the system of which they are a part. The analysis traces failures in components to determine their effects on the system. Of interest in system safety are effects that impact safety. 

Failure Mode and Effects Analysis Another method is failure mode and effects analysis. It considers what may go wrong and what the consequences will be. Most people are familiar with this method through diagnostic charts that aid in trouble shooting automobiles or other equipment. By locating the failure or symptom in the chart, one can locate possible causes and solutions for the problem. In failure mode and effects analysis for safety, one is trying to identify what controls will prevent or reduce the danger of some hazard. 

The isotopes produced by reactors are not common as biological markers. The absorption of neutrons generally results in radioisotopes (qv) that He below the line of stabiUty on the chart of the nucHdes. These tend to decay by j3 -emission, an undesirable mode for a diagnostic. 

A chart for vibration diagnosis is presented in Table 19-9. While this is a general criterion or rough guideline for diagnosis of mechanical problems, it can be developed into a very powerful diagnostic system when specific problems and their associated frequency domain vibration spectra are... 

In this example, data interpretations are based on g-statistic limits. These are computed by assuming the data are normally distributed in the multivariate sense. The diagnostic limits are used to establish when a statistically significant shift has occurred. Charts based on these statistics and used in this manner are analogous to conventional SPC charts. 

There are broadly two uses of chemometrics that interest the process chemist. The first of these is simply data display. It is a truism that the human eye is the best analytical tool, and by displaying multivariate data in a way that can be easily assimilated by eye a number of diagnostic assessments can be made of the state of health of a process, or of reasons for its failure [ 153], a process known as MSPC [154—156]. The key concept in MSPC is the acknowledgement that variability in process quality can arise not just by variation in single process parameters such as temperature, but by subtle combinations of process parameters. This source of product variability would be missed by simple control charts for the individual process parameters. This is also the concept behind the use of experimental design during process development in order to identify such variability in the minimum number of experiments. 

The control charts discussed earlier are very useful in the diagnostic aspects of quality process improvement. They can be used to stabilize a process by identifying out-of-control situations. After the process is stabilized and brought in control, further improvement of the process can be achieved by using some special control charts such as the cumulative sum (CUSUM) control chart and the exponentially weighted moving average (EWMA) control chart. These control charts can be used when small shifts in a process are of interest. 

An established external quality control (QC) scheme is not currently available. Pooled disease control CSF retained from other analyses is used. Aliquots of the pooled CSF are made and stored at -70°C. This CSF is analysed on five separate occasions and the mean and standard deviation determined. For an analytical/diagnostic run to proceed, analysis of QC material must provide concentration values that are within two standard deviations (plus and minus) of the calculated mean for that particular QC. Construction of Levy-Jennings type control charts provide historical information of overall performance and highlight potential deterioration in the performance of the system. 

Frequently, however, the lack of specificity in an analytical technique can be compensated for with sophisticated data processing, as described in the chemometrics chapter of this text (Chapter 8). Quinn and associates provide a demonstration of this approach, using fiber-optic UV-vis spectroscopy in combination with chemometrics to provide realtime determination of reactant and product concentrations.23 Automatic window factor analysis was used to evaluate the spectra. This technique was able to detect evidence of a reactive intermediate that was not discernable by off-line HPLC, and control charting of residuals was shown to be diagnostic of process upsets. Similarly, fiber-optic NIR was demonstrated by some of the same authors to predict reaction endpoint with suitable precision using a single PLS factor.24... 

Gradebook Diagnostics provide unique insight into class and student performance. With a single click, charts summarize the most difficult problems, vulnerable students, grade distribution, and score improvement over the duration of the course. 

The medical applications of nuclear technology range from in vitro and in vivo injections for diagnostic tests to cobalt radiation for cancer therapy. A new medical specialty was created, a family of compact cyclotrons was developed to provide short-lived nuclides, and a sizable industry evolved to produce technetium. Until the nuclear industry was created, technetium had been missing from the chart of chemical elements because the half-life of the most stable member was too short, 21,000 years. Technetium and several other nuclides of importance here are discussed elsewhere in the chapter in connection with their production (see Table 21.19).60,61... 

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