Assessing Quality

A New US Film System Classification and Image Quality Assessment. 

NDT as an objective method, which can be applied for 100% control if necessary, is used for quality assessment of critical components all over the world. But it is necessary to support quality of the implementation of NDT to ensure the detection of defects and to achieve reliable results. 

The specific character of NDT related to the quality assessment of safety critical products and objects requires constant analysis and continuous improvement of processes and their interconnection. Sometimes interaction of processes is very complicated (Figure 3) therefore the processes have to be systematized and simplified when possible to realize total quality management in NDT. 

The focus of this chapter is on the two principal components of a quality assurance program quality control and quality assessment. In addition, considerable attention is given to the use of control charts for routinely monitoring the quality of analytical data. 

The written directives of a quality control program are a necessary, but not a sufficient, condition for obtaining and maintaining an analysis in a state of statistical control. Although quality control directives explain how an analysis should be properly conducted, they do not indicate whether the system is under statistical control. This is the role of quality assessment, which is the second component of a quality assurance program. 

The goals of quality assessment are to determine when a system has reached a state of statistical control to detect when the system has moved out of statistical control and, if possible, to suggest why a loss of statistical control has occurred so that corrective actions can be taken. For convenience, the methods of quality assessment are divided into two categories internal methods that are coordinated within the laboratory and external methods for which an outside agency or individual is responsible. The incorporation of these methods into a quaKty assurance program is covered in Section 15C. 

The most useful methods for quality assessment are those that are coordinated by the laboratory and that provide the analyst with immediate feedback about the system s state of statistical control. Internal methods of quality assessment included in this section are the analysis of duplicate samples, the analysis of blanks, the analysis of standard samples, and spike recoveries. 

Selected Quality Assessment Limits for the Analysis of Waters and Wastewaters ... 

Spike Recoveries One of the most important quality assessment tools is the recovery of a known addition, or spike, of analyte to a method blank, field blank, or sample. To determine a spike recovery, the blank or sample is split into two portions, and a known amount of a standard solution of the analyte is added to one portion. The concentration of the analyte is determined for both the spiked, F, and unspiked portions, I, and the percent recovery, %R, is calculated as... 

Internal methods of quality assessment should always be viewed with some level of skepticism because of the potential for bias in their execution and interpretation. For this reason, external methods of quality assessment also play an important role in quality assurance programs. One external method of quality assessment is the certification of a laboratory by a sponsoring agency. Certification is based on the successful analysis of a set of proficiency standards prepared by the sponsoring agency. For example, laboratories involved in environmental analyses may be required to analyze standard samples prepared by the Environmental Protection... 

Agency. A second example of an external method of quality assessment is the voluntary participation of the laboratory in a collaborative test (Chapter 14) sponsored by a professional organization such as the Association of Official Analytical Chemists. Finally, individuals contracting with a laboratory can perform their own external quality assessment by submitting blind duplicate samples and blind standard samples to the laboratory for analysis. If the results for the quality assessment samples are unacceptable, then there is good reason to consider the results suspect for other samples provided by the laboratory. 

In the previous section we described several internal methods of quality assessment that provide quantitative estimates of the systematic and random errors present in an analytical system. Now we turn our attention to how this numerical information is incorporated into the written directives of a complete quality assurance program. Two approaches to developing quality assurance programs have been described a prescriptive approach, in which an exact method of quality assessment is prescribed and a performance-based approach, in which any form of quality assessment is acceptable, provided that an acceptable level of statistical control can be demonstrated. 

With a prescriptive approach to quality assessment, duplicate samples, blanks, standards, and spike recoveries are measured following a specific protocol. The result for each analysis is then compared with a single predetermined limit. If this limit is exceeded, an appropriate corrective action is taken. Prescriptive approaches to quality assurance are common for programs and laboratories subject to federal regulation. For example, the Food and Drug Administration (FDA) specifies quality assurance practices that must be followed by laboratories analyzing products regulated by the FDA. 

A good example of a prescriptive approach to quality assessment is the protocol outlined in Figure 15.2, published by the Environmental Protection Agency (EPA) for laboratories involved in monitoring studies of water and wastewater. Independent samples A and B are collected simultaneously at the sample site. Sample A is split into two equal-volume samples, and labeled Ai and A2. Sample B is also split into two equal-volume samples, one of which, Bsf, is spiked with a known amount of analyte. A field blank. Dp, also is spiked with the same amount of analyte. All five samples (Ai, A2, B, Bsf, and Dp) are preserved if necessary and transported to the laboratory for analysis. 

In a performance-based approach to quality assurance, a laboratory is free to use its experience to determine the best way to gather and monitor quality assessment data. The quality assessment methods remain the same (duplicate samples, blanks, standards, and spike recoveries) since they provide the necessary information about precision and bias. What the laboratory can control, however, is the frequency with which quality assessment samples are analyzed, and the conditions indicating when an analytical system is no longer in a state of statistical control. Furthermore, a performance-based approach to quality assessment allows a laboratory to determine if an analytical system is in danger of drifting out of statistical control. Corrective measures are then taken before further problems develop. 

The principal tool for performance-based quality assessment is the control chart. In a control chart the results from the analysis of quality assessment samples are plotted in the order in which they are collected, providing a continuous record of the statistical state of the analytical system. Quality assessment data collected over time can be summarized by a mean value and a standard deviation. The fundamental assumption behind the use of a control chart is that quality assessment data will show only random variations around the mean value when the analytical system is in statistical control. When an analytical system moves out of statistical control, the quality assessment data is influenced by additional sources of error, increasing the standard deviation or changing the mean value. 

Using Control Charts for Quality Assurance Control charts play an important role in a performance-based program of quality assurance because they provide an easily interpreted picture of the statistical state of an analytical system. Quality assessment samples such as blanks, standards, and spike recoveries can be monitored with property control charts. A precision control chart can be used to monitor duplicate samples. 

Once a control chart is in use, new quality assessment data should be added at a rate sufficient to ensure that the system remains in statistical control. As with prescriptive approaches to quality assurance, when a quality assessment sample is found to be out of statistical control, all samples analyzed since the last successful verification of statistical control must be reanalyzed. The advantage of a performance-based approach to quality assurance is that a laboratory may use its experience, guided by control charts, to determine the frequency for collecting quality assessment samples. When the system is stable, quality assessment samples can be acquired less frequently. 

Another important quality assessment tool, which provides an ongoing evaluation of an analysis, is a control chart. A control chart plots a property, such as a spike recovery, as a function of time. Results exceeding warning and control limits, or unusual patterns of data indicate that an analysis is no longer under statistical control. 

Finally, the textbook concludes with two chapters discussing the design and maintenance of analytical methods, two topics of importance to analytical chemists. Chapter 14 considers the development of an analytical method, including its optimization, verification, and validation. Quality control and quality assessment are discussed in Chapter 15. 

Data quality assessment requirements are related to precision and accuracy. Precision control limits are established, i.e., 4-10% of span value, as calculated from Eq. (15-1). The actual results of the may be used to calculate an average deviation (Eq. 15-3) ... 

COM(94jl09 Proposal on ambient air quality assessment and management... 

What are some of the criteria to use when selecting a consultant for indoor air quality assessments. 

Quality assessment. How good is the number that has been calculated ... 

The table data show that the stress/strain properties of compositions are improved by additional dispersion (mixing). Ultrasonic analysis is sufficiently reliable and informative as a means of mixing quality assessment. The very small change of the characteristics for filled compositions (chalk + kaolin) can be due to the fact that these fillers are readily distributed in the matrix as they are. 

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