Quality-control charts

Laquer, F. C. Quality Control Charts in the Quantitative Analysis Laboratory Using Conductance Measurement, ... 

FIGURE 9.12 Quality control chart of PSS SDV columns plate count (per m) measurements over a I0>year period 5% limits are also shown. 

Continuous quality control is based on principles that firstly were used in the system of quality control charts (QCC, Shewhart [1931]). Today, admittedly the monitoring of the characteristics of a process or product in order to detect deviations from the target value is not tied to charts but is mostly done by computer, although it is frequently still called a control chart system. 

Fig. 4.14. General scheme of a quality control chart LoS level of significance...

Parameters for the most important of the above mentioned quality control charts are given in Table 4.4. 

The underlying calibration procedure of a newly developed analytical method has to be examined by basic validation studies to determine the reliability of the method and its efficiency in comparison with traditional methods. In order to ensure long-term stability, it is necessary to perform revalidations, which can be combined with the use of quality control charts, over meaningful time periods. 

Identify available information, including information from quality control charts, performance in proficiency testing rounds, literature and validation information on related methods and data concerning comparison with other methods. Use the available information and professional judgement to review each relevant validation issue and sign-off issues adequately addressed and documented. 

Method validation provides information concerning the method s performance capabilities and limitations, when applied under routine circumstances and when it is within statistical control, and can be used to set the QC limits. The warning and action limits are commonly set at twice and three times the within-laboratory reproducibility, respectively. When the method is used on a regular basis, periodic measurement of QC samples and the plotting of these data on QC charts is required to ensure that the method is still within statistical control. The frequency of QC checks should not normally be set at less than 5% of the sample throughput. When the method is new, it may be set much higher. Quality control charts are discussed in Chapter 6. 

Up to 50 stored assay protocols include routines for RIA/IRMA, dual label assays, T3-uptake and FTI calculations and hepatitis, RAST and hCG screening. Quality-control charts can be printed automatically. 

Note This experiment assumes that a permanent log and a quality control chart are constantly maintained for each analytical balance in use in the laboratory. Each day you use a given analytical balance and log in with your name and date. The following calibration check should be performed weekly on all balances. If, according to the log, the calibration of the balance you want to use has not been checked in over a week, perform this procedure. Review Section 3.3 for basic information concerning the analytical balance. 

How can a quality control chart signal a problem with a routine laboratory procedure ... 

A quality control chart is a visual aid for determining whether a given analytical result is outside the action limits determined for the results for that procedure. If it is outside the action limits, the cause may be a problem with the procedure, among other things. 

It is often helpful to record the results of control samples in a visible manner not only because of the greater impact of a visual display but also for the relative ease with which it is possible to forecast trends. A variety of styles of quality control charts have been suggested but the most commonly used are those known as Levey-Jennings or Shewart charts, which indicate the scatter of the individual control results about the designated mean value (Procedure 1.7). 

Statistical Control for a New Method To implement a new method, a laboratory must produce a preliminary track record of its success so that quality control charts can be established and then maintained. Aside from acquiring the space, supplies, equipment, instrumentation, and manpower required, the method must be tested, modified, tested again, etc., until it is ready to go "online." Gillis and Callio (listed in Bibliography) recommend the following sequence for preparing an instrumental method for routine use. 

The analysis of quality control (QC) samples with the construction of quality control charts has been suggested as another way of performing PQ. Control samples with known amounts are interdispersed among actual samples at intervals determined by the total number of samples, the stability of the system, and the precision specified. The advantage of this procedure is that the system performance is measured more or less continuously under conditions that are very close to the actual application. 

Retrospective validation involves using the accumulated in-process production and final product testing and control (numerical) data to establish that the product and its manufacturing process are in a state of control. Valid in-process results should be consistent with the drug products final specifications and should be derived from previous acceptable process average and process variability estimates, where possible, and determined by the application of suitable statistical procedures, that is, quality control charting, where appropriate. The retrospective validation option is selected when manufacturing processes for established products are considered to be stable and when, on the basis of economic considerations and resource limitations, prospective qualification and validation experimentation cannot be justified. 

Concurrent validation is conducted under a protocol during the course of normal production. The first three production-scale batches must be monitored as comprehensively as possible. The evaluation of the results is used in establishing the acceptance criteria and specifications of subsequent in-process control and final product testing. Some form of concurrent validation, using statistical process control techniques (quality control charting), may be used throughout the product manufacturing life cycle. 

For in-process control and determination of quality levels, inspection plans and quality control charts are used (as relevant). For sampling plans and acceptance criteria. Military Standard 105E is used. 

Analysis of Retrospective Production Data Using Quality Control Charts... 

Much of the discussion here stems from experience with quality control charts in the pharmaceutical industry. For the use of quality control charts in other industries, the following requirement established by the Nuclear Regulatory Commission [1] may be useful. 

Figure 1 taken from the petroleum industry shows a quality control chart where the data in the frequency histogram is normally distributed. In this particular control chart, the grand average is 7.08 and is surrounded by + 1, 2, 3 standard deviations rather than range values. 

Figure 6 Residual standard deviation (RSD) quality control chart.

Another approach suggested by Bolton (11) in constructing a quality control chart, based upon a single numerical value for each lot or batch, is to use the relative standard deviation (RSD) of the data set ... 

Such data are shown in Table 3 and Fig. 6. Upper and lower control limits are calculated based upon n = 2 and A2 = 1.880. Thus, for 10 lots there will be 9 data points to plot, which results in a robust analysis of the quality control data for the product. Unlike a normal control chart, when you decide to use RSD values to create the quality control chart, the lower control limit (LCL) is more desirable than the upper control limit (UCL) simply because lower RSD values reflex a tighter dispersion around the mean. 

The Reliability of Measurements. The Analysis of Data. The Application of Statistical Tests. Limits of Detection. Quality Control Charts. Standardization of Analytical Methods. 

In industrial plants, large numbers of process variables must be maintained within specified limits in order for the plant to operate properly. Excursions of key variables beyond these limits can have significant consequences for plant safety, the environment, product quality and plant profitability. Statistical process control (SPC), also called statistical quality control (SQC), involves the application of statistical techniques to determine whether a process is operating normally or abnormally. Thus, SPC is a process monitoring technique that relies on quality control charts to monitor measured variables, especially product quality. 

Vogelsang, J. 1991. The quality control chart principle Application to the routine analysis of pesticide residues in air. Fresenius J. Anal. Chem. 340 384—388. 

G. Construct a quality-control chart from the data used in Table 13-4. 

The reliability of measurements. The arrptysis of data. The application of statistical tests. Limits of detection. Quality control charts. Standardization of analytical methods. Chcmometrics. 

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