Calibration control charts

Construct a precision control chart using the following 20 ranges, each determined from a duplicate analysis of a 10-ppm calibration standard... 

Documentation Data volume includes all quality control forms, e.g., zero/span control charts and multipoint calibration results... 

Fig. 4.12. Statistical process control chart for TXRF measurement systems. The sensitivity of the system can be controlled by daily calibration with an...

The quality control unit in a cosmetics company supervised the processing of the weekly batch of shampoo by determining, among other parameters, the viscosity and the dry residue. Control charts showed nothing spectacular. (See Fig. 4.10, top.) The cusum charts were just as uneventful, except for that displaying the dry residue (Fig. 4.10, middle and bottom) The change in trend in the middle of the chart was unmistakable. Since the analytical method was very simple and well-proven, no change in laboratory personnel had taken place in the period, and the calibration of the balances was done on a weekly basis, suspicions turned elsewhere. A first hypothesis,... 

DEGRAD STABILjcIs Section 1.8.4 The analysis of stability reports often suffers from the fact that the data for each batch of product is scrutinized in isolation, which then results in a see-no-evil attitude if the numerical values are within specifications. The analyst is in a good position to first compare all results gained under one calibration (usually a day s worth of work) irrespective of the products/projects affected, and then also check the performance of the calibration samples against experience, see control charts, Section 1.8.4. In this way, any analytical bias of the day will stand out. For this purpose a change in format from a Time-on-Stability to a Calendar Time depiction is of help. 

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. 

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. 

STL s quality-control programme includes the recovery of known additions of analyte, analysis of externally supplied standards, calibration, analysis of duplicates and control charting. Each analyte is monitored by analysing at least one AQC standard for every 20 samples. AQC results are plotted on control charts and action is taken if a point Hes outside +3 standard deviations (SD) or if two consecutive points He outside +2 SDs. 

Internal QC inclndes the nse of blanks, chemical calibrants, spiked samples, blind samples, replicate analysis, and QC samples. QC samples shotrld be homogeneous and stable. They shotrld be available in sufficient quantities. The use of control charts is recommended (see chapter 13). 

Some standards or decrees include the obligatory measurement of control samples or repeated measurement. This can be used for control charts with only little effort. Other values like calibration parameters are also available without additional woik. They also can be used for control charts, especially if the stability of calibration is known to be a weak point in the procedure. 

Some standards or decrees include obligatory measurement of control samples or multiple measuremente. Then it is only a minimal additional effort to document these measurements in control charts In some cases the daily calibration gives values (slope and/or intercept) that can be integrated into a control chart with little effort... 

Traditionally, the education that chemists and chemistry laboratory technicians receive in colleges and universities does not prepare them adequately for some important aspects of the real world of work in their chosen field. Today s industrial laboratory analyst is deeply involved with such job issues as quality control, quality assurance, ISO 9000, standard operating procedures, calibration, standard reference materials, statistical control, control charts, proficiency testing, validation, system suitability, chain of custody, good laboratory practices, protocol, and audits. Yet, most of these terms are foreign to the college graduate and the new employee. 

As stated above, an occasional point outside the warning limits is expected. However, if there begins to be some consistency with points outside the warning limits, there is sufficient cause for some evaluation of the situation. Perhaps some component of the system is out of calibration, or perhaps some bias has been introduced inadvertently. Figure 5.12 is an example of such a control chart. 

Figure 5.12 A control chart showing a consistent pattern outside the upper warning limit after Day 24, indicating that an evaluation of the situation is warrented. It may indicate a component of the system is out of calibration, etc.

Figure 5.14 A control chart showing a steady change from low to high values. Such a control chart can result from a steady drift in the calibration of a spectrophotometric detector, for example, indicating that the detector may need to be repaired or replaced.

Figure 4.22 Example of a control chart to test for outlying samples on the calibration set. Four factors were used to develop the model (original spectra from Figure 4.9, mean centred).

For quality assessment of an analytical process, a control chart could show the relative deviation of measured values of calibration check samples or quality control samples from their known values. Another control chart could display the precision of replicate analyses of unknowns or standards as a function of time. 

Specifications How good do the numbers have to be Write specifications Pick methods to meet specifications Consider sampling, precision, accuracy, selectivity, sensitivity, detection limit, robustness, rate of false results Employ blanks, fortification, calibration checks, quality control samples, and control charts to monitor performance Write and follow standard operating procedures... 

Documentation is critical for assessment. Standard protocols provide directions for what must be documented and how the documentation is to be done, including how to record information in notebooks. For labs that rely on manuals of standard practices, it is imperative that tasks done to comply with the manuals be monitored and recorded. Control charts (Box 5-1) can be used to monitor performance on blanks, calibration checks, and spiked samples to see if results are stable over time or to compare the work of different employees. Control charts can also monitor sensitivity or selectivity, especially if a laboratory encounters a wide variety of matrixes. 

The laboratory quality control program has several components documentation of standard operating procedures for all analytical methods, periodic determination of method detection levels for the analytes, preparation of standard calibration curves and daily check of calibration standards, analysis of reagent blank, instrument performance check, determination of precision and accuracy of analysis, and preparation of control charts. Determination of precision and accuracy of analysis and method detection limits are described under separate subheadings in the following sections. The other components of the quality control plan are briefly discussed below. 

Examination of product control charts is most useful in trying to distinguish between process-related or non-process-related causes.Trend analysis of key production parameters and attributes could assist in localizing a possible cause of the OOS. For example, if the potency of the product has been trending higher than usual for the last few batches produced (and the OOS resulted from an upper limit failure), this could be indicative of such causations as inaccurate moisture analysis or operator compensation error, error in the batch record, weighing error due to balance or scale bias, change in excipient purity which could impact functional characteristics or failure to maintain and/or calibrate apiece of equipment. 

Finally, there is the need for proper documentation, which can be in written or electronic forms. These should cover every step of the measurement process. The sample information (source, batch number, date), sample preparation/analytical methodology (measurements at every step of the process, volumes involved, readings of temperature, etc.), calibration curves, instrument outputs, and data analysis (quantitative calculations, statistical analysis) should all be recorded. Additional QC procedures, such as blanks, matrix recovery, and control charts, also need to be a part of the record keeping. Good documentation is vital to prove the validity of data. Analyt-... 

Calibration control standards (CCSs) are used to check calibration. The CCS is the first sample analyzed after calibration. Its concentration may or may not be known, but it is used for successive comparisons. A CCS may be analyzed periodically or after a specified number of samples (say, 20). The CCS value can be plotted on a control chart to monitor statistical control. 

Calibration of balances calibration of ultraviolet grating for wavelength accuracy exchange of lamps system suitability testing analysis of quality control samples and evaluation of results using control charts. 

It is evident that the distance between the inhouse and the specification limits is influenced by the quality of the calibration/measurement procedure a fixed relation, such as 2(j, 3(j, as has been proposed for control charts, might well be too optimistic or too pessimistic (for a single test result exactly on the 2(7 inhouse limit, the true value would have a = 16% chance of being outside the 3(7 SL). Note that it takes at least n - 6 (resp. n = 11) values to make a z = 2 (z = 3) scheme (see Figure 1.24) even theoretically possible. For n = 4, for instance, xmean would have to be > 1.5 a in order that the largest x could be beyond 3a run a series of simulations on program CONVERGE and concentrate on the first four data points to see that an OOS... 

A second, and perhaps more important, safeguard is the use of control charts for trend analysis. This plot will show any drift from the median value (nominal value or actual average value) alerting whoever is responsible for calibration maintenance before the values actually drift out of acceptance range. It is possible that the reason for the drift is the process itself. In this case, a service has been performed for production. If tablets/capsules (or any other product) are analyzed by the referee method and found to provide the expected value, the calibration transfer protocol may again be followed to correct the calibration. 

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