Monitoring charts range

Fig. 2 Characteristic operating curve for a control chart monitoring the range...

A Shewhart chart is used to monitor the variation of individual results over time, compared to a target value. Shewhart charts are useful for identifying when bias has entered a measurement system. Non-random patterns in the data, such as drift or step-changes, indicate that bias is present. A range chart is used to monitor the precision of a measurement system, regardless of whether there is any bias present. The data on both types of chart are best evaluated by setting control limits. 

Prefilled syringes will be monitored for volume check by directly dispensing the content into a tared calibrated cylinder of appropriate capacity, reading the volume, and noting down the weight in the average and range chart. 

Control charts based on variable sample data include the x chart and the. v chart. When dealing with a numerically measurable quality characteristic, the x chart is usually employed to monitor the process average and the s chart is used to monitor the process variability. When there is only one observation in each sample, the individual measurement chart (I chart) and moving range chart (MR chart) are used to monitor the process average and variability. It should be noted that due to the poor... 

All uncertainty estimates start with that associated with the repeatability of a measured value obtained on the unknown. It is neither required for the sake of quality control, nor could it always be economically justified, to make redundant determinations of each measured value, such as would be needed for complete statistical control. Repeat measurements of a similar kind under the laboratory s typical working conditions may have given satisfactory experience regarding the range of values obtained under normal operational variations of measurement conditions such as time intervals, stability of measurement equipment, laboratory temperature and humidity, small disparities associated with different operators, etc. Repeatability of routine measurements of the same or similar types is established by the use of RMs on which repeat measurements are made periodically and monitored by use of control charts, in order to establish the laboratory s ability to repeat measurements (see sect, entitled The responsible laboratory above). For this purpose, it is particularly important not to reject any outlier, unless cause for its deviation has been unequivocally established as an abnormal blunder. Rejection of other outliers leads a laboratory to assess its capabilities too optimistically. The repeatability in the field of a certified RM value represents the low limit of uncertainty for any similar value measured there. 

Shewhart control charts enable average process performance to be monitored, as reflected by the sample mean. It is also advantageous to monitor process variability. Process variability within a sample of k measurements can be characterized by its range, standard deviation, or sample variance. Consequently, control charts are often used for one of these three statistics. 

Malvern (Insitec) ECPS2 is designed to monitor and control particle size distributions from 0.5 to 1,500 pm, at concentrations up to 10,000 ppm, directly in pneumatic powder flow streams. Up to one thousand size distribution measurements per second are carried out at flow velocities from static to ultrasonic. Discrete data point, extracted from the log file, can be viewed. The data can also be viewed in tabular form and as a size distribution curve. Data can also be integrated over any selected range. A Statistical Process Control (SPC) option enables the file data to be viewed in standard control chart format either as an X or R chart. Various interface arrangements have been described, [203] ... 

The control chart is the basic analytical tool of SPC and is used for first assessing a process, then for monitoring a process output with respect to on-target control and process variability. A control chart is basically a time plot of a statistic calculated from a variable associated with a process. This variable may either be a process variable, such as temperature or flow rate, or a product variable, such as fill weight or potency. Examples of statistics are an individual measurement, an average of two or more measurements, a percentage of defective output items, a count of defect occurrences in time or space, or a measure of variation such as a range or standard deviation of two or more measurements. 

All three types of monitor may be used in the given system, connected in series. In a system used by the author the output of each of the three monitors was adjusted to range from 0 to 10 mV and all three were fed to a three-channel dot printing potentiometric chart recorder. Three different coloured traces were obtained corresponding to ultraviolet transmission, an approximately linear function of conductivity, and the count rate measured by the radio-activity flow... 

Samples can be divided into two aliquots and analyzed, and the duplicates used for control purposes. This is a simple quality control procedure that does not require stable control materials and therefore can be used when stable materials are not available or as a supplemental procedure when stable control materials are available. The differences between duplicates are plotted on a range type of control chart that has limits calculated from the standard deviation of the differences. When the duplicates are obtained from the same method, this range chart monitors only random error and thus is not adequate for ensuring the accuracy of the analytical method. When the duplicates are obtained from two different laboratory methods, then the range chart actually monitors both random and systematic errors but cannot separate the two types of errors. The interpretation becomes more difficult, particularly when there are stable systematic differences or biases between the two analytical methods. Multiplicative factors may be necessary to deal with proportional differences, and additive factors may be necessary to allow for constant differences. Interpretation of observed differences becomes more qualitative nevertheless, this procedure still provides a useful way of monitoring the consistency of the data being generated by the laboratory. 

The idea of monitoring accuracy and precision was developed by Walter Shewhart [18] and the target value here was the known concentration of analyte in a control standard. The range graph monitors the precision, and the target value is the capability that it is necessary to establish in order to set up the control chart. Process capability will be limited by the random errors involved in measurements rather than error in preparing the standards. 

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