Target control chart

Target control charts are control charts with fixed quality criterions. In the contrary to classical control charts of the Shewhart-type these control charts operate without statistically evaluated values. 

Different Control Charts Target Control Charts -1... 

We can convert all types of classical control chart (X-chart, blank value, recovery, range control chart etc.) into target control charts. 

Situations for which a target control chart is appropriate are described in this slide. 

The control samples for the target control charts and their measures are the same as for the classical control charts. The limits are given by different external quality criterion, described in the slide. 

The chart is constracted with an upper and lower limit. A pre-period is not necessary. The target control chart of the range and in some cases also of the blank only needs the upper limit. 

This shde contains hnks to EXCEL-sheets from ExcelKontrol 2.1. This sheets can be nsed to mn control charts with checks for out-of-control situations and with graphical displays. In the electronic material you will find the whole zipped program, which also allows target control charts. 

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. 

In each case, the aim of quality control charts4 (QCC) is the representation of quality target values x0 (standard values) and their statistical limits. A control chart usually consists of five lines as shown in Fig. 4.14. 

According to the character of the target value Q several types of control charts can be distinguished ... 

This is the simplest type of control chart. It is typically used to monitor day-to-day variation of an analytical process. It does so by monitoring the variation of a quality control (QC) sample or standard when measured by the process. Measurement value is plotted on the v-axis against time or successive measurement on the x-axis. The measurement value on the v-axis may be expressed as an absolute value or as the difference from the target value. The QC sample is a sample typical of the samples usually measured by the analytical process,... 

If control charts are transferred to analytical chemistry the first thing to do is to assign the target value. If a reference material / certified reference material (RM/CRM) is used, the certified value can be used as the target value. This is advisable only, if the mean of the measnrements is close to the reference valne. Otherwise out-of-control sitnations would occur very frequently. So in most cases the arithmetic mean of the measurements is used as target value... 

The Cusum Control Chart is a very special chart from which a lot of information can be drawn. Cusum is the abbreviation for cumulative sum and means the sum of all differences from the target value. Every day the difference of the control analysis from the target value is added to the sum of all the previous ddferences. 

This slide shows a target eontrol chart for ammoitia reference material measurements. The ehart was eonstraeted with the Exeel tool ExeeUControl 2.1, whieh also is ineluded in the eleetroiue material to this book. In eontiaiy to the classical control chart here only two limits and one out-of-eontrol situation (outside eontrol limits) are usually used. 

CUSUM Control Chart A CUSUM chart provides an efficient way of detecting small shifts in the mean of a process (l/2 a), the chart is usually used.The CUSUM chart incorporates information contained in a sequence of sample points. It keeps track of the cumulative sum of the deviations between each sample point (a sample mean) and a target value. Unlike the x chart, which often bases its out-of-control decision on just the most recently collected sample, the CUSUM calculated for a sample point carries the history prior to that sample. For example, a sequence of sample points above the centerline can trigger an out-of-control signal although all of them stayed well below the UCLs of the x chart. 

A control chart is a visual representation of confidence intervals for a Gaussian distribution. The chart warns us when a monitored property strays dangerously far from an intended target value. 

Product appearance was unremarkable. The pH was examined using a control chart. Because this is a single point observation, the moving range method was employed. The chart disclosed that the process operates within the calculated control limits. No trends were apparent. Individual batch results all met specification, and the process average (4.07) is close to the target value of 4.10. (See Fig. 11.)... 

The alcohol content averaged 15.09%, or 0.09% above target. Individual batches met specification in every instance. The control chart (Fig. 12) was unremarkable in terms of trends or tests for pattern instability. Batch 3 is slightly below the process average, effectively ruling out overaddition of alcohol as a factor in the low specific gravity previously observed. 

The concentration of active ingredient D1 for batch to batch is shown in Figure 13. The mean potency of all batches is 0.1 mg/5 ml above target. The control chart did not respond to tests for unnatural patterns and trends. It is noteworthy that the calculated UCL (16.7 mg/5 mL) for the 20 batches in this study exceeds the release specification for the product (15.5 to 16.5 mg/5 ml. A probability thus exists that a batch may eventually fail to meet the release criteria. Raw material purity is not a factor in the potency of an individual batch because it is taken into consideration at the time of manufacture. A possible explanation for the wide historical control limits is the assay methodology for... 

A cumulative sum (or cusum) chart is a type of control chart that can detect changes in process average more powerfully than an x chart. A reference value K is chosen. K can be the process target value, historical average, or any convenient value. As new values xh. .., xn are observed, the cumulative sums... 

When conducting an inspection, several target areas must be evaluated. Control limits or "charts" are helpful and should be established by plotting the defined limits of acceptable quality control. These charts are important tools for assessing laboratory precision, accuracy, and reproducibility. They can be based on a curve established from the high, mid, and low concentrations of a standard analyte. Either the mid level or the average of the three concentrations then becomes the mid-line for the control chart. Acceptable levels of fluctuation for routine mid-level standards,... 

Control charts display the data (and variance) in the order they occur with statistically determined upper and lower control limits. The SPC charts are used to monitor the process for maintenance of the target to zero and then to determine whether process changes have accomplished their desired quality effect. ... 

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. 

The Asymptotic Mean Square Deviation (AMSD) was used as the performance measure to compare different scenarios, since it incorporates the deviations from the target and the variability (particularly useful when a process is submitted to a disturbance). Besides the use of AMSD, the Average Run Length (ARL) was applied to evaluate the performance of each control chart. 

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