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The Control Chart Package allows sophisticated statistical process control (for example, by plotting Shewhart I-Charts as recommended in the USP <1010>). Detect out-of-control data by defining upper / lower control limits and control rules (Western Electric, Nelson, and user-defined). A status display provides feedback about the impact of a rule violation. Optional features include events to mark changes in the process, sidecharts to contain basic statistics in a box plot, the creation of subcharts for a specific range, and confidence intervals. Moreover, the data series can be colored by a secondary factor such as the operator name. Aggregate directly from independent assay runs or from manual input.
The following list highlights the USP <1010> methods supported by the Control Chart Package:
Extensive and independent configuration options on I-charts
Parameter statistics to view descriptive details for every chart
Statistical process control by defining control rules and control limits
Nelson & Western Electric Company (WECO) rules
Calculation of the standard deviation
The Control Chart Package supports you in statistical process control independently whether the data is derived from biological assays or your individual work environment.
You can plot data series into customizable charts to fit your needs: There are options to add intervals, sidecharts, and event markers, to create subcharts, or to define the coloring of data points by secondary characteristics or by threshold values, for instance. Furthermore, rule sets allow you to detect out-of-control data by configuring control limits and rules. A status display about the criticality of a rule violation provides visual feedback at a glance for you to take action on the process.
The Control Chart Package covers a broad range of use cases not limited to biological assays.
You can aggregate data from individual assay documents (for example, quantitative response assays, dose-response analysis assays, or microbial assays for antibiotics) or enter data of any type manually. For example, you can plot a data series to get a first glimpse of descriptive statistics. Based on the statistical characteristics, you can apply control limits and rules to monitor the process and reveal out-of-control data. Use events to mark changes in the process, for example, when you changed the cell culture or updated your SOPs. Moreover, you can create subcharts if you wish to monitor a specific range of data separately, such as the most recent days only. Finally, you are able to color data points by threshold values or a secondary characteristic like the operator to associate conspicuities accordingly.