Control charts are a type of statistical process control tool used to monitor and control a process over time. They are used to analyse and track the performance of a process and detect any changes or deviations from the expected or desired performance.
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Control charts (including types of control charts), typically involve plotting data points over time, with the mean, upper control limit (UCL), and lower control limit (LCL) also indicated on the chart. The mean is the central tendency of the data, while the UCL and LCL are calculated based on the data's standard deviation and represent the boundaries within which the process is expected to perform.
By monitoring the data points over time and comparing them to the control limits, control charts allow operators to quickly identify when a process is producing results that are outside of the expected range. This enables them to take corrective action before the process produces non-conforming products or services.
There are several different types of control charts, each with its own specific purpose and application. Some common types of control charts include:
X-bar and R chart: Used to monitor the central tendency and variability of a process.
Individual and Moving Range (I-MR) chart: Used to monitor the stability of a process over time when the sample size is one.
p-chart: Used to monitor the proportion of non-conforming units in a process.
c-chart: Used to monitor the number of non-conformities per unit in a process.
Control charts are a powerful tool for process improvement and quality control, allowing organizations to identify and address issues in their processes and achieve greater consistency and reliability in their operations.
Which control charts to use with attribute data and which one to use with continues data?
Control charts are classified into two types based on the type of data they are used to monitor: attribute control charts and variable control charts.
Attribute control charts are used with data that are categorical or discrete, such as the number of defective products or the proportion of non-conforming items in a sample. The two most commonly used attribute control charts are:
p-chart: This chart is used to monitor the proportion of non-conforming items or events in a sample. It is typically used when the sample size is large and the probability of non-conformities is relatively low.
c-chart: This chart is used to monitor the number of non-conformities per unit in a sample. It is typically used when the sample size is small and the probability of non-conformities is relatively high.
Variable control charts are used with continuous or numerical data, such as the weight or length of a product. The most commonly used variable control charts are:
X-bar and R chart: This chart is used to monitor the central tendency and variability of a process, based on the mean and range of the sample data.
X-bar and s chart: This chart is used to monitor the central tendency and variability of a process, based on the mean and standard deviation of the sample data.
Individual and Moving Range (I-MR) chart: This chart is used to monitor the stability of a process over time when the sample size is one.
In summary, the p-chart and c-chart are used with attribute data, while the X-bar and R chart, X-bar and s chart, and I-MR chart are used with continuous or variable data.
Comparing table of control charts
TABEL 1
Control Chart | Data Type | Purpose |
p-chart | Attribute | Monitors proportion of non-conforming items or events in a sample |
c-chart | Attribute | Monitors number of non-conformities per unit in a sample |
X-bar and R chart | Variable | Monitors central tendency and variability of a process, based on the mean and range of the sample data |
X-bar and s chart | Variable | Monitors central tendency and variability of a process, based on the mean and standard deviation of the sample data |
Individual and Moving Range (I-MR) chart | Variable | Monitors stability of a process over time when the sample size is one |
Note: There are other types of control charts as well, but these are the most commonly used ones.
Summary
Control charts are a type of statistical process control tool used to monitor and control a process over time. They enable operators to analyse and track the performance of a process and detect any changes or deviations from the expected or desired performance.
There are two main types of control charts: attribute control charts and variable control charts. Attribute control charts are used with data that are categorical or discrete, while variable control charts are used with continuous or numerical data.
The most commonly used attribute control charts are the p-chart and the c-chart. The p-chart is used to monitor the proportion of non-conforming items or events in a sample, while the c-chart is used to monitor the number of non-conformities per unit in a sample.
The most commonly used variable control charts are the X-bar and R chart, the X-bar and s chart, and the Individual and Moving Range (I-MR) chart. The X-bar and R chart and X-bar and s chart are used to monitor the central tendency and variability of a process, based on the mean and range or standard deviation of the sample data, respectively. The I-MR chart is used to monitor the stability of a process over time when the sample size is one.
Using control charts can help organizations identify and address issues in their processes, leading to greater consistency and reliability in their operations.
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"Every drop counts! Optimize your water use without sacrificing pressure."
Author: Robert Kurek (QE - Water And Energy Saving Industry) robertkurek.com (c)
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