A c-chart is an attributes control chart used with data collected in subgroups that are the same size. C-charts show how the process, measured by the number of nonconformities per item or group of items, changes over time. Nonconformities are defects or occurrences found in the sampled subgroup.
Why do we use P chart?
A p-chart is an attributes control chart used with data collected in subgroups of varying sizes. Because the subgroup size can vary, it shows a proportion on nonconforming items rather than the actual count. P-charts show how the process changes over time.
A u-chart is an attributes control chart used with data collected in subgroups of varying sizes. U-charts show how the process, measured by the number of nonconformities per item or group of items, changes over time. Nonconformities are defects or occurrences found in the sampled subgroup.
The seven QC tools are:
- Stratification (Divide and Conquer)
- Check Sheet (Tally Sheet)
- Cause-and-effect diagram (“fishbone” or Ishikawa diagram)
- Pareto chart (80/20 Rule)
- Scatter diagram (Shewhart Chart)
- Control chart.
An NP chart is a data analysis technique for determining if a measurement process has gone out of statistical control. It is sensitive to changes in the number of defective items in the measurement process. The “NP” in NP charts stands for the np (the mean number of successes) of a binomial distribution.
An np-chart is an attributes control chart used with data collected in subgroups that are the same size. Np-charts show how the process, measured by the number of nonconforming items it produces, changes over time.
How do I choose the appropriate type of control chart?
|Attribute||Standardized p||Standardized Proportion Defective|
|Attribute||c||Number of Defects|
|Attribute||u||Number of Defects per unit|
|Attribute||Standardized u||Standardized Number of Defects per unit|
Statistical Process Control (SPC) is an industry-standard methodology for measuring and controlling quality during the manufacturing process. Quality data in the form of Product or Process measurements are obtained in real-time during manufacturing.
A control chart is a popular statistical tool for monitoring and improving quality. Originated by Walter Shewhart in 1924 for the manufacturing environment, it was later extended by W. Edward Deming to the quality improvement in all areas of an organization (a philosophy known as Total Quality Management, or TQM).
Also called: statistical process control. The control chart is a graph used to study how a process changes over time. Data are plotted in time order. A control chart always has a central line for the average, an upper line for the upper control limit and a lower line for the lower control limit.
The check sheet is a form (document) used to collect data in real time at the location where the data is generated. The data it captures can be quantitative or qualitative. When the information is quantitative, the check sheet is sometimes called a tally sheet.
A Pareto chart, named after Vilfredo Pareto, is a type of chart that contains both bars and a line graph, where individual values are represented in descending order by bars, and the cumulative total is represented by the line.
A run chart is a line graph of data plotted over time. By collecting and charting data over time, you can find trends or patterns in the process. Because they do not use control limits, run charts cannot tell you if a process is stable. However, they can show you how the process is running.
Three-sigma limit (3-sigma limits) is a statistical calculation that refers to data within three standard deviations from a mean. Control charts are used to establish limits for a manufacturing or business process that is in a state of statistical control.
Process capability is the repeatability and consistency of a manufacturing process relative to the customer requirements in terms of specification limits of a product parameter. This measure is used to objectively measure the degree to which your process is or is not meeting the requirements.
In statistical quality control, the and s chart is a type of control chart used to monitor variables data when samples are collected at regular intervals from a business or industrial process.
The primary Statistical Process Control (SPC) tool for Six Sigma initiatives is the control chart — a graphical tracking of a process input or an output over time. In the control chart, these tracked measurements are visually compared to decision limits calculated from probabilities of the actual process performance.
Variables control charts plot continuous measurement process data, such as length or pressure, in a time-ordered sequence. In contrast, attribute control charts plot count data, such as the number of defects or defective units.
The control chart was invented by Walter A. Shewhart working for Bell Labs in the 1920s.
A Control Plan is a method for documenting the functional elements of quality control that are to be implemented in order to assure that quality standards are met for a particular product or service. The intent of the control plan is to formalize and document the system of control that will be utilized.
Variation (Special Cause) Special cause variation is a shift in output caused by a specific factor such as environmental conditions or process input parameters. It can be accounted for directly and potentially removed and is a measure of process control.