C Chart Calculator
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What is a C Chart?
A C Chart, or Count Chart, is a powerful statistical tool used in quality control to monitor the number of defects (nonconformities) in a production sample. Unlike P Charts which measure the proportion of defective items, the C Chart focuses on the total number of individual defects found within a constant subgroup size. For example, it is used to count the number of surface scratches on a car door, the number of typos in a manuscript page, or the number of broken circuits on a motherboard.
How to Use the C Chart Calculator
Using our online C Chart calculator is straightforward. Follow these steps:
- Collect your data: Ensure you have a series of defect counts from samples that are of equal size.
- Input Data: Paste your numbers into the text area above, separating each entry by a comma or a new line.
- Calculate: Press the calculate button to instantly determine your control limits.
- Analyze: Review the Upper Control Limit (UCL), Lower Control Limit (LCL), and Center Line (c̄). The tool will also flag any data points that fall outside these limits, indicating a process that might be out of statistical control.
Formula for C Chart Calculations
The C Chart is based on the Poisson distribution. The following formulas are used to determine the control limits:
- Center Line (c̄): Total Defects / Number of Samples
- Upper Control Limit (UCL): c̄ + 3 √(c̄)
- Lower Control Limit (LCL): Max(0, c̄ - 3 √(c̄))
Frequently Asked Questions
When should I use a C Chart instead of a U Chart?
Use a C Chart when your subgroup size is constant (e.g., you always inspect exactly one square yard of fabric). If your subgroup size varies (e.g., you inspect different lengths of fabric), you should use a U Chart which tracks the average number of defects per unit.
What does "Out of Control" mean?
If a data point exceeds the UCL or falls below the LCL (though LCL is often zero), it suggests that an "assignable cause" is affecting the process. This means the variation is not just natural randomness and requires investigation.