For example, one article meets the specification then its good quality otherwise poor quality.
Role of Statistics Quality Control Chart
The variation in any items produced in any manner is not acceptable. Maybe the variation occurs due to chance / random factors and assignable causes.
1.Chance / Random Factors:
If the variation occurs due to some inherent pattern of variation and no cause can be assigned to it, it is called chance factors or random factors. Chance factors are tolerable and do not affect the quality of the product.
These kinds of situations said to be the process is under statistical control.
2.Assignable Causes:
The deviation observed from a given specification is called assignable causes. These variations are not in random nature.
The role of statistical control is to collect and analyze relevant data for the purpose of detecting whether the process is under control or not. The Statistics Quality Control Charts are used for describing the patterns of the variation.
Statistics Quality Control Charts developed by Dr. W A Shewhart in 1924. The most frequently used control charts are for mean X bar, Range R, Root Mean Square, Number of defects, etc…
In general Statistics Quality Control Chart contains three lines namely,
1) Central Line (CL)
2) Lower Control Limit (LCL)
3) Upper Control Limit (UCL).
Statistics Quality Control Chart used to identify the chance pattern, the variation due to assignable causes need to identify and removed. This brings the process under control. The 3 sigma limits are usually used for control charts.
Mainly four statistical quality control tools are available.
1) Statistics Quality Control Chart for variables
Consider for measurable data on quality characteristics that are usually continuous in nature. The charts are used for the X bar, Range, and Sigma charts.
2) Statistics Quality Control Charts for fraction of defects
Used for when units are classified as defective or non-defective. These charts mainly known as p charts.
3) Statistics Quality Control Charts for the number of defects per unit
It deals with discrete variables which are a count of the number of defects per unit. Mainly c chart used for this purpose.
4 Acceptance Sampling procedure
Acceptance inspection has to be carried out by the manufacturer. It’s not possible to inspect all the items, thus sampling needs to carry out.
The advantage of the R chart is easier to calculate and better than the sigma chart in the case of small samples. Range and standard deviations are in the same direction in the case of samples.
In a small number of samples, R and sigma chart conclusions are almost the same.
When do we need to use the X bar chart?
In case of R chart is not under control should not be prepared the X bar chart.
Conclusion
How to interpret the control chart, that is more important and it’s mentioned below.
If all the points lie within control limits, the process considered under control. Otherwise not.
If any pattern observed in the control charts indicates an assignable cause of variation.
