Discrete or attribute data deals with counts. There are two types of attributes - defectives and defects.
Defectives are number of parts that are non conforming to a standard. Defective counts are parts that fail to meet a specific criteria set by the customer.
Defects on the other hand are non conformities or problems/issues within parts. A single part can have multiple defects i.e. the defect count can be greater than the total number of parts inspected.
It is important to understand the fundamental difference between defects and defectives because the statistics, tools are different for each. Here we will look at the stats/charts for defective data.
Defective data can be presented in several ways. There are 3 ways to calculate and chart defective data.
1. p or proportion
2. % or percent
3. ppm or parts per million
Most continuous improvement practitioners get confused between the 3 ways and this causes misinterpretation of the information presented. To clearly understand the difference, we will use sample data and perform the calculations.
For a set of 250 samples, quality inspection found 12 bad parts i.e. 12 defectives.
Defectives are number of parts that are non conforming to a standard. Defective counts are parts that fail to meet a specific criteria set by the customer.
Defects on the other hand are non conformities or problems/issues within parts. A single part can have multiple defects i.e. the defect count can be greater than the total number of parts inspected.
It is important to understand the fundamental difference between defects and defectives because the statistics, tools are different for each. Here we will look at the stats/charts for defective data.
Defective data can be presented in several ways. There are 3 ways to calculate and chart defective data.
1. p or proportion
2. % or percent
3. ppm or parts per million
Most continuous improvement practitioners get confused between the 3 ways and this causes misinterpretation of the information presented. To clearly understand the difference, we will use sample data and perform the calculations.
For a set of 250 samples, quality inspection found 12 bad parts i.e. 12 defectives.
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