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Defects and defectives - Minitab
It depends on the severity of the defect. New cars may have several defects, some of which may not even be noticed by the customer. However, if the car contains a defect that is measured and reported, the car (or part of the car) may be considered defective. Consider the loan application process. In this case, the processing department is the ...

Attributes control charts in Minitab
A unit may have many defects, but the unit itself is either defective or nondefective. For example, a scratch on a metal panel is a defect. If several scratches exist, the entire panel may be considered defective. Select your attribute control chart based on whether your data follow a binomial or a Poisson distribution.

All statistics and graphs for - Minitab
Rejectable quality level (RQL or LTPD) The rejectable quality level (RQL) is the highest defective rate or defect rate that the consumer is willing to tolerate in an individual lot. The RQL describes what the sampling plan will reject, and the AQL describes what the sampling plan will accept.

What are DPU, DPO, and DPMO? - Minitab
Defects per million opportunities (DPMO) is the number of defects in a sample divided by the total number of defect opportunities multiplied by 1 million. DPMO standardizes the number of defects at the opportunity level and is useful because you can compare processes with different complexities.

Enter your data for Attributes Acceptance Sampling - Minitab
In Acceptable quality level (AQL), enter a number to represent the highest defective rate or defect rate from a supplier's process that is considered acceptable. You want to design a sampling plan that accepts a particular lot of product at the AQL most of the time.

Example of a weighted Pareto Chart - Minitab
The weighted Pareto chart shows that stitching errors, which account for 23.3% of the total number of defects in the unweighted Pareto chart, account for 30.5% of the total defect costs.

Interpret the key results for U Chart - Minitab
In This Topic Step 1: Determine whether the defect rate is stable and in control Step 2: Identify which points failed each test

Overview for Binomial Capability Analysis - Minitab
Use Binomial Capability Analysis to determine whether the percentage of defective items meets customer requirements. Use when each item is classified into one of two categories, such as pass or fail. Using this analysis, you can do the following: Determine whether the process is in control. Estimate the percentage of defective items for each sample and across all samples (%defective). Assess ...

Data considerations for Product Report - Minitab
A defect is any departure from specifications. A defect does not necessarily mean that the product or service cannot be used, just that it wasn't as intended. Consider a loan application process. You sample several forms to estimate the defect rate. One application has 7 incorrect entries—there are 7 defects present on this form.

All statistics for Pareto Chart - Minitab
Percent is calculated by (count for type of defect/total number of defects) x 100. The height of the bars of the histogram represents the percentage of each category, which is shown on the right Y-axis.

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