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The process capability analysis module builds on the basics of statistics. Here you will gain a deeper insight into data types and distribution forms.
In this module, you will learn, among other things, how to present and interpret the performance of processes in various key figures. You will gain a basic understanding of whether the statements in your data are statistically relevant or not. You will learn to interpret diagrams correctly and to think and act in terms of probabilities.
● Data acquisition
● Types of diagrams
● Normal distribution
● Binomial distribution
● Poisson distribution
● Weibull distribution
● Sigma level
● z-value table
● Process performance
● Specification limits
● Accuracy
● Precision
● Cp & Cpk
● z-value vs. Cpk
● Process capability DPMO
● DPU
● Ppm
● Long-term & short-term capability
● Sigma Shift
● Test for normal distribution
Process capability analysis is a statistical method used to evaluate the ability of a process to produce products or results within defined specification limits. This tool is used to measure and improve the consistency and reliability of production processes by evaluating data on process performance and comparing it with the specified tolerances.
Process capability analysis has evolved as an essential part of QA in manufacturing and other operational areas since the mid-20th century. With the increasing importance of Six Sigma and other QA programs in the 1980s, these techniques gained importance to ensure lower defect rates.
Process capability analysis is widely used in the manufacturing industry as well as in other sectors that control complex processes, such as pharmaceuticals, automotive and electronics manufacturing. It helps organizations understand, monitor and optimize processes to ensure consistent quality.
With more than 4,000 projects and case studies, Alphadi is a leader in the field of Lean Six Sigma and Sales Process Engineering. We advise you holistically so that your goals are achieved sustainably and in the long term.
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