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Process Capability is the extent to which a stable process meets customer specifications. It applies to all businesses and industries and to aspects of life. Learn concepts that can be put to immediate use in the workplace to help you measure and improve processes.

Gain an understanding of process capability and how it can be used to predict the potential failure rate from a process. Learn the statistical techniques that are used to predict the complete output of a process based on a relatively small sample. A Process Capability Analysis is a predictive tool that enables right decisions to be made based on data and facts. You will use practical exercises to learn how to carry out effective process capability studies.

Cmk (capability machine index). If you also want to study the position of the machine’s capability in relation to the tolerance limits, you use the Cmk index, which describes the capability corrected for position. It is not much use having a high Cm index if the machine setting is way off center in relation to the middle of the tolerance range. A high Cmk index means, then, that you have a good machine with a small spread in relation to the tolerance width, and also that it is well centered within that width. If Cmk is equal to Cm, the machine is set to produce exactly in the middle of the tolerance range

Using Minitab to hands-on Practice with Normal, Weibull, Binomial Process Capability (Cp, Cpk, Cm, Cmk, Pp, Ppk, Cpm, Z Scores), Box Cox & Johnson.

What you'll learn

Basic Concepts of Process capability: Cp, Cpk, Cm, Cmk, Pp, Ppk, Cpm, Z Scores, USL, LSL

Step by Step Process to conduct study and Analysis in Minitab

Compute Cp, Cpk, Cm, Cmk, Pp, and Ppk values for processes using continuous data.

Process Capability Concepts: Normality, Stability, Six Pack Analysis, Long Term Vs Short Term, Observed, Expected, Overall, Within, Z Bench

Data Transformation Techniques: Box-Cox and Johnson Transformation, Lambda

Decisioning which Process Capability Study to perform for all practical challenging situations - Normal, Weibull, Binomial

Determine how well a process and machine is able to meet customer requirements by measure of process capability and identify when one process is more capable than another.

Distinguish capable from non-capable processes.

Interpret Cp, Cpk, Cm, Cmk, Pp and Ppk and relate them to a defect level.

Identify how sample measurements are used to estimate population values.

Determine which Control Chart type is most appropriate for monitoring a particular process parameter.

Take relevant process information for a process using discrete data.

Calculate process assessment measurements.

Look at a powerful operation metric called Rolled Throughput Yield.

Detail of Course Outline: