Minitab I-MR Chart Configuration and Parameters PPT

This PPT slide, part of the 138-slide Six Sigma - Statistical Process Control (SPC) PowerPoint presentation, presents a practical example of using Minitab software for creating Individual-Moving Range (I-MR) control charts, a key tool in statistical process control. The left section displays the Minitab interface, specifically the path to access the I-MR chart functionality: Stat > Control Charts > Variable Charts for Individuals > I-MR. This hierarchical navigation is crucial for users to efficiently locate the necessary tools within the software.

The central part of the slide highlights the parameters for the I-MR chart, emphasizing the selection of variables, which in this case is labeled as "Process Y." This indicates that the user can customize the chart based on specific processes they are monitoring. The right section of the slide outlines the options available for configuring the I-MR chart. It includes various parameters such as limits, tests for special causes, and the ability to display different types of data.

A notable feature is the list of out-of-control criteria, which are essential for identifying when a process may be deviating from expected performance. This list is based on the foundational work of Walter Shewhart, who established many of the principles of statistical process control in the 1920s. By understanding these criteria, users can better interpret the data generated by the I-MR chart and take appropriate actions to maintain process stability.

Overall, this slide serves as a concise guide for users looking to implement I-MR charts in Minitab, providing both a visual representation of the software interface and a foundational understanding of the underlying statistical principles.

This slide is part of the Six Sigma - Statistical Process Control (SPC) PowerPoint presentation.

Developed by a Senior Executive and Operational Excellence Coach with experience at organizations including NOKIA, MICROVENTION, and MAGELLAN, this presentation provides a detailed Introduction to Statistical Process Control (SPC) Charts.

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