Control charts have two general uses in an improvement project. This article provides an overview of the different types of control charts to help practitioners identify the best chart for any monitoring situation.
Control chart stability (CCS) is not always needed for either predictions or baseline estimates for process improvement. By recognizing the limitations of CCS, better prediction methods can be used that require less effort.
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To escape from post-financial crisis times, financial services companies need to effectively and efficiently manage their risks. This article showcases how financial services can leverage FMEA and control charts to manage their operational risk and reduce costs.
Learn how best to introduce statistical process control in an existing production environment where not all processes are in control and fully capable.
This article describes how earned value management (EVM) indexes and control charts may be used in tangent to capture more insight from project performance.
Applying univariate control charts is possible but inefficient and can lead to erroneous conclusions when working with more than one process variable. Instead, use multivariate control charts.
Among other benefits, a run chart is used to determine whether the central tendency of a process is changing. Learn step-by-step how to create and then interpret a run chart.
Knowing whether a process is in control and stable is paramount to producing a product or service that meets customer needs. In this hour-long Minitab training course, Eduardo Santiago covers many useful topics related to statistical process control.
Many quality professionals have declared that pre-control charts have gone the way of the Dodo bird. Before writing them off, however, learn more about pre-control charts and how they compare to control (or Shewhart) charts.
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