![]() Although predictable, this process does not consistently meet customer needs. This type of process will produce a constant level of nonconformances and exhibits low capability. This process is predictable and its output meets customer expectations.Ī process that is in the threshold state is characterized by being in statistical control but still producing the occasional nonconformance. This process has proven stability and target performance over time. When a process operates in the ideal state, that process is in statistical control and produces 100 percent conformance. Processes fall into one of four states: 1) the ideal, 2) the threshold, 3) the brink of chaos and 4) the state of chaos (Figure 1). If the process is unstable, the process displays special cause variation, non-random variation from external factors.Ĭontrol charts are simple, robust tools for understanding process variability. A process is in control when based on past experience it can be predicted how the process will vary (within limits) in the future. When a process is stable and in control, it displays common cause variation, variation that is inherent to the process. The descriptions below provide an overview of the different types of control charts to help practitioners identify the best chart for any monitoring situation, followed by a description of the method for using control charts for analysis. The most common application is as a tool to monitor process stability and control.Ī less common, although some might argue more powerful, use of control charts is as an analysis tool. Control charts have two general uses in an improvement project.
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