Abstract
Different control charts in combination with the process capability indices, Cp, Cpm and Cpk, as part of the control strategy, were evaluated, since both are key elements in determining whether the method or process is reliable for its purpose. All these aspects were analyzed using real data from unitary processes and analytical methods. The traditional x-chart and moving range chart confirmed both analytical method and process are in control and stable and therefore, the process capability indices can be computed. We applied different criteria to establish the specification limits (i.e., analyst/customer requirements) for fixed method or process performance (i.e., process or method requirements). The unitary process does not satisfy the minimum capability requirements for Cp and Cpk indices when the specification limit and control limits are equal in breath. Therefore, the process needs to be revised; especially, a greater control in the process variation is necessary. For the analytical method, the Cpm and Cpk indices were computed. The obtained results were similar in both cases. For example, if the specification limits are set at ±3% of the target value, the method is considered “satisfactory” (1.22<Cpm<1.50) and no further stringent precision control is required.
Highlights
IntroductionIt is impossible to determine the quality of a product. it is necessary that the manufacturing processes are in control and stable as well as all the involved unitary processes in order to reduce the process variability
Their performance is predictable, allowing out-of-control situations to be reliably detected. In this type of control chart, the first step is as follows: a set of process data are collected and analyzed all at once in a retrospective analysis, constructing different control limits in order to verify if the process is in control over the time during the collection of data
In industrial activities or in the laboratory, it is necessary to obtain information about the performance of the process or analytical method when it is operating under statistical control
Summary
It is impossible to determine the quality of a product. it is necessary that the manufacturing processes are in control and stable as well as all the involved unitary processes in order to reduce the process variability. Shewhart control charts are effective when the in-control process data are stationary (i.e., the process data vary around a fixed mean in a stable manner) and uncorrelated Under these conditions, their performance is predictable, allowing out-of-control situations to be reliably detected. A limitation of Shewhart control charts is that it uses only the information about the process contained in the last analyzed sample, ignoring any information provided by the set of collected data This fact makes the Shewhart control chart relatively insensitive to small process shifts, about 1.5 standard deviations or less. Roberts [2] and later Crowder [3] and Lucas and Saccucci [4] introduced the EWMA control chart which analyzed different aspects of interest in detecting small changes in the process Other authors, such as Lucas [5], Hawkins and Olwell [6], indicate that the Cusum control is more effective than the traditional Shewhart control chart in this type of situations
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