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Making Sense of Accuracy, Repeatability, and Specification for Automated Fluid Dispensing
March 11, 2014 |Estimated reading time: 1 minute
A dispensing motion system can be made to perform better or worse under different operating conditions. This article will explain accuracy and repeatability, and how they can be applied to different specifications. It will also discuss key considerations when interpreting accuracy and repeatability for decision making.
Figure 1: Accuracy.
Accuracy vs. Repeatability
“Accuracy” and “repeatability” are commonly encountered terms used as performance characteristics of fluid dispensing equipment. Unfortunately, these terms are often confused or misunderstood. Accuracy (Figure 1) is a measure of how close an achieved position is to a desired target position. Repeatability (Figure 2) is a measure of a system’s consistency to achieve identical results across multiple tests. The ultimate goal is to have both a highly accurate and highly repeatable system.
Figure 2: Repeatability.
Repeatability is often expressed as the range (variation) of measurements achieved for multiple test points under consistent test conditions. Figure 2 illustrates examples of repeatable and non-repeatable processes. Thus, for the purposes of specifications, achieving smaller repeatability numbers is better because it indicates tighter groupings or a smaller range within the test data distribution. Repeatability differs from accuracy in that it is concerned with variations in achieved results relative to each other within a given sample size.
In a fluid dispensing system, accuracy is the ability of the equipment to dispense to a target position. An accurate system is one that dispenses exactly at the target location. In order to measure accuracy, though, we really measure the individual test offset error between the achieved result and the target (ideal), as shown in Figure 1. Thus, accuracy specifications are really expressions of the system inaccuracy and achieving a smaller specification means a system is more accurate. When specifying accuracy, however, it should not be based on a single test result, but many test results. As such, it is common practice to use the average (mean) error amongst a range of test data to express the accuracy of the entire test data distribution. Read the full article here.Editor's Note: This article originally appeared in the February 2014 issue of SMT Magazine.