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Application Notes – Pattern Category What classes of SMD components is this category used for? The pattern category is typically used for components that cannot be described well by the leaded, leadless, or area array categories. A good candidate for the pattern category is a component that can be described by a set of geometric features. Devices commonly placed with this category include shields, lids, and some connectors.

Examples of components typically centered with the Pattern category:

NOTE: This document is not meant to be an exhaustive explanation of the Pattern category. Please refer to Voyager for more details about the category. What pattern shapes are supported? The pattern algorithm supports a wide variety of features. Here is a list of currently supported features:

Corner (NE, NW, SW, SE) Triangle Rectangle Swiss cross Diamond Disc Lead (N, S, E, or W) Vertex (N, S, E, or W)

The most commonly used patterns are corners and discs. How does the algorithm find individual pattern features?

The algorithm attempts to find programmed features based on edge detection techniques. The image to the left depicts the finding of a NW corner on a shield. Note that this process takes place internally and is not visible during normal operation of the machine.

Extrapolated corner location

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How does the algorithm work? To help explain the Pattern category from a user-interface perspective, we start from the Vision tab of a pattern component definition.

There are two classes of patterns in the definition of a pattern component: Rough: Rough patterns are found as a prelude to a more accurate “precise find” using precise patterns. Rough patterns are optional – a component can be centered with only precise patterns. Precise: Precise patterns are either used exclusively, or in conjunction with rough patterns in a rough-precise find scenario. A pattern component definition includes the field, Minimum Precise, where the user specifies the minimum number of precise patterns that must be found in order to place the part. The advantage of rough-precise find is that the rough find determines a first estimate of the location of the component which is then used as a starting point for finding precise features. Since the rough center of the component has been determined, small search areas can be programmed for the precise find. This increases the robustness of the precise find. This technique helps compensate for loose part presentation that forces the user to program large feeder pick tolerances. To summarize, the user has the following programming options:

Programming approach Application

Use all precise patterns Small number of patterns, good contrast, and no nearby satellite features. Most common.

Use rough-precise find A need to find precise features that may be surrounded by other features. Less common.

Select the Process… button to set up a Rough-Precise find.

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Other Pattern Programming Terms % Confidence The field % Confidence sets the minimum acceptable “correlation score” that each feature must exhibit as a result of the image processing in order to be found. Note that the same value for confidence applies to all the features in the component definition. Typical confidence levels are in the 80% range. It is not recommended to reduce the confidence below 50% as unexpected features may be found. Inspection Type There are two choices for Inspection Type: High Speed or High Accuracy. With the high speed option, the algorithm finds pattern features to within one pixel. With the high accuracy option, the algorithm uses additional image processing to find the pattern features with sub-pixel accuracy. High accuracy processing is somewhat more time-consuming and is usually not necessary for the types of components placed using the pattern algorithm. The general rule is to start with high speed centering and move to high accuracy based on a specific performance requirement.

Note: High Speed and High Accuracy inspection types should not be confused with the Accuracy selection in the Heads tab of the component definition. This selection refers to the speed at which the machine runs when placing the component. Critical Patterns In addition, a pattern feature can be labeled as “critical”. A pattern labeled critical must be found by the vision system for the component to be placed. If the vision system fails to find a critical pattern, the component is rejected regardless of whether the Minimum Precise requirement is met.

Examples

Example 1: A simple rectangular shield

• Program the four corners of the shield. • By default the four corners are configured as

precise find patterns. • Rough-precise find is not necessary for this

component.

The SE Corner has been defined as a critical pattern. It must be found for the component to be placed.

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Example 1 (continued) Selecting the Process button on the Vision tab shows that the four programmed features are defined as Precise patterns by default.

Example 2: A simple rectangular shield with an orientation feature

Assume that the shield has a unique hole that can be used as an orientation feature. • Program the four corners of the shield. • Program the orientation hole as a disk.

NOTES: By default all of the patterns are configured as

precise find patterns. Rough-precise find is not necessary for this

component. • Configure the disc as a critical feature. If the shield is

presented at the wrong orientation, the four corners may be found but the disc will not. Since the disc is configured as a critical pattern, the component will be rejected if the disc is not found.

Disc programmed as a critical feature.

Feature used for orientation

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Example 3: Rough-precise find with a pinned connector

Assume that the component has a series of pins that must be used for centering. Furthermore assume that there are non-programmed features surrounding the pins. • Program the two corners of the shield as rough find

patterns. • Program the seven discs (corresponding to the pins)

as precise find patterns. • Program the indicated disc as a critical pattern. This

pattern is used to assure correct orientation. • Set the minimum number of precise patterns to 6. Pattern List:

Critical pattern

Program rough find using the two corners.

Define the remaining disc patterns as precise find features.

The machine attempts to find the rough patterns first. If the rough find is not successful, the component is rejected. If the rough find succeeds, a tight search area (defined by the precise find search area) is drawn around the location of the precise features. In this example, the critical disc must be found and 6 of 7 precise patterns must be found for the component to be placed. Another approach to assure correct orientation is to set the Minimum Precise value to 7. In this case no critical features are required.

Precise find search area

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What if my component has rounded corners? For corners and vertices, Dim 3/4 in the Pattern tab are used to define an “ignore” zone that can be used for rounded corners or chamfered corners.

Example: A shield has a rounded corner. Define a 20-mil corner with a 5-mil ignore zone to compensate for the rounded corner. The vision system will find the two line segments and extrapolate a corner point.

NOTE: Dim 3/4 cannot exceed 25% of the length of the respective corner feature. For example, assume that Dim1 = 50-mils and Dim2 = 40-mils. Dim3 can be no greater than 12.5-mils and Dim4 can be no greater than 10-mils. What types of Pattern inspections are available? The Vision tab of the pattern component definition contains inspection options.

Three inspection types are available:

Location Tolerance X/Y: In this inspection, the found points are overlayed with the model. The vision software then determines whether the distance between each found/model pair is within the programmed location tolerances.

Relative Distance: In this inspection, the distance between features is checked against the model. The vision software then determines whether the pattern spacings are within the programmed distance tolerance.

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How small a pattern can be resolved with a given camera? The answer to this question depends on the camera used to center the component. By default, the vision system requires a minimum of 6 pixels per pattern for centering and 6.5 pixels per pattern for centering and inspection. Example: Assume we are working with a hypothetical 2.0-mil/pixel camera.

• Minimum pattern size for centering = 6-pixels × 2.0-mil/pixel = 0.012” (0.305-mm) • Minimum pattern size for centering/inspection = 6.5-pixels × 2.0-mil/pixel = 0.013” (0.330-mm) Keep in mind that for patterns that take up a small number of pixels (< 10, for example) the ability of the algorithm to distinguish between pattern types (e.g. a square versus a circle) is diminished. If shape recognition and discrimination is important for your application, a higher magnification camera may be required. What are the typical vision failure modes for pattern components? The most prevalent failure mode for pattern components is a failure to find some or all of the programmed features. Error messages indicating this condition include “Missing features” and “No features found”. Possible causes/solutions • Poor lighting choice The pattern algorithm requires the component to have reasonably good contrast. Missing features are frequently the result of insufficient contrast. Consider the images below:

Poor lighting choice Better lighting choice • Inaccurate component geometry in the definition After features are found on the image of a component, the algorithm compares the found features to the geometric model of the component. If the model differs sufficiently from the image, pattern features will not be assigned and find errors will likely result. It is good practice to compare the programmed geometry to the actual component geometry to make sure that the definition is accurate.

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• Poor choice of features It is best to define pattern features that are unique in their area of the component. Example:

Corner defined – good choice Circle defined – poor choice

The corner is a good choice since there is only one corner candidate in the field-of-view.

The circle is a poor choice as there are many circle candidates in the field-of-

view. This can lead to component rejection. • Corner rounding Depending on the geometry of a particular component and the magnification of the camera used to find the part, corners may appear rounded. For such component/camera combinations, rounded corner programming as described previously is strongly recommended. Two examples are provided below:

Rounded corner programming recommended. Rounded corner programming not required.