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In many existing AFP cells manual inspection of composite plies accounts for a large percentage of production time. Next generation AFP cells can require an even greater inspection burden. The industry is rapidly developing technologies to reduce inspection time and to replace manual inspection with automated solutions. Electroimpact is delivering a solution that integrates multiple technologies to combat inspection challenges. The approach integrates laser projectors, cameras, and laser profilometers in a comprehensive user interface that greatly reduces the burden on inspectors and decreases overall run time. This paper discusses the implementation of each technology and the user interface that ties the data together and presents it to the inspector.

Incorporation of laser projectors in AFP machine cell controller reduces ply boundary inspection time, on-part course identification and part probing.

Inspection of fasteners prior to installation is critical to the quality of aerospace parts. Fasteners must be inspected for length/grip and diameter at a minimum. Inspecting the fasteners mechanically just prior to insertion can cause additional cycle time loss if inspection cannot be performed at the same time as other operations. To decrease fastener inspection times and to ensure fastener cartridges contain the expected fastener a system was devised to measure the fastener as it travels down the fastener feed tube. This process could be adapted to inspection of fasteners being fed to the process head of a running machine eliminating the mechanical inspection requirement and thus decreasing cycle time.

In AFP manufacturing systems, manually inspection of parts consumes a large portion of total production time and is susceptible to missing defects. The aerospace industry is responding to this inefficiency by focusing on the development of automated inspection systems. The first generation of automated inspection systems is now entering production. This paper reviews the performance of the first generation system and discusses reasonable expectations. Estimates of automated inspection time will be made, and it will be shown that the automated solution enables a detailed statistical analysis of manufactured part quality and provides the data necessary for statistical process control. Data collection allows for a reduction in rework because not all errors need to be corrected. Expectations will be set for the accuracy for both ply boundary and overlap/gap measurements. The time and resource cost of development and integration will also be discussed.

Precision hole inspection is often required for automated aircraft assembly. Direct contact measurement has been proven reliable and accurate for over 20 years in production applications. At the core of the hole measurement process tool are high precision optical encoders for measurement of diameter and countersink depth. Mechanical contact within the hole is via standard 2-point split ball tips, and diametric data is collected rapidly and continuously enabling the system to profile the inner surface at 0 and 90 degrees. Hole profile, countersink depth, and grip length data are collected in 6 seconds. Parallel to the active process, auto-calibration is performed to minimize environmental factors such as thermal expansion. Tip assemblies are selected and changed automatically. Optional features include concave countersink and panel position measurement.

Accurate measurement of countersinks in curved parts has always been a challenge. The countersink reference is defined relative to the panel surface which includes some degree of curvature. This curvature thus makes accurate measurements very difficult using both contact and 2D non-contact measurements. By utilizing structured light 3D vision technologies, the ability to very accurately measure a countersink to small tolerances can be achieved. By knowing the pose of the camera and projector, triangulation can be used to calculate the distance to thousands of points on the panel and countersink surface. The plane of the panel is then calculated using Random Sample Consensus (RANSAC) method from the dataset of points which can be adjusted to account for panel curvatures. The countersink is then found using a similar RANSAC method.