Ensenso 3D cameras are revolutionizing aircraft cabin assembly by integrating into automated processes that ensure precise detection and alignment of drilling positions. This sophisticated method is part of the Digital Cabin Architectures and Design for Manufacturing (DiCADeMA) initiative, spearheaded by the German Aerospace Centre (DLR).
The project introduces a seamless digital framework in aircraft production, aiming to establish complete digital continuity from design through to manufacturing. A pivotal element in this process is the Ensenso 3D camera from IDS Imaging Development Systems GmbH, which facilitates highly accurate drilling alignment.
Marking Drilling Positions
The core objective of the DiCADeMA project is a continuous digital integration from aircraft design to production. Adjustments in cabin designs, such as seating arrangements or luggage compartment locations, are directly updated in digital design files and fed into the manufacturing planning stage.
Through simulation, these variations can be validated before any physical part is crafted
Through simulation, these variations can be validated before any physical part is crafted. Upon digital approval, production begins without delay. Within this digital transformation, a new automated system was developed to mark drilling positions on an aircraft frame prototype. The setup comprises connected systems: an autonomous mobile robot (AMR) approaches the desired frame section, where a lightweight robot adjusts the marking unit, positioned with the 3D camera. The Ensenso camera then undertakes fine alignment, supervised by a Manufacturing Execution System (MES) that manages all subprocesses.
Precise Correction Values
The Ensenso N36 camera is essential for capturing the workspace as a detailed 3D point cloud, which is then compared to the CAD data of the aircraft frame.
This step enables the detection of even minor deviations between the actual frame and the target design, generating precise correction values communicated to the MES. Through a standardized OPC UA interface, data transfers securely among the camera, robot, and control system. The MES decodes this data into specific robot instructions for positioning, achieving an accuracy within five millimeters, thereby enhancing the Ensenso camera’s performance without risking collisions during acquisition.
Iterative Minimization Process
Serving as a crucial interface between digital design and physical manufacturing, the Ensenso camera identifies local geometries, such as rivets and surfaces, and assesses captured point clouds against reference data from the CAD.
This assessment is facilitated by hand–eye calibration and an iterative minimization process, the result of which is a transformation matrix accurately describing drilling position corrections. Applying these corrections allows for precise drilling.
Demanding Environmental Conditions
A human operator follows the robot, using the marked positions to drill immediately
A human operator follows the robot, using the marked positions to drill immediately. This iterative process ensures that both robots and workers operate safely in close quarters.
The application in aerospace manufacturing necessitates cameras that are compact, with minimal working distances to maintain accuracy while limiting robotic movements. The Ensenso N36 matches these requirements, designed specifically for challenging environments. Its small footprint allows for efficient installation, whether fixed or on a robotic arm.
Actual Assembly Operation
By providing 3D imagery of moving and stationary objects, the integrated projector within the camera ensures high-contrast textures in difficult lighting. Through a pattern mask projecting random dots, it enhances deficient features. Pre-calibrated at the factory, these cameras can be quickly operational.
This digital progression affords the DLR more streamlined processes. Leveraging camera-based alignment significantly enhances precision and repeatability, while continuous data recording ensures comprehensive process documentation and traceability. It also eases workload on personnel, allowing them to prioritize assembly tasks while robots handle tedious alignment duties, thus reducing production times by eliminating manual measurement needs.
Actual Point Clouds
The mock-up demonstration highlights the promise of merging digital process chains, robotics, and 3D imaging. Future project phases will scrutinize the system's accuracy and refine evaluation algorithms, involving both camera technology and mathematical methodologies for point cloud alignment.
What is currently being explored in aircraft manufacturing holds potential for cross-industry applications, exemplifying the transformative role of optical sensors and intelligent software in ushering in improved, networked, and efficient manufacturing processes.
An Ensenso 3D camera integrated into an automated process chain ensures accurate detection and alignment of drilling positions in aircraft cabin assembly.
In modern aircraft production, precision is everything. Every hole and every fixing point must be precisely positioned to ensure safety and quality. As part of the DiCADeMA project (Digital Cabin Architectures and Design for Manufacturing) led by the German Aerospace Centre (DLR), a novel, fully digitally networked process has been developed. Through intelligent automation, this approach elevates aircraft cabin manufacturing to a new level. A key component in this process is an Ensenso 3D camera from IDS Imaging Development Systems GmbH, which ensures highly precise detection and alignment of drilling positions.
Marking drilling positions
The aim of the project is to establish a continuous digital thread from design to production. Changes to the cabin design, such as seat spacing and the associated new position of the luggage compartments, are recorded directly in the digital design data and automatically transferred to production planning. Simulations allow these variants to be validated before any physical component is manufactured. Once digital validation is complete, production can begin immediately.
To make this digital process tangible, an automated system for marking drilling positions was developed on a mock-up of an aircraft frame structure. Several networked systems work together in this setup: An autonomous mobile robot (AMR) approaches the frame and positions itself near the target area. Mounted on the AMR is a lightweight robot that moves the marking unit, including the 3D camera, into the acquisition position. At this point, the Ensenso camera takes over the fine alignment. An integrated Manufacturing Execution System (MES) controls all sub-processes.
Precise correction values
The camera used, an Ensenso N36, captures the environment as a three-dimensional point cloud and matches it against the CAD data of the aircraft frame. In this way, even the smallest deviations between the target model and the actual geometry can be detected. The system uses this data to calculate precise correction values, which are transmitted to the higher-level MES.
Communication takes place via a standardized OPC UA interface, ensuring reliable and secure data exchange between the camera, the robot and the control system. The MES translates the acquired data into concrete control commands for the robot, which then performs the marking of the drilling position. The autonomous robot achieves a positioning accuracy of around five millimeters. This allows the camera to reach the acquisition position without risk of collision.
Iterative minimisation process
The Ensenso camera becomes a key link between digital design and real-world manufacturing: It recognises local geometries, in this case several rivets and the surface on which they are set and compares the captured point clouds with reference data from the CAD.
This comparison is made possible, among other things, by hand–eye calibration and an iterative minimisation process. The result is a transformation matrix that precisely describes the correction required for the drilling position. By applying this correction value, the drilling position can be set precisely.
Demanding environmental conditions
An operator follows the vehicle and drills the hole immediately afterwards at the marked spot. This process is repeated for each installation point, while robots and humans can work safely in close proximity to one another.
For this application in aircraft manufacturing, a compact camera with a very short working distance is required in order to keep the path from the acquisition position to the drilling position as short as possible. This helps to maintain high accuracy and avoids excessive robot movements. The Ensenso N36 meets these requirements. The Ensenso N series has been specially developed for use in demanding environmental conditions. Thanks to its compact design, the camera can be installed in a space-saving manner, either in a fixed position or mounted on a robot arm.
Actual assembly operation
This makes it equally suitable for 3D capture of both moving and stationary objects. The integrated projector ensures high-contrast texture even under challenging lighting conditions: It projects additional structures onto the object surface using a pattern mask with a random dot pattern, thereby supplementing missing or weak features. All cameras are pre-calibrated at the factory and can therefore be put into operation quickly and easily.
The digital process offers the DLR several advantages. Camera-based alignment significantly increases precision and repeatability. At the same time, continuous data acquisition enables complete documentation and traceability of all process steps. Assembly personnel are relieved, as the robot takes over the time-consuming task of position determination, allowing skilled workers to focus on the actual assembly operation. In addition, production times are significantly reduced, as manual measurements or readjustments are no longer necessary.
Actual point clouds
The demonstration on the mock-up clearly illustrates the potential that lies in combining the digital process chain, robotics and 3D image processing. In further project steps, the accuracy of the system and the performance of the evaluation algorithms will be examined in greater detail. This will involve not only the camera itself, but also the optimization of the mathematical methods used to align nominal and actual point clouds.
What is currently being tested in aircraft manufacturing may also be applied in other industries in the future. The system impressively demonstrates how optical sensor technology and intelligent Software are paving the way for a new era in manufacturing: networked, efficient and precisely on target.
