Conference PaperPDF Available

Technology Innovations for Faster Aircraft Cabin Conversion


Abstract and Figures

During the life cycle of commercial aircraft, passenger cabins are converted multiple times. The planning database for these conversions often lack consistent, up-to-date geometry data which eventually leads to assembly problems and an extension of the aircraft ground time. In this paper, concepts for the use of innovative technologies like Augmented Reality (AR) and mobile 3D scanning are presented in order to quickly recognize potential assembly problems and to increase the completeness and accuracy of the planning database for cabin conversion.
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AST 2019, February 1920, Hamburg, Germany
Constantin Deneke1, Jan Oltmann2, Thorsten Schüppstuhl1, Dieter Krause2
1Insitute for Aircraft Production Technology, Hamburg University of Technology
Denickestraße 17, 21073 Hamburg, Germany
2Insitute for Product Development and Mechanical Engineering,
Hamburg University of Technology
Denickestraße 17, 21073 Hamburg, Germany
During the life cycle of commercial aircraft, passenger cabins are converted multiple times.
The planning database for these conversions often lack consistent, up-to-date geometry data
which eventually leads to assembly problems and an extension of the aircraft ground time. In
this paper, concepts for the use of innovative technologies like Augmented Reality (AR) and
mobile 3D scanning are presented in order to quickly recognize potential assembly problems
and to increase the completeness and accuracy of the planning database for cabin conversion.
Commercial passenger air traffic has been increasing for decades and the biggest
aircraft manufacturers, Airbus and Boeing, forecast a further doubling in the next 15
and 20 years respectively ([1], [2]). The passenger cabin plays a major role for
passenger comfort and safety. Passenger cabins are converted multiple times during the
airplane’s life span which can exceed 25 years in order to maintain high levels of
comfort and safety. In [3] a demand of more than 33.000 cabin conversions for
commercial airplanes is forecasted between 2010 and 2029. To meet these high
demands of cabin conversions and to resist the growing competition in this field of
industry, an efficient cabin conversion process is required at the out-carrying
companies like OEMs or MROs.
The cabin conversion process can be separated into two main phases as shown in
Figure 1, the planning and design (PD) and the modification and installation (MI). In
the PD-phase prior to the actual conversion on site the process consists of different
steps. First, the preconditions for the design phase are set. This includes the inspection
of an aircraft and gathering of required geometrical and other information. This is
usually done by investigating all relevant documents which include documents from
the airplane manufacturer and previous maintenance and modification documents.
Constantin Deneke, Jan Oltmann, Thorsten Schüppstuhl, Dieter Krause
After that the designing of the cabin layout as well as the verification of the assembly
with respect to design clashes can be done. In case of design clashes feasible solutions
are proposed [3].
Figure 1 current process of cabin conversion
Based on the analyses at a MRO company that performs the whole cabin conversion
process hindrances of an efficient conversion process are derived. There are 3 main
aspects that lead to an insufficient planning database.
The airplane has undergone numerous maintenance and modification programs,
the documentation for which is only paper-based.
The airplane might not be designed with modern 3D CAD systems, and in case
3D CAD data is existent, it is proprietary to the aircraft manufacturers and not
accessible to the MRO company.
The airplane might have had several owners, operators and MROs, with
inconsistent data management.
These circumstances lead to the information about the current cabin state, which
engineers gather from various documents for design planning, being partially
incomplete, not fully up-to-date, or even contradictory. To compensate for this lack of
consistent, up-to-date information, design engineers use the few opportunities they
have to gather more information about the current state of the airplane’s cabin during
ground times in so-called surveys or physical fit checks (see Figure 1). This might be
during maintenance programs or overnight stops of the airplane. However, these
opportunities are very time limited and it is rarely possible to get all required
information from the current cabin. As a consequence, the design planning of a cabin
conversion can only be based on the available information which is still not complete
and fully up-to-date. This leads to the occurrence of assembly problems during the
conversion time.
Figure 2: Example of occurring clashes during a cabin component installation
For example design clashes between cabin components and cabin structure elements,
like brackets, regularly obstruct the installation of cabin components. Assembly
AST 2019, February 1920, Hamburg, Germany
problems like the one shown in Figure 2 lead to the need of an additional modification
process and thus an extension of the aircraft ground time and a significant increase of
costs. In the next section we describe two technologies which can assist with finding
planning errors at an earlier stage and which are capable of acquiring up-to-date cabin
geometry data to reduce and avoid the occurrence of assembly problems.
One technology which is capable to recognize as-build and as-designed deviations -
and thus eligible for the detection of planning errors - is Augmented Reality.
Augmented Reality system supplements the real world with virtual objects that appear
to coexist in the same space as the real world [4]. Proposed AR applications in the
aircraft industry have been around for decades. [5] describes an AR demonstration
system by Boeing for assembly tasks such as wire installation. With the growing
available computational power, AR is being used more and more in industry on a daily
basis. A current example for the application in the aircraft industry is the Smart
Augmented Reality Tool developed by the Airbus company Testia [6]. AR has also
been proposed to support planning tasks for other industrial applications ([7], [8]). The
key technology of any mobile AR application is the pose tracking of the AR device, so
virtual and real components can be correctly registered with each other to give the user
a realistic and immersive visualization. Mobile Augmented Reality devices usually use
visual tracking methods which can be distinguished between marker-based and
markerless methods. Marker-based methods extract a predefined, distinguishable
marker in the surrounding to determine the device’s position relative to the marker.
Markerless methods, however, extract natural features in the camera image to track the
device’s position. This means this method has a much higher computational
complexity, with its accuracy and robustness being highly dependent on the
surroundings [9].
A common technology for the acquisition of comprehensive geometry data is 3D
scanning. Among the key technologies in 3D scanning devices is the method of how
3D depth data is acquired. Most laser scanners use geometric triangulation [10]. Other
methods include time-of-flight measurement, structured light projection and
photogrammetry. Mobile 3D scanning devices use pose tracking methods for the
registration of single scans to each other to be able to fully digitalize an object’s
geometry. Similar to AR pose tracking, the pose tracking of mobile 3D scanner can be
either marker-based or markerless. In an additional post-processing step, algorithms
like the ICP (Iterative Closest Point), whose purpose it is to register two coarsely
aligned point clouds [11], might be used for increasing the accuracy of the registration.
The accuracy and precision of the 3D data of an object depends on the used 3D
sensor technology as well as on the accuracy of the registration. Effects on the
accuracy, the precision, but also whether a depth measurement of a 3D scan can be
successfully taken in the first place, are also dependent on the object and its
surroundings. For example dispersion of the emitted light and the reflectivity or
absorption properties of the object are influencing variables for the quality of the 3D
scan [12]. To improve the aircraft conversion, concepts and processes for the
Constantin Deneke, Jan Oltmann, Thorsten Schüppstuhl, Dieter Krause
integration of AR and 3D scanning technologies are presented in the next section.
3.1 AR digitalisation system
In order to integrate smart tools such as Augmented Reality and 3D scanning devices
into the cabin conversion process, there are specific requirements that the devices and
technologies have to meet. Especially the opportunities to gather additional information
of the actual cabin structure prior to ground time face strong limitations. These
opportunities are not bound to a certain airport or hangar location but can occur at
airports or maintenance sites worldwide. Furthermore, these opportunities face strong
time restrictions, because the aircraft might only be accessible for a few hours.
Therefore, the smart tool must have high mobility and since there might not be
enough time to transport it from one global location to another high availability. From
this requirement it can be further derived that the smart tool must be low cost. The tool
must have the capability to gather as much relevant information as possible within a
short period of time. This also means that an efficient process for the acquisition of the
information is required. Furthermore, the application of the tool cannot be limited to
specialists who are trained to use the device, as they might not be available when the
aircraft is accessible. Thus, the application of the tool must be user-friendly, intuitive
and needs efficient user guidance.
To meet these requirements, we propose the use of an Augmented Reality system.
Augmented Reality in general has the capability to fulfill the mentioned requirements,
e.g. regarding mobility, costs, and speed. There are two limitations though, which
restrict the use of Augmented Reality. The first one is that the acquisition of
geometrical information from the surroundings is very restricted with common AR
devices like tablets. These devices are not able to acquire complete 3D data with an
acceptable accuracy. To overcome this limitation, we propose to enhance Augmented
Reality technology with 3D scanning technology. With this, the geometry of the aircraft
cabin structure can be acquired. This geometry data can be enriched with information
by AR user interaction on-site and then used later for the planning of the cabin
3.2 Local high resolution refinement
The second limitation of the use of Augmented Reality is its accuracy which mainly
depends on the pose tracking of the device. As a result, with current AR technology it
is not possible to gather geometrical information with millimeter accuracy which is
desired for product design. Thus, our concept proposes to use Augmented Reality to
determine planning errors and acquire additional information within the AR accuracy.
For cases where AR does not show unambiguous results, for example a cabin element
may or may not clash with a structure element, we propose to perform local 3D scans
with a high-resolution sensor at the beginning of the modification and installation
phase. Since there are only a few locations where the modification and installation
phase can take place it would be possible to have a high-resolution 3D scanner available
at those locations for employees who are trained to use it. Performing local scans in
AST 2019, February 1920, Hamburg, Germany
limited, by the AR system pre-defined locations, is an option to acquire highly accurate
geometrical information in the beginning of the modification and installation phase.
The more precise scanned point clouds can be used either to check possible
clashes of the cabin layout, planned with respect to the ideal, or to update more details
to the planning model. However, in current CAD software there are only a few
functions that allow to work with data point clouds and carry out design clash analyses.
Therefore, software support is being developed to help engineers to find design clashes
of point clouds and CAD models. Moreover additional functions to quickly adjust
current CAD parts or to update the planning model shall be implemented.
In this section we evaluate the accuracy of devices which could be integrated in our
concept show the current implementation of the two technology approaches.
4.1 Accuracy evaluation in aircraft cabin mock-up
Specifications about accuracies and precision of addressed technologies as they are
stated in data sheets have been determined with standardized methods under
standardized environmental conditions. But the usability and accuracy of addressed
technologies are as described in chapter 2 highly dependent on the application
environment. Therefore, tests were performed in an aircraft cabin mock-up to
determine their capabilities for the addressed application. We considered the accuracy
of 3D scans recorded by these devices as an indication of whether the devices were
usable for the addressed application. 3D-scans can only be accurately taken if the depth
sensor can handle the surface of objects and if the pose tracking works sufficiently in
the environment, in our case an aircraft cabin mock-up.
Cabin mock-up - Figure 3 shows the cabin mock-up and the positions of the reference
points as white dots. The mock-up consists of an aircraft panel with the original frame
and stringer layout. The aircraft floor was rebuilt with true aircraft dimensions and seat
track positions. The dimensions of the whole mock-up are about 4.3 x 2.1 x 3.3 m.
Figure 3 used positions of reference points in the cabin mock-up
Reference Data - As reference for the evaluation, the position of 28 reference points
are measured with a laser tracker (model: Leica LTD 800) with a submillimeter
accuracy. From each scan the reference points are extracted and distances between all
points are calculated. These distances are compared to the true distances of the
Constantin Deneke, Jan Oltmann, Thorsten Schüppstuhl, Dieter Krause
reference points.
3D scanning devices - Figure 4 shows the devices used for accuracy evaluation. The
selection of scanners represents the state of the art of 3D Scanners to a good extend for
large scanning volumes from low to high cost scanning sensors. A high precision
terrestrial scanner, the Faro Focus 3D X130, is used to compare mobile and stationary
measurements. Two different commercially available high precision mobile 3D
scanners as well as a low cost AR system, the Lenovo Phab 2, were chosen to compare
different measuring methods but also different device classes. The Handyscan 3D 700
uses marker-based pose tracking, while the others work markerless. The Artec EVA on
the other side is not fully mobile itself, because it requires a laptop connection during
operation. The Lenovo Phab 2 is a commercially available mobile on Android basis
which uses a built-in time of flight camera for 3D scanning.
Figure 4 - 3D scanning devices used for analysis
3D 700
Phab 2
(res. 10 mm)
Faro Focus
3D X130
No. of reference points
Average deviation [mm]
Standard deviation [mm]
Min. deviation [mm]
Max. deviation [mm]
Scan boundary dimensions
L: 4310
H: 2160
D: 530
L: 4310
H: 2160
D: 3340
L: 4310
H: 2160
D: 3340
Table 1 Measurement results of accuracy evaluation from performed tests in cabin mock-up
Results The results are depicted in Table 1. The Creaform Handyscan sensor achieves
in the performed tests the best accuracy having an average deviation of 2.94 mm. One
reason for this is that it uses a marker-based tracking system in order to align single
scans accurately to each other. The results of the Artec Eva scanner and the terrestrial
Faro scanner are in a similar order of magnitude around 4 mm in average. However, it
has to be stated that the Artec Eva Scanner originally was not designed for such large
volume scans, but nevertheless gives good results. With Lenovo Phab2 two scans were
recorded, one with a 10 mm resolution which covers the entire cabin mock-up and one
with the 5 mm resolution which covers only a section of it due to limited
computational power. Both scans show as expected a lower accuracy than the high-
AST 2019, February 1920, Hamburg, Germany
end scanning devices. While the smaller scan with the higher resolution - with an
average accuracy of 5.9 mm - delivers comparable results to the high-end devices, the
full mock-up scan has a lower accuracy of 12.6 mm in average. The reason for this is
a combination of a less accurate position tracking system, whose accuracy might
decrease over moved distance, and a less accurate 3D sensor compared to the high end
It must be concluded that no device delivers an absolute high precision result.
But all scanning devices deliver results that can support cabin conversion planning
dependent on the scenario in which the devices are used. Even the Lenovo Phab 2
results are fairly good and can be sufficient for the intended AR-concept. Furthermore,
it has to be pointed out that presented results are only valid for the described scenario
and test conditions. They do not allow to derivate statements about general device
4.2 AR digitalisation system
Crucial for any mobile Augmented Reality system is its localization in the environment,
which can be divided into position initialization and tracking. The localization in the
addressed application needs to be set up in a short amount of time due to the restrictions
in the PD-phase. Marker-based approaches require the installation of markers which
can be time-consuming, especially in large environments like aircraft cabins. For the
position initialization the use of a reference model is proposed which is put in place by
user interaction. With this, the device’s coordinate system can be transformed to the
aircraft coordinate system, and is consistent with aircraft and CAD models used for
planning. The position tracking can be performed by markerless visual tracking
methods as indicated to be working robustly in chapter 3. Among the functionalities of
the proposed AR system is the viewing and positioning of virtual models like the cabin
components. With these, the user can recognize potential design clashes or divergences
between expected and real conditions on-site. For proper documentation for later
planning adaption several additional functions are proposed. These include 3D
scanning to acquire the local 3D geometry of the cabin structure and its enrichment
with virtual information by user-interaction. This enrichment includes the ability
to overlay scan data with virtual objects, for example where scan data is of low
quality due to object’s surface properties,
to input localized user annotations, for example for the assignment of part
numbers to objects and
to take localized pictures to give the design engineers a visual reference of a
certain object or region.
An AR system with these functionalities is currently under development. For the first
implementation a Lenovo Phab 2 phablet device is used. Figure 5 shows the application
demonstrating an example task. Shown is the cabin mock-up with augmented virtual
models of brackets (in blue color) which in this case demonstrate all expected positions
of brackets. The user can see if brackets are in the environment which were not
expected or if expected positions of certain brackets differ from the reality. In these
cases the user can provide information about missing or wrongly positioned brackets.
Furthermore, 3D scans can be recorded to generate comprehensive information about
Constantin Deneke, Jan Oltmann, Thorsten Schüppstuhl, Dieter Krause
the real geometry of the area.
Figure 5 AR demonstration example
4.3 Local high resolution refinement
In case local high resolution scanning is required the commercially available terrestrial
or mobile scanning devices can be used. This data can be taken to analyze possible
clash scenarios on the cabin design with respect to the cabin layout.
However, the use of data point clouds in CAD environment is still a problem,
since there are no possibilities to compare data point clouds and CAD data. There is
the opportunity to use mesh data, but there will be a similar problem because the
scanned mesh data is not enclosed and cannot be properly analysed in a CAD system.
For this reason, a software tool in C# for the commercial software SolidWorks via its
API is developed to enhance the use of measurement data in a CAD environment. In
the future the software tool, amongst others, shall allow to
detect design clashes between CAD planning data and measured point clouds
or mesh data, and characterize them for redesign in the CAD system
facilitate a design space analysis based on measured data,
allow fitting and mapping of CAD geometry to scanned data to update planning
data (e.g. new placement of brackets)
output statistical uncertainties for localization with respect to measured data
The design clash analysis is implemented as interference detection of a point within a
CAD part using the ray-casting algorithm. For that infinite rays are taken starting from
every measurement point to a random direction. The number of intersections with the
surfaces of a CAD part determines whether the point is or is not within the part. An odd
number says the point is within the part and vice versa.
In the current state of implementation, the first two aspects have already been
addressed. The focus was then set on the data processing of large point clouds on a
common desktop working station with respect to usability and performance for
usability concerns. This includes, above all, a pre-import data structuring via octree
method [13], a manual selection of the design space of interest, and the consideration
of bounding boxes for every CAD during the analysis part. These aspects fasten the
analysis of the point cloud to less than 10 % of the time without. Using a point cloud
with more than 5 million points and a defined interference with a CAD part as shown
AST 2019, February 1920, Hamburg, Germany
in Figure 6 leads to an analysis duration of 30-40 min.
Figure 6 Implementation of clash analysis tool in SolidWorks (top) and interference
detection process from aircraft mock-up of aircraft panel and OHSC (bottom)
One difficulty working with point clouds in SolidWorks is a performance reduction of
the SolidWorks environment since API requests are slow. For that reason, it is
necessary to use two different point clouds, a reduced one for the visualization and the
full point cloud for the clash analysis. An example is shown in Figure 6 (bottom). The
difference between the detailed design clash results imported to SolidWorks and the
reduced visualization of the full panel is highlighted. Finally, the clash detection can
either be used for design changes of current CAD models or to update the planning
database accordingly. Here the automatic mapping of existing CAD parts to
measurement data shall facilitate this task.
To detect possible clashes before the assembly of cabin components, as wells as to
increase the completeness and accuracy of the planning data, innovative technologies
like AR and 3D scanning are introduced as support tools for the planning of cabin
conversions. For the concept first evaluations are carried out within an aircraft mock-
up at TUHH. The use of combined AR and 3D scanning as presented is a very
promising technology for mobile virtual fit checks and for gathering more information
about the current state of the aircraft cabin. The benefit of the introduced system is its
mobility and thus usability everywhere and by everyone. However, so far, the accuracy
Reduced data
Full data
Visualization of
clashed area
Clash analysis results Detailed analysis Adapt assembly
Constantin Deneke, Jan Oltmann, Thorsten Schüppstuhl, Dieter Krause
of this technology is still limited. But if the accuracy of a scan is not sufficient, a high
precision can be carried out at predefined spots based on the AR application.
Furthermore, the use of the measurement data for quick design changes a plugin for a
CAD software is under development which allows automatic clash detection of
measured and CAD data and facilitate a design space analysis and the model updating
of the planning model. The concept will be further developed and validated in a real
aircraft environment in order to evaluate to what extend and accuracy clashes or design
deviations from the planning base can be detected and updated.
This work belongs to the research project “Cabin 4.0” in cooperation with Lufthansa
Technik and is supported by the Federal Ministry for Economic Affairs and Energy as
part of the Federal Aeronautical Research Programme “LuFo V-2”.
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... Therefore we propose to include modern technologies, in particular Augmented Reality (AR) and 3D scanning technologies. In our previous paper we described the overall concept and estimated accuracies of proposed AR technologies, based on recorded 3D scans, and 3D scanning technologies [4]. This present paper focuses on how information can be gathered with an AR system and how this information can be made accessible to and used by planning engineers. ...
... This present paper focuses on how information can be gathered with an AR system and how this information can be made accessible to and used by planning engineers. Figure 1: Example of a clash caused by insufficient planning data [4] 2 LITERATURE REVIEW Azuma et al.'s widely accepted definition of Augmented Reality states that an AR system combines real and virtual objects in a real environment, runs interactively and in real time, and registers real and virtual objects with each other [5]. ...
... Besides these, further data exists, for example documents in PDF format. There may also be additional 3D models in existence, such as, for example cabin elements, or there may be previously performed 3D scans in existence -of, for example, our proposed complementary high-resolution digitalization approach [4]. These can further support the planning process. ...
... During the cabin retrofit, for leased aircraft for example occurring approximately every five to seven years, big parts of the aircraft's cabin are removed and replaced by a partly or completely newly designed interior [1][2][3]. As this new cabin has to fit into the specific aircraft's body-its airframe-perfectly, planning the cabin as well as the retrofit process heavily relies on exact knowledge about the specific airframe [4]. While this scenario calls for an approach that currently can be frequently found in the literature under the term digital twin, aviation's special circumstances complicate the adaptation of said concepts and result in the need for an even more elaborate data handling effort. ...
... This usually leads to extended time on the ground as conflicts are identified only during the attempt to install the new cabin, leading to impromptu required modifications and adaptations of the design or mounting. However, as each day spent on the ground to perform the retrofit is cost-intensive, the retrofit requires a sufficient planning basis as a foundation, ideally long before the aircraft arrives at the retrofit facility [4]. ...
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... Knowing exact geometric information, or at least what exact components are installed at which position would reduce these conflicts, streamline the complete retrofit-process as well as reduce costs and missed revenues resulting from the longer time spent on the ground and not operating. [3] Besides these financial benefits for the aircraft's operator, a digitally available up-to-date representation of specific aircraft would ease the overall retrofit planning process, as it would provide the engineer more easily with more accurate ...
... Therefore, to keep the actual ground time during a modification short, a sufficient planning basis is required as the foundation of a cabin modification [12]. Consequently, DOs request as much information as possible from the Continuing Airworthiness Management Organisation (CAMO) and the aircraft's holder to be able to reliably layout and prepare the retrofit. ...
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... hatracks, passenger service units and lining panels outside the fuselage to reduce lead-time and working hours. Other concepts focus on a modular, assembly-friendly design of interior components or the application of augmented reality tools for faster cabin conversions [7,11,13]. Fette et al. [10] introduced a concept of robot-supported assembly of an overhead storage compartment. The abovementioned publications address the assembly either of complete monuments at the OEMs production line during line fit or the assembly of monuments from single panels and do not contribute to an increased productivity during the assembly of the subassemblies themselves. ...
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Product life cycles change, market developments and quantities are increasingly difficult to predict, as is the case in the production of charging stations. For these reasons, scalable assembly concepts with an adaptable degree of automation are becoming increasingly important. Currently, charging stations are still manufactured manually. With increasing quantities, however, manual production is no longer economical. New technologies such as lightweight robotics offer a great potential for making production more flexible in terms of quantity. At the same time, new challenges arise because these requirements must be taken into account from the very beginning of product development and process planning. Currently, there are no planning approaches and recommendations for action that take this into consideration. Therefore, the research project “Simultaneous product and process development of a charging station outlet module suitable for automation” (SUPPLy) develops an integrated, digital and simultaneous product and process development of a modular charging station suitable for automation. The aim of the project is to develop an assembly process which enables an economic production of charging stations in case of fluctuating sales figures. The focus is not only on changes in the production process but also on a product design that is suitable for automation. The paper presents the ideas on a conceptual level.
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The assembly of products is often supported by jigs. Especially for large dimensional products, jigs and fixtures are used to align the components and ensure the stability of the assembly until all parts are firmly mounted. This paper describes the development of mobile, modular and adaptive assembly jigs, which are designed to support ergonomic working in the production of high-lift systems for civil aircrafts. The jig supports the workers to adapt the position and orientation of the product to the current assembly operation. The fundamentals of the development are explained and the features of a concept, called assembly wheel, are presented. The assembly wheel consists of two or more robot arms on a circular seventh axis. The robot arms hold and position the components to be assembled so that all joining spots are freely accessible to the worker. The ergonomic benefits of the concept were examined in a study using a 3D model of the jig. A demonstrator on a scale of 1:2 was set up, with which real experiments with an adaptive jig can be conducted for evaluation.
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In Line-less Mobile Assembly Systems (LMAS) the mobilization of assembly resources and products enables rapid physical system reconfigurations to increase flexibility and adaptability. The clean-floor approach discards fixed anchor points, so that assembly resources such as mobile robots and automated guided vehicles transporting products can adapt to new product requirements and form new assembly processes without specific layout restrictions. An associated challenge is spatial referencing between mobile resources and product tolerances. Due to the missing fixed points, there is a need for more positioning data to locate and navigate assembly resources. Distributed large-scale metrology systems offer the capability to cover a wide shop floor area and obtain positioning data from several resources simultaneously with uncertainties in the submillimeter range. The positioning of transmitter units of these systems becomes a demanding task taking visibility during dynamic processes and configuration-dependent measurement uncertainty into account. This paper presents a novel approach to optimize the position configuration of distributed large-scale metrology systems by minimizing the measurement uncertainty for dynamic assembly processes. For this purpose, a particle-swarm-optimization algorithm has been implemented. The results show that the algorithm is capable of determining suitable transmitter positions by finding global optima in the assembly station search space verified by applying brute-force method in simulation.
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To generate suitable grasping positions between tessellated handling objects and specific planar grippers, we propose a 2D analytical approach which uses a polygon clipping algorithm to generate detailed information about the intersection between both objects. With the generated knowledge about the intersection we check whether its shape fits to the set criteria of the operator and represents a valid grasping position. Before the polygon clipping algorithm is applied, a preprocessing step is performed, where appropriate surfaces from the handling object and the gripper are extracted. After rotating all surfaces into a common plane, potential clipping positions are detected and the clipping is performed to get an accurate intersection detection. The validation shows comparable running times to a OBBTree algorithm (0.1 ms per grasping position) while increasing the stability of the results from 30 to 100% for the evaluated test objects.
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An effective three-dimensional (3D) data representation is required to assess the spatial distribution of the photovoltaic potential over urban building roofs and facades using 3D city models. Voxels have long been used as a spatial data representation, but practical applications of the voxel representation have been limited compared with rasters in traditional two-dimensional (2D) geographic information systems (GIS).We propose to use sparse voxel octree (SVO) as a data representation to extend the GRASS GIS r.sun solar radiation model from 2D to 3D. The GRASS GIS r.sun model is nested in an SVO-based computing framework. The presented 3D solar radiation computing framework was applied to 3D building groups of different geometric complexities to demonstrate its efficiency and scalability. We presented a method to explicitly compute diffuse shading losses in r.sun, and found that diffuse shading losses can reduce up to 10% of the annual global radiation under clear sky conditions. Hence, diffuse shading losses are of significant importance especially in complex urban environments.
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Automatic 3D point cloud registration is a main issue in computer vision and remote sensing. One of the most commonly adopted solution is the well-known Iterative Closest Point (ICP) algorithm. This standard approach performs a fine registration of two overlapping point clouds by iteratively estimating the transformation parameters, assuming good a priori alignment is provided. A large body of literature has proposed many variations in order to improve each step of the process (namely selecting, matching, rejecting, weighting and minimizing). The aim of this paper is to demonstrate how the knowledge of the shape that best fits the local geometry of each 3D point neighborhood can improve the speed and the accuracy of each of these steps. First we present the geometrical features that form the basis of this work. These low-level attributes indeed describe the neighborhood shape around each 3D point. They allow to retrieve the optimal size to analyze the neighborhoods at various scales as well as the privileged local dimension (linear, planar, or volumetric). Several variations of each step of the ICP process are then proposed and analyzed by introducing these features. Such variants are compared on real datasets with the original algorithm in order to retrieve the most efficient algorithm for the whole process. Therefore, the method is successfully applied to various 3D lidar point clouds from airborne, terrestrial, and mobile mapping systems. Improvement for two ICP steps has been noted, and we conclude that our features may not be relevant for very dissimilar object samplings.
Conference Paper
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The authors describe the design and prototyping steps they have taken toward the implementation of a heads-up, see-through, head-mounted display (HUDset). Combined with head position sensing and a real world registration system, this technology allows a computer-produced diagram to be superimposed and stabilized on a specific position on a real-world object. Successful development of the HUDset technology will enable cost reductions and efficiency improvements in many of the human-involved operations in aircraft manufacturing, by eliminating templates, formboard diagrams, and other masking devices
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In 1997, Azuma published a survey on augmented reality (AR). Our goal is to complement, rather than replace, the original survey by presenting representative examples of the new advances. We refer one to the original survey for descriptions of potential applications (such as medical visualization, maintenance and repair of complex equipment, annotation, and path planning); summaries of AR system characteristics (such as the advantages and disadvantages of optical and video approaches to blending virtual and real, problems in display focus and contrast, and system portability); and an introduction to the crucial problem of registration, including sources of registration error and error-reduction strategies
Reverse engineering is the process of discovering the technological principles of an object or component through analysis of its structure and function. Such analysis can then be used to redesign the object very quickly using computer-aided design in concert with rapid-manufacturing processes to produce small numbers of components adapted to the needs of a particular customer. This way of working has huge benefits of speed and flexibility over traditional mass-production-based design and manufacturing processes. This edited collection of essays from world-leading academic and industrial authors yields insight into all aspects of reverse engineering: • The methods of reverse engineering analysis are covered, with special emphasis on the investigation of surface and internal structures. • Frequently-used hardware and software are assessed and advice given on the most suitable choice of system. • Rapid prototyping is introduced and its relationship with successful reverse engineering is discussed. • Importantly, legal matters surrounding reverse engineering are addressed as are other barriers to the adoption of these techniques. • Applications of reverse engineering in three significant areas: automotive; aerospace; and medical engineering are reported in depth. Reverse Engineering is a "must have" title for anyone working with advanced modern manufacturing technologies, either with a view to researching and improving them further or to making their company leaner and more agile in a competitive manufacturing marketplace. The Springer Series in Advanced Manufacturing publishes the best teaching and reference material to support students, educators and practitioners in manufacturing technology and management. This international series includes advanced textbooks, research monographs, edited works and conference proceedings covering all subjects in advanced manufacturing. The series focuses on new topics of interest, new treatments of more traditional areas and coverage of the applications of information and communication technology in manufacturing.
Die heutige Fabrikplanung basiert stark auf den Werkzeugen der Digitalen Fabrik, um den immer kürzeren Produktlebenszyklen und den dadurch nötigen Strukturänderungen gerecht zu werden. Jedoch sind die digitale und die reale Fabrik zumeist nicht konsistent auf Grund von fehlenden oder unvollständigen digitalen Daten. Die Erweiterte Realität kann hier eine intuitive Schnittstelle bieten. Diese Technologie verbindet reale und virtuelle Informationen und ermöglicht dadurch die lagegerechte Einbindung von digitalen Planungsdaten in Ansichten der realen Produktion. Diese Arbeit beschreibt den Weg hin zu einer produktiven Anwendung von Erweiterter Realität für Fabrikplanung. Als kritische Faktoren für den Erfolg werden dabei Genauigkeit und Prozessunterstützung für die Registrierung zwischen echter und digitaler Welt behandelt. Das entwickelte System wurde bereits erfolgreich für zahlreiche industrielle Planungsprobleme angewandt.
Global Networks, Global Citizens: Global Market Forecast
  • Airbus
Airbus, "Global Networks, Global Citizens: Global Market Forecast 2018-2037", (2018).
Contributions to aircraft preliminary design and optimization
  • M F Niţǎ
M. F. Niţǎ, Contributions to aircraft preliminary design and optimization, Dr. Hut, München (2013).
Augmented Reality for the factory of the future
  • A C Bonard
A. C. Franck Bonard, "Augmented Reality for the factory of the future", (2016).