Figure 2-19 - uploaded by Zaoxu Zhu
Content may be subject to copyright.
Source publication
![Figure 2-2: Circuit breakers connected by wires [20]](profile/Zaoxu-Zhu/publication/318562371/figure/fig3/AS:631672680755222@1527613911698/2-Circuit-breakers-connected-by-wires-20_Q320.jpg)
![Figure 2-3: An anti-chafing grommet on the edge of a lightening hole [21]](profile/Zaoxu-Zhu/publication/318562371/figure/fig4/AS:631672680742961@1527613911818/3-An-anti-chafing-grommet-on-the-edge-of-a-lightening-hole-21_Q320.jpg)
Harness 3D routing is one of the most challenging steps in the design of aircraft Electrical Wiring Interconnection System (EWIS), due to the intrinsic complexity of the EWIS, the increasing number of applying design constraints, and its dependency on the design changes of the airframe and installed systems. The current routing process employed by...
Citations
... Fundamental work in [20,21] was expanded in [22] to develop a virtual environment for the 3-D wire harness design problem. An automatic clamp placement and hybrid multi-objective optimization in combination with harness routing is presented in [23]. ...
The implementation of a fully instrumented, automated and simulation-enabled engineering software platform capable of automating the currently still manual model-based systems engineering (MBSE) design process for physical systems architecture generation and optimization in an aircraft wing is presented. The software platform uses graph-based design languages to integrate and entirely automate the mainly manual packing, piping and harness routing design. This design automation and optimization is achieved by a novel software stack of an optimization software coupled with a design compiler. It is shown that through rule-based model generation by a design compiler in the form of a design graph as a central data model, a cross-domain data consistency is achieved. This allows for automated execution and coupling of engineering tasks over several different domains such as packing, piping and routing design to converge to an optimized wing physical architecture design variant in agreement with given predetermined design constraints.
... A two-steps optimization method was proposed in our previous work to enable automation of the harness routing design. 8,9 In the first step, a 3 D discretization of the airframe surfaces where the EWIS is allowed to be fixed is generated and no-go areas (i.e., where systems are installed) are identified. Then, a simplified harness is routed through the nodes of the discretized surfaces representation. ...
... 10 In industry, EWIS designers already take actions to handle the over-detailed DMUs. Nevertheless, the results are not satisfactory in view of applying the automatic routing solutions proposed in Ref. (8). Existing Feature Recognition and Suppression Methods (FRSM), which recognize and suppress features from neutral CAD formats and then suppress some of them, could provide a potential solution (see the next section). ...
Routing design of aircraft Electrical Wiring Interconnection System (EWIS) is time-consuming and error-prone. A solution, which automatically routes the EWIS inside the aircraft Digital MockUp (DMU), has been proposed and presented in the previous publications. The DMU, however, includes over-detailed features, which hardly influence the routing results but significantly increase the geometry-involved computational time thus hampering any automated routing. These features cannot be easily and efficiently suppressed. Therefore, a quick 3 D geometry simplification method, named Alpha-SIM, is proposed to enable a quick simplification of the airframe components included in the DMU and improve the benefit of the aforementioned automatic EWIS routing approach. The method is inspired by Descriptive Geometry techniques and the 3 D modelling approach using 2 D sketches, and aims at removing very detailed and/or internal features while preserving the intuitive notional shape of the given CAD model. The intuitive notional shape is represented by a 3 D point cloud of the model outer boundary and their 2 D projections on user-defined planes. These 2 D projections are then processed such to generate a set of 2 D profiles, called Alpha-Shapes, which are used, eventually, to re-build the 3 D model of the DMU components in a simplified/de-featured manner. By controlling the density of the 3 D points and the Alpha value to generate the 2 D profiles from the point projections, various geometric approximation levels can be achieved. The results of the test cases demonstrate the efficiency and effectiveness of the proposed method on the geometry simplification for automatic EWIS routing.
Many industries are facing the challenge of increasing the number of cables in their products. All of these cable paths must be planned in a time-consuming, repetitive, and error-prone process. Instead of manually defining all waypoints for a broad range of cables, automation can provide globally optimized and valid paths for accelerated product development. To establish automated electrical routing, an industrial-oriented application is directly integrated into existing 3D CAD workflows. The purpose of this research is to investigate the applicability and performance of Reinforcement Learning in identifying optimal paths in a three-dimensional space. Therefore, information is directly extracted from 3D CAD, and results are immediately returned to CAD. Handing over the crucial task of routing to a Multi-Agent Deep Q-Network (MADQN) promises a scalable solution for various environments of different sizes and levels of complexity. Minimizing the total cable lengths while considering cable and environment-specific constraints is formulated as a shortest-path problem in three-dimensional space in order to make it solvable for the developed approach. To reduce the complexity based on the application domain, the agents’ accessible space is decreased to a maximum distance from the initial 3D CAD geometry. This paper provides a detailed explanation of the developed approach, which is compared to established methods in electrical routing such as the A* algorithm.
