Abstract
The routing design of the various electrical wires, tubes, and hoses of a commercial vehicle requires a significant number of man-hours because of the variety of the commercial vehicles, frequent design changes of other vehicular components and the manual trial-and-error approaches. This study proposes a new graph-based routing algorithm to find the collision-free routing path in the constrained space of a commercial vehicle. Minimal spanning tree is adopted to connect multi-terminal points in a graph and Dijkstra’s algorithm is used to find the shortest route among the candidate paths; the design domain is divided into several sub-domains to simplify the graph and the proposed algorithm solves the routing problems in a sequential manner to deal intermediate points. Then, the proposed method was applied to the design of the routes for four different routing components of a commercial truck. The results indicate that the developed methodology can provide a satisfactory routing design satisfying all the requirements of the design experts in the automotive industry.
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References
Asmara, A. (2013). Pipe routing framework for detailed ship design. Ph.D. Thesis, Delft, The Netherlands: TU Delft.
Chan, A. L. S., Hanby, V. I., & Chow, T. T. (2007). Optimization of distribution piping network in district cooling system using genetic algorithm with local search. Energy Conversion and Management, 48, 2622–2629.
Chikurde, R. C., Kumar, M., & Singh, T. (2013). Optimization and validation of exhaust tailpipe noise for passenger car. In Symposium on international automotive technology, technical paper 2013-26-0101, SIAT, India.
Christodoulou, S. E., & Ellinas, G. (2010). Pipe routing through ant colony optimization. Journal of Infrastructure Systems, 16(2), 149–159.
Cormen, T. H., Leiserson, C. E., Rivest, R. L., & Stein, C. (2009). Introduction to algorithms. Cambridge: The MIT Press.
Dijkstra, E. W. (1959). A note on two problems in connexion with graphs. Numerische Mathematik, 1, 269–271.
Dong, Z., & Lin, Y. (2017a). Ship pipe routing method based on genetic algorithm and cooperative coevolution. Journal of Ship Production and Design, 33, 122–134.
Dong, Z., & Lin, Y. (2017b). A particle swarm optimization based approach for ship pipe route design. International Shipbuilding Progress, 63(1–2), 59–84.
Drotz, M., & Huber, J. (2014). Alternative harness routing and pass-through. M.S. Thesis, Gothenburg, Sweden: Chalmers University of Technology.
El-Mahdy, O. F. M., Ahmed, M. E. H., & Metwalli, S. (2010). Computer aided optimization of natural gas pipe networks using genetic algorithm. Applied Soft Computing, 10, 1141–1150.
Gharaei, A., Shekarabi, S. A. H., & Karimi, M. (2019). Modelling and optimal lot-sizing of the replenishments in constrained, multiproduct and bi-objective EPQ models with defective products: Generalised cross decomposition. International Journal of Systems Science: Operations & Logistics, 6(3), 193–236.
Goebbels, G., Göbel, M., Hambürger, T., Hornung, N., Klein, U., Nikitin, I., Rattay, O., Scharping, J., Troche, K., & Wienss, C. (2007). Real-time dynamics simulation of cables, hoses and wiring harnesses for high accuracy digital mockups and load analysis. In: Proceedings of automotive power electronics (pp. 1–9), Paris, France.
Gotou, J., & Adachi, M. (2007). Harness routing structure. U.S. Patent No. 7,284,785. Washington, DC: U.S. Patent and Trademark Office.
Guirardello, R., & Swaney, R. E. (2005). Optimization process plant layout with pipe routing. Computers & Chemical Engineering, 30, 99–114.
Hermann, T., Patil, L., Srinivas, L., Murthy, K., & Dutta, D. (2012). A search-based approach for prediction of flexible hose shapes. In: Proceedings of the ASME 2012 international mechanical engineering congress & exposition IMECE 2012 (pp. 397–404), Houston, Texas, USA.
Hermansson, T., Bohlin, R., Carlson, J. S., & Söderberg, R. (2013). Automatic assembly path planning for wiring harness installations. Journal of Manufacturing Systems, 32(3), 417–422.
Hermansson, T., Bohlin, R., Carlson, J. S., & Söderberg, R. (2016). Automatic routing of flexible 1D components with functional and manufacturing constraints. Computer-Aided Design, 79, 27–35.
Hightower, D. W. (1969). A solution to line-routing problems on the continuous plane. In: Proceeding DAC’69 proceedings of the 6th annual design automation conference (pp. 1–24), Miami Beach, Florida, USA.
Hong, C., Estefen, S. F., Wang, Y., & Lourenço, M. I. (2018). An integrated optimization model for the layout design of a subsea production system. Applied Ocean Research, 77, 1–13.
Hu, W. & Yan J. (2015). Design for packaging and crash protection of fuel lines of powertrain for cars. Master’s thesis, Gothenbur, Sweden: Chalmers University of Technology.
Ito, T. (1999). A genetic algorithm approach to piping route path planning. Journal of Intelligent Manufacturing, 10, 103–114.
Jiang, W., Lin, Y., Chen, M., & Yu, Y. (2015). A co-evolutionary improved multi-ant colony optimization for ship multiple and branch pipe route design. Ocean Engineering, 105, 63–70.
Kang, S., Myung, S., & Han, S. (1999). A design expert system for auto-routing of ship pipes. Journal of Ship Production, 15(1), 1–9.
Kim, H., Ruy, W., & Jang, B. S. (2013). The development of a practical pipe auto-routing system in a shipbuilding CAD environment using network optimization. International Journal of Naval Architecture and Ocean Engineering, 5, 468–477.
Kobayashi, M., Hirano, Y., & Higashi, M. (2013). Optimization of assembly processes of an automobile wire harness. Computer-Aided Design and Applications, 11(3), 305–311.
Lee, C. Y. (1961). An algorithm for path connections and its applications. IRE Transactions on Electronic Computers, EC, 10(3), 346–365.
Liu, Q. (2016). A rectilinear pipe routing algorithm: Manhattan visibility graph. International Journal of Computer Integrated Manufacturing, 29(2), 202–211.
Liu, Q., & Jiao, G. (2018). A pipe routing method considering vibration for aero-engine using kriging model and NSGA-II. IEEE Access, 6, 6286–6292.
Liu, Q., & Wang, C. (2012). Multi-terminal pipe routing by Steiner minimal tree and particle swarm optimization. Enterprise Information Systems, 6(3), 315–327.
Liu, Q., & Wang, C. (2015). A graph-based pipe routing algorithm in aero-engine rotational space. Journal of Intelligent Manufacturing, 26, 1077–1083.
Mehlhorn, K., & Sanders, P. (2008). Algorithms and data structures: The basic toolbox. Berlin: Springer.
Montgomery, D. C. (2017). Design and analysis of experiments. New York: Wiley.
Nicholson, T. A. J. (1966). Finding the shortest route between two points in a network. The Computer Journal, 9(3), 275–280.
Niu, W., Sui, H., Niu, Y., Cai, K., & Gao, W. (2016). Ship pipe routing design using NSGA-II and coevolutionary algorithm, Mathematical Problems in Engineering, 2016, 7912863, 1–21.
Park, J. (2002). Pipe-routing algorithm development for a ship engine room design. Ph.D. Thesis, Seattle, USA: University of Washington.
Park, J., & Storch, R. L. (2002). Pipe-routing algorithm development: case study of a ship engine room design. Expert Systems with Applications, 23, 299–309.
Prim, R. C. (1957). Shortest connection networks and some generalizations. The Bell System Technical Journal, 36(6), 1389–1401.
Qu, Y., Jiang, D., Gao, G., & Huo, Y. (2016). Pipe routing approach for aircraft engines based on ant colony optimization. Journal of Aerospace Engineering, 29(3), 04015057, 1–10.
Qu, Y., Jiang, D., & Yang, Q. (2018). Branch pipe routing based on 3D connection graph and concurrent ant colony optimization algorithm. Journal of Intelligent Manufacturing, 29(7), 1647–1657.
Rabbani, M., Foroozesh, N., Mousavi, S. M., & Farrokhi-Asl, H. (2019). Sustainable supplier selection by a new decision model based on interval-valued fuzzy sets and possibilistic statistical reference point systems under uncertainty. International Journal of Systems Science: Operations & Logistics, 6(2), 162–178.
Ren, T., Zhu, Z., Dimirovski, G. M., Gao, Z., Sun, X., & Yu, H. (2014). A new pipe routing method for aero-engines based on genetic algorithm. Proceedings of the Institution of Mechanical Engineers, Part G: Journal of Aerospace Engineering, 228(3), 424–434.
Roh, M., Lee, K., & Choi, W. (2007). Rapid generation of the piping model having the relationship with a hull structure in shipbuilding. Advances in Engineering Software, 38, 215–228.
Sayyadi, R., & Awasthi, A. (2016). A simulation-based optimisation approach for identifying key determinants for sustainable transportation planning. International Journal of Systems Science: Operations & Logistics, 5(2), 161–174.
Shekarabi, S. A. H., Gharaei, A., & Karimi, M. (2019). Modelling and optimal lot-sizing of integrated multi-level multi-wholesaler supply chains under the shortage and limited warehouse space: Generalized outer approximation. International Journal of Systems Science: Operations & Logistics, 6(3), 237–257.
Shirakawa, M., & Arakawa, M. (2018). Multi-objective optimization system for plant layout design (3rd report, Interactive multi-objective optimization technique for pipe routing design). Journal of Advanced Mechanical Design Systems, and Manufacturing, 12(2), JAMDSM0053.
Sui, H., & Niu, W. (2016). Branch-pipe-routing approach for ships using improved genetic algorithm. Frontiers of Mechanical Engineering, 11(3), 316–323.
Thomas, J., & Keil, M. J. (2011). Validation of a non-linear mathematical model for predicting the shape of brake hoses in automotive applications. Simulation, 87(6), 538–551.
Van der Velden, C., Bil, C., Yu, X., & Smith, A. (2007). An intelligent system for automatic layout routing in aerospace design. Innovations in Systems and Software Engineering, 3, 117–128.
Wang, Y., Yu, Y., Li, K., Zhao, X., & Guan, G. (2018). A human-computer cooperation improved ant colony optimization for ship pipe route design. Ocean Engineering, 150, 12–20.
Yajima, T., Omori, M., Sugiyama, H., & Yamashita, K. (2009). Harness routing structure for vehicle. U.S. Patent No. 7,561,445. Washington, DC: U.S. Patent and Trademark Office.
Yamaguchi, H., Takedomi, H., Sato, H., & Kitami, Y. (2007). U.S. Patent No. 7,172,042. Washington, DC: U.S. Patent and Trademark Office.
Yin, Y. H., Xu, L. D., Bi, Z., Chen, H., & Zhou, C. (2013). A novel human-machine collaborative interface for aero-engine pipe routing. IEEE Transactions on Industrial Informatics, 9(4), 2187–2199.
Yin, Y. H., Zhou, C., & Zhu, J. Y. (2010). A pipe route design methodology by imitating human imaginal thinking. CIRP Annals-Manufacturing Technology, 59(1), 167–170.
Zhu, D., & Latombe, J. (1991). Pipe routing = Path Planning (with Many Constraints). In Proceedings of the 1991 IEEE international conference on robotics and automation (pp. 1940–1947), Sacramento, CA, USA.
Acknowledgements
This study was supported by the R&D project, “Development and comparison study of measures for wire and pipe arrangement of commercial vehicle” sponsored by Hyundai Motor Company. Such support does not constitute an endorsement by the sponsor of the opinions expressed in this paper. The first five authors are grateful for the support they received from employees at Hyundai Motor Company, especially those who are on the Commercial Vehicle Engineering Data Management Team. We would also like to thank Hyundai Motor Company for their assistance and constructive suggestions during our project.
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Kim, S., Choi, T., Kim, S. et al. Sequential graph-based routing algorithm for electrical harnesses, tubes, and hoses in a commercial vehicle. J Intell Manuf 32, 917–933 (2021). https://doi.org/10.1007/s10845-020-01596-9
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DOI: https://doi.org/10.1007/s10845-020-01596-9