Research on an improved ant colony algorithm for optimizing the inspection path of free-form surfaces

• Autorzy: Chen Yueping , Wei Sian , Ma Jiegao

Identyfikatory

DOI

10.24425/mms.2025.154343

• Języki publikacji: EN

Abstrakty

EN

To address the disordered inspection paths and long inspection time encountered when coordinate measuring machines (CMMs) inspect free-form surface parts, an improved ant colony algorithm was proposed to optimize the inspection path and thereby improve inspection efficiency. To enhance the optimization performance of the ant colony algorithm and overcome its shortcomings, such as low search speed and susceptibility to local optimal solutions, this work improves the initial pheromone distribution, pheromone evaporation factor, and pheromone update strategy and introduces a local search strategy. The experimental results revealed that the improved ant colony algorithm had strong search directionality in the early stages of iteration, higher search speed, and an enhanced ability to escape from local optimal solutions; the inspection paths of the free-form surface optimized by the improved ant colony algorithm were neat and aesthetically pleasing, and the inspection efficiency increased by up to 14.75%, 23.59%, and 34.21% compared with those of the classic ant colony algorithm, artificial bee colony algorithm, and genetic algorithm, respectively.

Słowa kluczowe

EN

free-form surface; path planning; ant colony algorithm; coordinate measuring machine

• Wydawca: Komitet Metrologii i Aparatury Naukowej PAN
• Czasopismo: Metrology and Measurement Systems
• Rocznik: 2025
• Tom: Vol. 32, nr 2
• Strony: 1--17
• Opis fizyczny: Bibliogr. 32 poz., rys., tab., wykr., wzory

Twórcy

autor

Chen Yueping

• Guangxi University of Science and Technology, School of Mechanical and Automotive Engineering, Liuzhou, China

autor

Wei Sian

• Guangxi University of Science and Technology, School of Mechanical and Automotive Engineering, Liuzhou, China

autor

Ma Jiegao

• Dongfeng Liuzhou Motor Co., Ltd, Liuzhou, China

Bibliografia

• [1] Zahmati, J., Amirabadi, H., & Mehrad, V. (2018). A hybrid measurement sampling method for accurate inspection of geometric errors on freeform surfaces. Measurement, 122, 155-167. https://doi.org/10.1016/j.measurement.2018.03.013
• [2] Kamrani, A., Nasr, E.A., Al-Ahmari, A., Abdulhameed, O., & Mian, S.H. (2014). Feature-based design approach for integrated CAD and computer-aided inspection planning. The International Journal of Advanced Manufacturing Technology, 76(9-12), 2159-2183. https://doi.org/10.1007/s00170-014-6396-0
• [3] Abdulhameed, O., Mian, S.H., Al-Ahmari, A., & Alkhalefah, H. (2020). Patch and curvature specific estimation of efficient sampling scheme for complex surface inspection. The International Journal of Advanced Manufacturing Technology, 110(11-12), 3407-3422. https://doi.org/10.1007/s00170-020-06063-6
• [4] He, G., Sang, Y., Pang, K., & Sun, G. (2018). An improved adaptive sampling strategy for freeform surface inspection on CMM. The International Journal of Advanced Manufacturing Technology, 96(1-4), 1521-1535. https://doi.org/10.1007/s00170-018-1612-y
• [5] Teodor, V.G., Păunoiu, V., Susac, F., & Baroiu, N. (2019). Optimization of the measurement path for the car body parts inspection. Measurement, 146, 15-23. https://doi.org/10.1016/j.measurement.2019.06.002
• [6] Li, B., Feng, P., Zeng, L., Xu, C., & Zhang, J. (2018). Path planning method for on-machine inspection of aerospace structures based on adjacent feature graph. Robotics and Computer-Integrated Manufacturing, 54, 17-34. https://doi.org/10.1016/j.rcim.2018.05.006
• [7] Liu, Y., Zhao, W., Sun, R., & Yue, X. (2020). Optimal path planning for automated dimensional inspection of free-form surfaces. Journal of Manufacturing Systems, 56, 84-92. https://doi.org/10.1016/j.jmsy.2020.05.008
• [8] Tsagaris, A., & Mansour, G. (2019). Path planning optimization for mechatronic systems with the use of genetic algorithm and ant colony. IOP Conference Series Materials Science and Engineering, 564(1), 012051. https://doi.org/10.1088/1757-899x/564/1/012051
• [9] Yi, B., Qiao, F., Hua, L., Wang, X., Wu, S., & Huang, N. (2022). Touch Trigger Probe-Based Interference-Free Inspection Path Planning for Free-form Surfaces by Optimizing the Probe Posture. IEEE Transactions on Instrumentation and Measurement, 71, 1-8. https://doi.org/10.1109/tim.2022.3147314
• [10] Li, Y., Zeng, L., Tang, K., & Xie, C. (2019). Orientation-point relation based inspection path planning method for 5-axis OMI system. Robotics and Computer-Integrated Manufacturing, 61, 101827. https://doi.org/10.1016/j.rcim.2019.101827
• [11] Abdulhameed, O., Al-Ahmari, A., Mian, S.H., & Aboudaif, M.K. (2020). Path planning and setup orientation for automated dimensional inspection using coordinate measuring machines. Mathematical Problems in Engineering, 2020, 1-17. https://doi.org/10.1155/2020/9683074
• [12] Han, Z., Liu, S., Yu, F., Zhang, X., & Zhang, G. (2017). A 3D measuring path planning strategy for intelligent CMMs based on an improved ant colony algorithm. The International Journal of Advanced Manufacturing Technology, 93(1-4), 1487-1497. https://doi.org/10.1007/s00170-017-0503-y
• [13] Stojadinovic, S.M., Majstorovic, V.D., Durakbasa, N.M., & Sibalija, T.V. (2016). Ants colony optimisation of a measuring path of prismatic parts on a CMM. Metrology and Measurement Systems, 23(1), 119-132. https://doi.org/10.1515/mms-2016-0011
• [14] Zhao, Z., Li, Y., & Fu, Y. (2022). Collision-free path planning for efficient inspection of free-form surface by using a trigger probe. The International Journal of Advanced Manufacturing Technology, 120(3-4), 2183-2200. https://doi.org/10.1007/s00170-022-08917-7
• [15] Zakharov, O., Balaev, A., & Kochetkov, A. (2017). Modeling Optimal Path of Touch Sensor of Coordinate Measuring Machine Based on Traveling Salesman Problem Solution. Procedia Engineering, 206, 1458-1463. https://doi.org/10.1016/j.proeng.2017.10.661
• [16] He, G., Huang, X., Ma, W., Sang, Y., & Yu, G. (2016). CAD-based measurement planning strategy of complex surface for five axes on machine verification. The International Journal of Advanced Manufacturing Technology, 91(5-8), 2101-2111. https://doi.org/10.1007/s00170-016-9932-2
• [17] Zhao, W., Wang, X., & Liu, Y. (2022). Path planning for 5-Axis CMM inspection considering path reuse. Machines, 10(11), 973. https://doi.org/10.3390/machines10110973
• [18] Han, Z., Liu, S., Li, X., Wang, Y., Zhang, X., & Zhang, G. (2018). Path planning method for intelligent CMMs based on safety and the high-efficiency principle. The International Journal of Advanced Manufacturing Technology, 95(9-12), 4003-4012. https://doi.org/10.1007/s00170-017-1500-x
• [19] Lin, C., & Lin, C. (2019). An adaptive-group-based differential evolution algorithm for inspecting machined workpiece path planning. The International Journal of Advanced Manufacturing Technology, 105(5-6), 2647-2657. https://doi.org/10.1007/s00170-019-04521-4
• [20] Zhang, P., Wang, J., Tian, Z., Sun, S., Li, J., & Yang, J. (2022). A genetic algorithm with jumping gene and heuristic operators for traveling salesman problem. Applied Soft Computing, 127, 109339. https://doi.org/10.1016/j.asoc.2022.109339
• [21] Jain, R., Singh, K.P., Meena, A., Rana, K.B., Meena, M.L., Dangayach, G.S., & Gao, X. (2022). Application of proposed hybrid active genetic algorithm for optimization of traveling salesman problem. Soft Computing, 27(8), 4975-4985. https://doi.org/10.1007/s00500-022-07581-z
• [22] Yang, K., You, X., Liu, S., & Pan, H. (2020). A novel ant colony optimization based on game for traveling salesman problem. Applied Intelligence, 50(12), 4529-4542. https://doi.org/10.1007/s10489-020-01799-w
• [23] Xiao, Z., Wang, Z., Liu, D., & Wang, H. (2021). A path planning algorithm for PCB surface quality automatic inspection. Journal of Intelligent Manufacturing, 33(6), 1829-1841. https://doi.org/10.1007/s10845-021-01766-3
• [24] Liu, H., Lee, A., Lee, W., & Guo, P. (2023). DAACO: adaptive dynamic quantity of ant ACO algorithm to solve the traveling salesman problem. Complex & Intelligent Systems, 9(4), 4317-4330. https://doi.org/10.1007/s40747-022-00949-6
• [25] Chen, J., Zheng, K., Li, Q., & Ayush, A. (2022). Influence of subproblem solutions on the quality of traveling thief problem solutions. Journal of Intelligent & Fuzzy Systems, 44(2), 1943-1956. https://doi.org/10.3233/jifs-221032
• [26] Gao, W. (2020). Modified ant colony optimization with improved tour construction and pheromone updating strategies for traveling salesman problem. Soft Computing, 25(4), 3263-3289. https://doi.org/10.1007/s00500-020-05376-8
• [27] İlhan, İ., & Gökmen, G. (2022). A list-based simulated annealing algorithm with crossover operator for the traveling salesman problem. Neural Computing and Applications, 34(10), 7627-7652. https://doi.org/10.1007/s00521-021-06883-x
• [28] Wang, L., Cai, R., Lin, M., & Zhong, Y. (2019). Enhanced List-Based Simulated Annealing Algorithm for Large-Scale Traveling Salesman Problem. IEEE Access, 7, 144366-144380. https://doi.org/10.1109/access.2019.2945570
• [29] Khan, I., & Maiti, M.K. (2018). A swap sequence based Artificial Bee Colony algorithm for Traveling Salesman Problem. Swarm and Evolutionary Computation, 44, 428-438. https://doi.org/10.1016/j.swevo.2018.05.006
• [30] Choong, S.S., Wong, L., & Lim, C.P. (2018). An artificial bee colony algorithm with a Modified Choice Function for the traveling salesman problem. Swarm and Evolutionary Computation, 44, 622-635. https://doi.org/10.1016/j.swevo.2018.08.004
• [31] Ouaarab, A., Ahiod, B., & Yang, X. (2013). Discrete cuckoo search algorithm for the travelling salesman problem. Neural Computing and Applications, 24(7-8), 1659-1669. https://doi.org/10.1007/s00521-013-1402-2
• [32] Osaba, E., Yang, X., Diaz, F., Lopez-Garcia, P., & Carballedo, R. (2015). An improved discrete bat algorithm for symmetric and asymmetric Traveling Salesman Problems. Engineering Applications of Artificial Intelligence, 48, 59-71. https://doi.org/10.1016/j.engappai.2015.10.006

Uwagi

This work was financially supported by the National Nature Science Foundation of China (51565006, 52165054), the Natural Science Foundation of the Guangxi Province (2025GXNSFHA069171), the Science Research Innovation Team Project of the Guangxi Provincial Education Department, and the Science Research Innovation Team Project of Guangxi University of Science and Technology.