Mr. Zian Liu Profile

Zian Liu

at Xiamen University of Technology

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Proceedings Article | 5 November 2020 Paper

Research on multi-objective optimization of decision scheme in CNC manufacturing process

Zian Liu, Kun Qin, Jianchun Liu, Jinfa Su

Proceedings Volume 11568, 115681M (2020) https://doi.org/10.1117/12.2580167

KEYWORDS: Optimization (mathematics), Manufacturing, Genetic algorithms, Surface roughness, Spindles, Energy efficiency, Data modeling, Radium, Performance modeling

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From precision machining to green manufacturing, the search for an economical and effective green manufacturing chain system has gradually become the focus of the metal processing industry in order to ensure the quality of workshop manufacturing, increase the production capacity per unit of energy consumption, and reduce processing consumables. The existing research The focus is more on the establishment of the objective function model, the optimization method used and the targeted optimization direction are relatively single, and a more complete manufacturing system has not been established. There are three main optimization goals for processing process parameters in this subject: starting from the direction of processing quality, reducing the surface roughness of the workpiece as the optimization goal, establishing a cutting surface integrity (Ra) function; starting from the direction of enterprise manufacturing, to improve milling efficiency Optimize the objective and establish the cutting efficiency (SEC) function; starting from the processing cost, to reduce the amount of tool wear as the optimization objective, build a machine tool tool wear visual inspection mechanism to assist in the establishment of the tool wear (VB) function, and introduce a non-dominant sorting genetic algorithm to obtain Pareto After the frontier solution, different optimization suggestions are proposed for the refinement of rough/finish processing and general processing. The results show that the NSGA-Ⅱ model has a stronger search ability than the GA model when faced with multiple quasi-measurement decision problems. The processing efficiency can be increased by 42.7%, the tool cost can be saved by 25%, and the workpiece quality can be increased by 21.8%.

Proceedings Article | 5 November 2020 Paper

Research on collision detection algorithm of multi-robot bonnet polishing system

Kun Qin, Zian Liu, Jianchun Liu

Proceedings Volume 11568, 1156815 (2020) https://doi.org/10.1117/12.2579860

KEYWORDS: Optical spheres, Polishing, Detection and tracking algorithms, Robots, Space robots, Space operations, Sensors, Sensing systems, Parallel computing

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In a multi-robot bonnet polishing system, the mobile space between robots overlaps with each other, so collision detection is the premise of the safe and stable operation of the system. The sphere and capsule bounding boxes are used to simplify the model of the multi-robot bonnet polishing system, and the collision detection problem is transformed into the judgment of intersection among bounding boxes in the simplified model. The intersection of bounding boxes is preliminarily judged by the second projection method. The bounding box is projected into line segments. It avoids a lot of multiplication and square operation. If the projection line segments are not overlapped, the bounding box will not intersect. If the projection line segments are overlapped, the problem is transformed into the shortest distance solution from point to point, point to line and line to line. Using space geometry method to calculate the shortest distance between point and line segment. Using the method of transforming reference coordinate system to calculate the shortest distance between two line segment. Through the analysis of simulation software, compared with other algorithms, the average time consumed of the algorithm is reduced by 100%, and the detection efficiency is significantly improved. The algorithm can be better applied to multi-robot bonnet polishing system.

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