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Cheng Yu Jiang

Researcher at Northwestern Polytechnical University

Publications -  5
Citations -  23

Cheng Yu Jiang is an academic researcher from Northwestern Polytechnical University. The author has contributed to research in topics: Configuration design & Computer Aided Design. The author has an hindex of 2, co-authored 4 publications receiving 23 citations.

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A fixture design system for networked manufacturing

TL;DR: A hybrid CBR/KBR (case- based reasoning/knowledge-based reasoning) fixture design method is proposed, with CBR as its core, KBR as its assistant and CBRas as the support of case-adaptation process for rapid configuration design.
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Research on Analyzing and Coding Technology of Manufacturing Information Resource Based on Granularity-Structure

TL;DR: The result proves that the technique of analyzing and coding to MIR based on GS has provided an effective method to standardize the MIR organization under the development mode of product life cycle (PLC).
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Study of the Classification of Cutting Forces and the Build of Accurate Milling Force Model in End Milling

TL;DR: In this article, a new approach is proposed to model the milling force based on the cutting force shape characteristics in end milling, and the relationship between the cutting forces shape characteristics and the cutting depths is analyzed and milling forces are classified into 10 types according to the combination of cutting depths.
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Efficient Algorithms for Calculations of the Maximum Surface Form Errors in Peripheral Milling

TL;DR: Some key techniques such as the finite-element modeling of the tool-workpiece system; the determinant algorithm to judge instantaneous immersion boundaries between a cutter element and the workpiece; iterative scheme for the calculations of tool- workpiece deflections considering the former convergence cutting position are developed and the method for calculating the position and magnitude of the maximum surface form errors are developed.
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Optimization of precision molding process parameters of viscoelastic materials based on BP neural network improved by genetic algorithm

TL;DR: In this article , a thermocompression model of a viscoelastic material and a mold is developed using coupled thermal-structural analysis in Abaqus, and the data was analyzed to investigate the influence of process parameters on GMP performance.