Towards intelligent design optimization: Progress and challenge of design optimization theories and technologies for plastic forming

工程优化 计算机科学 领域(数学) 利用 工业工程 过程(计算) 产品设计 最优化问题 数学优化 工程类 系统工程 产品(数学) 数学 计算机安全 算法 纯数学 操作系统 几何学
作者
Heng Li,Jingchao Yang,Guangyao Chen,Xin Liu,Zhao Zhang,Guangjun Li,Wenhui Liu
出处
期刊:Chinese Journal of Aeronautics [Elsevier BV]
卷期号:34 (2): 104-123 被引量:20
标识
DOI:10.1016/j.cja.2020.09.002
摘要

Plastic forming is one of enabling and fundamental technologies in advanced manufacturing chains. Design optimization is a critical way to improve the performance of the forming system, exploit the advantages of high productivity, high product quality, low production cost and short time to market and develop precise, accurate, green, and intelligent (smart) plastic forming technology. However, plastic forming is quite complicated, relating to multi-physics field coupling, multi-factor influence, multi-defect constraint, and triple nonlinear, etc., and the design optimization for plastic forming involves multi-objective, multi-parameter, multi-constraint, nonlinear, high-dimensionality, non-continuity, time-varying, and uncertainty, etc. Therefore, how to achieve accurate and efficient design optimization of products, equipment, tools/dies, and processing as well as materials characterization has always been the research frontier and focus in the field of engineering and manufacturing. In recent years, with the rapid development of computing science, data science and internet of things (IoT), the theories and technologies of design optimization have attracted more and more attention, and developed rapidly in forming process. Accordingly, this paper first introduced the framework of design optimization for plastic forming. Then, focusing on the key problems of design optimization, such as numerical model and optimization algorithm, this paper summarized the research progress on the development and application of the theories and technologies about design optimization in forming process, including deterministic and uncertain optimization. Moreover, the applicability of various modeling methods and optimization algorithms was elaborated in solving the design optimization problems of plastic forming. Finally, considering the development trends of forming technology, this paper discusses some challenges of design optimization that may need to be solved and faced in forming process.
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