Transactions of Materials and Heat Treatment

Title：Research on intelligent forging technology and its industrialization strategy

Authors： Wang Xinyun Jin Junsong Li Jianjun Xia Juchen

Unit： Huazhong University of Science & Technology

KeyWords： intelligentialize forging industrialization equipment process design

ClassificationCode：

year,vol(issue):pagenumber：2018,43(7):112-120

Abstract：

Forgings are the basic parts in the manufacturing industry, and intelligent forging is an inevitable development trend in the forging technology. Therefore, the advantages and significance of intelligent forging were discussed in terms of product quality, production efficiency, optimization of industrial structure and energy conservation and green environmental protection. From the aspects of design and manufacturing, the connotation of intelligent manufacturing was explained, and the current status of R & D and application of intelligent forging technology in China was introduced considering intelligent design technology, intelligent equipment technology as well as intelligent workshop technology. Furthermore, the problems in the intelligentization of forging industry in China were discussed in terms of enterprise level, automation, digitization, informatization as well as forging equipment and molds. The results show that the intelligent forging technology is still at a very early stage. In view of current situation, the development proposals were given in terms of research and development of leadingedge technologies, personnel training and industryrelated standards.

Funds：

王新云（1973-），男，博士，教授，E-mail：wangxy_hust@163.com

Reference：

[1]吴顺达. 战略性新兴产业和锻造行业[J]. 锻造与冲压, 2012, (1):22.

Wu S D. Strategic emerging industries and forging industry[J]. Forging and Metal Forming, 2012, (1):22.

[2]郭良刚, 王凤琪, 梁磊, 等. 高性能环件辗轧成形智能仿真优化新思路与研究进展[J]. 精密成形工程, 2017, 9(4):1-11.

Guo L G, Wang F Q, Liang L, et al. New idea and advances in intelligent simulation and optimization of highperformance ring rolling process[J]. Journal of Netshape Forming Engineering, 2017, 9(4):1-11.

[3]陈宇, 吕文兵, 陆新江. 模锻过程结合机理与数据的智能控制方法[J]. 锻压技术, 2017,42(4):170-178.

Chen Y, Lyu W B, Lu X J. Intelligent control method combining mechanism and data in the die forging process[J]. Forging & Stamping Technology, 2017,42(4):170-178.

[4]张希磊, 章志兵, 柳玉起. 基于CATIA平台的汽车覆盖件模具非标斜楔智能辅助设计系统[J]. 锻压技术, 2017, 42(6):140-145.

Zhang X L, Zhang Z B, Liu Y Q. Nonstandard wedge aided design system of automobile panel die based on CATIA platform[J]. Forging & Stamping Technology, 2017, 42(6):140-145.

[5]张瑛. 伺服螺旋精压机控制系统研发及成形工艺库实现[D]. 广州：广东工业大学, 2016.

Zhang Y. Research on Control System of Servo Crew Coining Press and Realization of Forming Technology Library[D]. Guangzhou:Guangdong University of Technology, 2016.

[6]苏畅, 孙勇, 徐超, 等. 人工智能方法在热模锻压力机故障诊断技术中的应用[J]. 锻压技术, 2015, 40(4):102-105.

Su C, Sun Y, Xu C, et al. Application of artificial intelligence methods in fault diagnosis technology of hot die forging press[J]. Forging & Stamping Technology, 2015, 40(4):102-105.

[7]王晓哲, 洪衍涛. 台达伺服系统在快速成形机上的应用[J]. 智能机器人, 2014,(8):30-32.

Wang X Z, Hong Y T. Application of delta servo system on rapid forming machine[J]. Intelligent Robot, 2014, (8):30-32.

[8]曾琦, 蒋鹏, 任学平. 自动化锻造生产线在线监测技术[J]. 锻造与冲压, 2013, (3):32.

Zeng Q, Jiang P, Ren X P. On-line monitoring technology of automatic forging production line[J]. Forging and Metal Forming, 2013, (3):32.

[9]王强. 面向精确热成形工艺的数字机械伺服压力机应用研究[D]. 武汉：华中科技大学, 2016.

Wang Q. The Research of Digital Servo Press Machine Used for Precision Hot Stamping Process[D]. Wuhan:Huazhong University of Science and Technology, 2016.

[10]徐岩, 秦波. 基于人工智能技术的板料冲压成形回弹预测研究方法探析[J]. 电子制作, 2014, (19):41.

Xu Y, Qing B. Research on prediction method of springback of sheet metal forming based on artificial intelligence[J]. Practical Electronics, 2014, (19):41.

[11]王佳骏, 郭鸿镇, 梁厚权, 等. 基于BP神经网络的TC18钛合金锻造工艺参数研究[J]. 热加工工艺, 2014,43(15):1-6.

Wang J J, Guo H Z, Liang H Q, et al. Study on forging parameters of TC18 titanium alloy based on BP neural network[J]. Hot Working Technology, 2014,43(15):1-6.

[12]安兴运. 基于以太网的热成形生产线总控系统研究[D]. 武汉：华中科技大学, 2014.

An X Y. Research on Bus Control System of Thermoforming Production Line Based on Ethernet[D]. Wuhan:Huazhong University of Science and Technology, 2014.

[13]樊红梅, 孙宇, 王尚斌. 压力成形设备智能控制与远程诊断维护系统[J]. 塑性工程学报, 2010, 17(5):37-42.

Fan H M, Sun Y, Wang S B. Intelligent monitoring and remote fault diagnosis & maintenance system for pressure forming equipment[J]. Journal of Plasticity Engineering, 2010, 17(5):37-42.

[14]秦芳诚, 李永堂, 巨丽, 等. 环件辗扩成形过程微观组织及性能控制研究进展[J]. 机械工程学报, 2016, 52(16):42-56.

Qin F C, Li Y T, Ju L, et al. Advances in control of microstructure and properties during rolling forming of ring parts[J]. Journal of Mechanical Engineering, 2016, 52(16):42-56.

[15]陈飞, 崔振山, 董定乾. 微观组织演变元胞自动机模拟研究进展[J]. 机械工程学报, 2015, 51(4):30-39.

Chen F, Cui Z S, Dong D Q. Research progress in cellular automaton simulation of microstructure evolution[J]. Journal of Mechanical Engineering, 2015, 51(4):30-39.

[16]孟炬, 朱彬, 张宜生, 等. 高强钢热冲压成形过程宏微观数值模拟综述[J]. 河北工业科技, 2015, 32(3):272-276.

Meng J, Zhu B, Zhang Y S, et al. Review on macro-and micro-modeling of high strength steel hot stamping process[J]. Hebei Journal of Industrial Science & Technology, 2015, 32(3):272-276.

[17]邹甜, 华林, 韩星会. 环件热轧全过程微观组织演化数值模拟和试验研究[J]. 机械工程学报, 2014, 50(16):97-103.

Zou T, Hua L, Han X H. Simulation and experiment study on the microstructure evolution during the whole hot ring rolling process[J]. Journal of Mechanical Engineering, 2014, 50(16):97-103.

[18]孙勇, 赵君鑫, 代合平, 等. 基于ISA95标准的数字化锻造工厂模型[J]. 锻压技术, 2016, 41(5):8-13.

Sun Y, Zhao J X, Dai H P, et al. Model of digital forging factory based on standard ISA95[J]. Forging & Stamping Technology, 2016, 41(5):8-13.

[19]曾琦, 蒋鹏, 任学平, 等. 曲轴智能锻造系统集成[J]. 锻压技术, 2017, 42(4):138-142.

Zeng Q, Jiang P, Ren X P,et al. Integrated technology of crankshaft intelligent forging system[J]. Forging & Stamping Technology, 2017, 42(4):138-142.

[20]黄阳, 朱育林, 李东波. 锻造CAPP专家系统生成技术的研制[J]. 机电产品开发与创新, 2006, 19(6):79-80.

Huang Y, Zhu Y L, Li D B. Study on technology of creating the forging CAPP expert system[J]. Development & Innovation of Machinery & Electrical Products, 2006, 19(6):79-80.

[21]赵升吨, 贾先. 智能制造及其核心信息设备的研究进展及趋势[J]. 机械科学与技术, 2017, 36(1):1-16.

Zhao S D, Jia X. Research progress and development trend of intelligent manufacturing and its core information equipment[J]. Mechanical Science and Technology for Aerospace Engineering, 2017, 36(1):1-16.

[22]陈超, 赵升吨, 范淑琴, 等. 伺服液压机的研究现状及发展趋势[J]. 锻压技术, 2015, 40(12):1-6.

Chen C, Zhao S D, Fan S Q, et al. Advance and trend of servo hydraulic press[J]. Forging & Stamping Technology, 2015, 40(12):1-6.

[23]赵升吨, 陈超, 崔敏超, 等. 交流伺服压力机的研究现状与发展趋势[J]. 锻压技术, 2015, 40(2):1-7.

Zhao S D, Chen C, Cui M C, et al. Research status and development tendency of AC servo press[J]. Forging & Stamping Technology, 2015, 40(2):1-7.

[24]俞庆华. 舒勒智能冲压车间——智能数据解决方案提升成形技术领域的工艺可靠性与成本效益[J]. 汽车零部件, 2018, (1):36.

Yu Q H. Smart press shop in Schuler=Improvement of process reliability and cost effectiveness in forming by intelligent data solutions[J]. Automobile Parts, 2018, (1):36.

[25]徐刚, 崔瑞奇, 王华. 我国金属成形(锻压)机床的现状与发展动向[J]. 锻压装备与制造技术, 2017, 52(3):7-16.

Xu G,Cui R Q, Wang H. Status and developing trend of national metalforming machine tool[J]. China Metalforming Equipment & Manufacturing Technology, 2017, 52(3):7-16.

[26]廖志慧,刘宏伟,阮班明. 生产车间“聪明”起来[N]. 襄阳日报,2018-08-26.

Liao Z H, Liu H W, Ruan B M. Production workshop becomes smarter[N]. Xangyang Daily,2018-08-26.

[27]汪拥进, 梁文奎. 三环锻造：从中国制造迈向中国“智”造[N]. 中国质量报,2018-05-08

Wang Y J, Liang W K. Tri-Ring Forging Co., Ltd.: From made in China to intelligent made in China[N]. China Quality Daily,2018-05-08.

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