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【期刊论文】Methodology of Parametric Programming for Error Compensation on CNC Centres
刘战强, Z.-Q. Liu
,-0001,():
-1年11月30日
Although work has been carried out on parametric programming on CNC centres, there have been few papers which focus on error compensation. Parametric programming for error compensation is presented in this paper on the basis of a simple model of machining system deflections induced by the radial cutting force in CNC turning operations. The resulting errors are introduced as compensation values to the conventional tool movements along the programmed tool path. This can result in a complex tool path. Parametric programming is applied to handle this complexity for error compensation.
Error compensation, Machining error, Parametric programming, Turning
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【期刊论文】Cutting tool materials for high speed machining*
刘战强, LIU Zhangqiang** and AI Xing
PROGRESS IN NATURAL SCIENCE Vol. 15, No.9, September 2005,-0001,():
-1年11月30日
High speed machinning (HSM) is one of the emerging cutting processes, which is machinging at speed significantly higher than the speed commonly in use on the shop floor. In the last twenty years, high speed machining has received great attentions as a technological solution for high productivity in manufacturing. This article reviews the developments of tool materials in high speed ma-chining operations, and the properties, applications and prospective developments of tool materials in HSM are also presented.
tool materials, high speed machning
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【期刊论文】Simulation Diagnosis for the Bottleneck of roduction Lines and It's Application
刘战强, J. Zhou, a, Z.Q. Liu, b, P.L. Huang, X. Ai, c and J.X. Deng, d
Materials Science Forum Vols. 471-472,-0001,():
-1年11月30日
Traditional bottleneck diagnosis of production lines mainly relies on the designer's experience, theoretical calculation or data analysis after practical system run. There are some disadvantages of the traditional bottleneck diagnosis for production lines. Using the virtual manufacturing technologies, a novel Simulation Diagnosis methodology about the Bottleneck of Production Lines (SDBPL) has been presented. With the proposed method, an existed production line is modeled, simulated and analyzed. Its bottleneck is quickly diagnosed by some ways such as visual simulation results, cycle time, machine utilization and labor utilization. Results reveal that SDBPL can find the location of bottleneck in the practical production lines without wasting practical resource because the entire course of the diagnosis for bottleneck is implemented in virtual environment, and SDBPL is quicker than that of traditional methods as well.
Simulation diagnosis, Bottleneck, Production line, Virtual modeling
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刘战强, 黄传真, 万熠, 艾兴
计算机集成制造系统-CIMS, 2003 9 (11): 937~943,-0001,():
-1年11月30日
根据加工工件来优化选择刀具,包括刀具材料、刀具几何参数、刀具结构、切削参数和机床等切削数据,将关系到生产效率、生产成本及加工质量。建立切削数据库,向机械制造业提供合理或优化的切削用量,是增强企业竞争力最有效的措施之一。本文结合国内外切削数据库研究开发现状,探讨建立切削数据库的核心技术,分析切削数据库研究及应用过程中存在的问题,着重探讨切削数据库的发展趋势,指出切削数据库未来的研究方向将是集成化、智能化、实用化、网络化和标准化。
切削数据库, 刀具, 切削用量
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刘战强, Z.Q. Liu, a, J.B. Zhang, b and Z.T. Tang, c
Materials Science Forum Vols. 471-472,-0001,():
-1年11月30日
Industry is looking for practical means to improve the accuracy of the parts machined on CNC machines. Some artificial intelligence (AI) systems have been applied in modeling and compensating manufacturing process errors in CNC machining. However, these systems are not capable of predicting the results of a new operation if no sufficient data on a number of similar operations is available. A generalized AI approach named synergistic interactions amongst modeling, sensing and learning is proposed in this paper. Based on the AI approach, a new strategy of error compensation of workpiece dimension in CNC machining is developed and applied in a CNC turning center. Error compensation results are illustrated the effectiveness of the error compensation strategy. The learning curve shows that the error compensation confidence gradually progresses towards 100% confidence from zero along with the CNC machine operation time increasing.
Error compensation, CNC machining, Artificial intelligence, Modeling, Sensing, Learning
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