INCONEL® 合金加工和刀具磨损有限元分析评估:扩展回顾

IF 3.3 Q2 ENGINEERING, MANUFACTURING Journal of Manufacturing and Materials Processing Pub Date : 2024-02-09 DOI:10.3390/jmmp8010037
André F. V. Pedroso, N. Sebbe, R. Costa, Marta L. S. Barbosa, R. Sales-Contini, F. Silva, R. Campilho, A. D. De Jesus
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引用次数: 0

摘要

INCONEL® 的机加工在预测其性能方面面临巨大挑战,而对其机加工性能进行全面的实验评估成本高昂且难以为继。可以通过有限元分析(FEA)进行非破坏性的实验设计(DOE)。然而,确定数值模型和构成模型能否准确预测 INCONEL® 加工至关重要。因此,本文对有限元分析加工策略进行了全面回顾,系统地总结和分析了从 2013 年到 2023 年通过有限元分析在 INCONEL® 铣削、车削和钻孔模拟方面取得的进展。此外,还讨论了非常规制造模拟。本综述重点介绍了研究人员在处理 INCONEL® 有限元加工时提出的最新建模数字解决方案、前景和局限性。本文的起源得益于各种来源的文章和书籍。通过有限元分析对 INCONEL® 加工进行模拟,可以通过适当选择损伤和失效标准大大提高实验分析的效果。这种方法不仅能更精确地校准参数,还能改进加工过程中的温度 (T) 预测、精确的刀具磨损 (TW) 数量和类型预测,以及通过评估表面粗糙度 (SR) 和表面应力状态进行精确的表面质量评估。此外,它还有助于在可能使用刀具涂层时做出明智的选择。
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INCONEL® Alloy Machining and Tool Wear Finite Element Analysis Assessment: An Extended Review
Machining INCONEL® presents significant challenges in predicting its behaviour, and a comprehensive experimental assessment of its machinability is costly and unsustainable. Design of Experiments (DOE) can be conducted non-destructively through Finite Element Analysis (FEA). However, it is crucial to ascertain whether numerical and constitutive models can accurately predict INCONEL® machining. Therefore, a comprehensive review of FEA machining strategies is presented to systematically summarise and analyse the advancements in INCONEL® milling, turning, and drilling simulations through FEA from 2013 to 2023. Additionally, non-conventional manufacturing simulations are addressed. This review highlights the most recent modelling digital solutions, prospects, and limitations that researchers have proposed when tackling INCONEL® FEA machining. The genesis of this paper is owed to articles and books from diverse sources. Conducting simulations of INCONEL® machining through FEA can significantly enhance experimental analyses with the proper choice of damage and failure criteria. This approach not only enables a more precise calibration of parameters but also improves temperature (T) prediction during the machining process, accurate Tool Wear (TW) quantity and typology forecasts, and accurate surface quality assessment by evaluating Surface Roughness (SR) and the surface stress state. Additionally, it aids in making informed choices regarding the potential use of tool coatings.
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来源期刊
Journal of Manufacturing and Materials Processing
Journal of Manufacturing and Materials Processing Engineering-Industrial and Manufacturing Engineering
CiteScore
5.10
自引率
6.20%
发文量
129
审稿时长
11 weeks
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