High performance cutting of lightweith composites and advanced aerospace alloys

现代飞机应该确保减少燃油消耗以及减少二氧化碳、氮氧化物和噪音排放。为了实现这些目标，机身、发动机设计和制造技术的改进是必要的。这意味着需要使用轻质材料来制造机身和发动机，并使用先进的涡轮材料来制造圆盘和叶片。最广泛用于机身的先进高强度合金是铝合金、铝锂、铝镁钪、钛合金和轻质复合材料，如纤维增强塑料(FRP)、碳纤维或玻璃纤维增强聚合物(C/GFRP)和钛金属基复合材料(TiMMC)。用于飞机发动机的金属材料，如Inconel 718、Udimet、Allvac、芳纶、Ti6Al4v和Ti-6246。这些材料在汽车和生物医学领域也具有巨大的应用潜力。 在咨询了行业(普惠、RTI和庞巴迪)之后，利用这笔发现基金，我们将重点评估两种材料：钛金属基复合材料(TiMMCs)和碳纤维增强聚合物(CFRP)。我们的初步研究和文献回顾让我们有机会定义一个有效的假设： 1.通过适当控制初始切割条件和初始刀具磨损，可以将整个刀具寿命提高至少20%。 2.采用更适合复合材料(CFRP)的表面粗糙度分析方法和参数，即利用分形分析，可以更准确地预测零件的使用性能。 3.使用基于模式识别和数据逻辑分析的生存分析、分形分析和刀具磨损监测，可以提高刀具寿命的估计。 分析初始切削条件、初始刀具磨损及其在加工过程中对整个刀具寿命的影响(TiMMCs)和(CFRP)的概念以前从未被研究过。我们的初步工作还表明，混沌理论和分形学在分析初始切削条件和表面粗糙度方面具有很好的应用前景。分形学理论已经在许多工程和技术应用中被证明是非常有效的。这种新的哲学可以极大地改变机械加工的研究方法。这涉及到对加工过程的初始参数进行彻底的分析。因此，这项工作的原创性在于使用混沌理论和分形学作为一种方法来理解刀具磨损和生成新的、有意义的含纤维塑料(CFRP)表面粗糙度参数。这种新的方法还可以极大地提高刀具的诊断和监测以及切削参数的优化。我们并不声称要使机械加工理论发生革命性的变化，但我们打算为机械加工过程的分析带来一个新的视角。

Modern aircraft should ensure reduced fuel consumption as well as reduced CO2, NOx, and noise emission. To achieve these goals, airframe, engine design and manufacturing technology improvements are necessary. This implies the need to employ lightweight materials for airframes and engines and advanced turbine materials for discs and blades. The most widely used advanced high strength alloys for airframes are aluminium alloys, aluminium-lithium, aluminium-magnesium-scandium, titanium alloys and lightweight composite materials like Fiber Reinforced Plastic (FRP), Carbon or Glass Fiber Reinforced Polymer (C/GFRP), and Titanium Metal Matrix Composites (TiMMCs). For aircraft engines, metallic materials like Inconel 718, Udimet, Allvac, Aramid, Ti6Al4v and Ti-6246. These materials also have great potential for application in the automotive and biomedical sectors. After consulting the industry (Pratt&Whitney, RTI and Bombardier), with this discovery grant, we will focus on evaluation of two materials: Titanium Metal Matrix Composites (TiMMCs) and Carbon Fibre Reinforced Polymer (CFRP). Our preliminary research and a literature review give us the opportunity to define a working hypothesis: 1. It is possible to increase the entire tool life by at least 20% by appropriate control of initial cutting conditions and initial tool wear. 2. Part performance in service can be predicted more accurately using new surface roughness analysis methods and parameters better adapted to composite materials (CFRPs), namely using fractal analysis. 3. Tool life estimations can be improved using survival analysis, fractal analysis, and tool wear monitoring based on pattern recognition and Logical Analysis of Data. The concept of analyzing initial cutting conditions, initial cutting tool wear, and their impact on entire tool life during machining (TiMMCs) and (CFRPs) has never been studied before. Our preliminary works also show that the application of chaos theory and fractals for analysis of initial cutting conditions and surface roughness is very promising. The theory of fractals has already proven highly effective in many engineering and technology applications. This new philosophy can dramatically change research methods in machining. This involves a thorough analysis of the initial parameters of the machining process. Consequently, the originality of this work lies in the use of chaos theory and fractals as an approach to understand cutting tool wear and generate new, meaningful surface roughness parameters for plastics containing fibers (CFRPs). This new approach can also greatly improve the diagnosis and monitoring of cutting tools and the optimization of cutting parameters. We do not claim to revolutionize machining theory but we intend to bring to light a new perspective for the analysis of machining processes.