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Multi-sensor in-process metrology of laser powder bed fusion additive manufacturing: Fusing form, texture and temperature measurement.

激光粉末床熔融增材制造的多传感器过程中计量：熔融形式、纹理和温度测量。

基本信息

批准号：
EP/P021468/1
负责人：
Simon Donald Aldred John Lawes
金额：
$ 36.08万
依托单位：
University of Nottingham
依托单位国家：
英国
项目类别：
Research Grant
财政年份：
2017
资助国家：
英国
起止时间：
2017 至无数据
项目状态：
已结题

来源：
https://gtr.ukri.org/projects?ref=EP%2FP021468%2F1
关键词：
Multi sensor process metrology laser

项目摘要

This proposal is to develop a multi-sensor system for in-process metrology of parts made by the additive manufacturing (AM) process - laser powder bed fusion (L-PBF). AM, also known as '3D printing', is changing the way that engineers solve the problems of today. Unlike subtractive manufacturing methods, where materials must be cut away to produce a finished part, AM processes build parts up layer-by-layer. This provides almost limitless design freedom, allowing the design of more organic, more lightweight, more bespoke solutions. However, the technology is not without its challenges. The current state of AM technology cannot produce parts with the consistency or geometric tolerances that are required for many applications. The production of metal parts by AM is particularly challenging. The most prominent technology for producing AM metal parts is L-PBF, also called selective laser melting. To produce parts economically the process must be fast with high laser power making L-PBF a highly energetic process that is sensitive to a changes in process variables. Defects can occur at any stage of the process: incomplete melting, aggregation of unmelted powder, pitting, balling, spattering, as well as defects caused by thermal or residual stresses: cracking, spalling and layer separation. Effective control of the L-PBF process is an extremely challenging task, and the subject of significant research both in the UK and global research communities. One aspect of that challenge that has become clear in the last few years is the need for step change improvements in in-process condition monitoring and metrology. The key parameters for in-process control are the melt pool temperature, the powder bed temperature and the presence of physical defects in the powder laying and laser fusion stages. The laser fusion event that consolidates the powder takes place over a few hundreds of nanoseconds, making it very difficult to observe and control in real-time. Fortunately, a great deal of information about the melting conditions can be observed in the consolidated surface that fusion leaves behind; a so-called process signature or fingerprint. By capturing information on the form and the texture of the part surface it is possible to determine whether the laser and scan parameters have been chosen correctly, and critically it is also possible to monitor whether any major defects have occurred. AM processes, including L-PBF, are not yet mature enough that quality can be assured. Each machine will have slightly different performance characteristics, and the part quality can change from day to day, with small changes in the environment, the powder quality or the laser condition. For AM to be more widely adopted, industries need assurance, and that means highly robust in-process measurements.Current in-process measurement methods are inadequate; 2D imaging methods cannot identify all of the common defects or measure surface texture in the process fingerprint. The few pre commercial 3D measurement systems that have been demonstrated, have been unable to accommodate the extreme range in texture observed for L-PBF. In simple terms the surfaces are either too reflective for some methods, or too diffuse for others, often producing misleading imaging artefacts or missing significant defects. This lack of robust in-process metrology, stymies development and slows the wider adoption of L-PBF. What is required is a robust measurement of form, texture and thermal distribution of the metal powder bed. This proposal will achieve that aim by the intelligent combination of measurement data captured by multiple sensor systems. Each sensor individually cannot capture the whole surface, but when combined, will offer the most complete in process measurement achievable to date. This multi-sensor system will have profound benefits for process control of L PBF processes as well as providing a wealth of in process data to feed into future research.

该提案旨在开发一种多传感器系统，用于通过增材制造（AM）工艺-激光粉末床融合（L-PBF）制造的零件的过程中计量。AM，也被称为“3D打印”，正在改变工程师解决当今问题的方式。与减材制造方法不同，在减材制造方法中，材料必须被切除以生产成品零件，AM工艺逐层构建零件。这提供了几乎无限的设计自由，允许设计更有机，更轻便，更定制的解决方案。然而，这项技术并非没有挑战。AM技术的当前状态不能生产具有许多应用所需的一致性或几何公差的部件。用AM生产金属零件尤其具有挑战性。生产AM金属零件的最突出的技术是L-PBF，也称为选择性激光熔化。为了经济地生产零件，该过程必须快速，高激光功率使L-PBF成为对过程变量变化敏感的高能过程。缺陷可能发生在工艺的任何阶段：不完全熔化、未熔化粉末的聚集、点蚀、成球、飞溅，以及由热应力或残余应力引起的缺陷：开裂、剥落和层分离。L-PBF过程的有效控制是一项极具挑战性的任务，也是英国和全球研究界的重要研究课题。在过去的几年中，这一挑战的一个方面变得越来越明显，那就是需要在过程中的条件监测和计量中进行阶跃变化改进。过程控制的关键参数是熔池温度、粉末床温度以及粉末铺设和激光熔化阶段中是否存在物理缺陷。固化粉末的激光聚变事件发生在数百纳秒内，因此很难实时观察和控制。幸运的是，在熔融留下的固结表面中可以观察到大量关于熔融条件的信息;所谓的过程签名或指纹。通过捕获零件表面的形状和纹理信息，可以确定激光和扫描参数是否选择正确，关键是还可以监控是否发生任何重大缺陷。包括L-PBF在内的增材制造工艺还不够成熟，无法保证质量。每台机器的性能特征略有不同，零件质量每天都会发生变化，环境、粉末质量或激光条件都会发生微小变化。为了使增材制造得到更广泛的应用，各行业需要保证，这意味着高度可靠的过程中测量。目前的过程中测量方法是不够的; 2D成像方法无法识别所有常见的缺陷或测量过程指纹中的表面纹理。已经证明的几个预商用3D测量系统已经不能适应针对L-PBF观察到的纹理的极端范围。简单地说，这些表面对于某些方法来说反射性太强，或者对于其他方法来说过于漫射，通常会产生误导性的成像伪影或遗漏重要的缺陷。这种缺乏强大的过程中计量的情况阻碍了L-PBF的发展并减缓了L-PBF的更广泛采用。所需要的是对金属粉末床的形式、纹理和热分布的稳健测量。该提案将通过智能组合多个传感器系统捕获的测量数据来实现这一目标。每个传感器单独不能捕获整个表面，但当组合在一起时，将提供迄今为止最完整的过程测量。这种多传感器系统将对LPBF过程的过程控制产生深远的影响，并为未来的研究提供丰富的过程数据。