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

该方案旨在开发一种用于加法制造(AM)工艺-激光粉床熔化(L-PBF)制造的零件的多传感器在线计量系统。AM，也被称为“3D打印”，正在改变工程师解决当今问题的方式。与减法制造方法不同，在减法制造方法中，必须切割材料才能生产出成品零件，而AM工艺则是逐层制造零件。这提供了几乎无限的设计自由，允许设计出更有机、更轻便、更定制的解决方案。然而，这项技术并不是没有挑战。在目前的AM技术状态下，无法生产出许多应用所需的一致性或几何公差的零件。AM生产金属零件尤其具有挑战性。制造AM金属零件最突出的技术是L激光熔化，也被称为选择性激光熔化。为了经济地生产零件，该过程必须是快速的，具有高激光功率，这使得L-PBF成为一个对过程变量变化敏感的高能量过程。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、球化、溅射，以及由热应力或残余应力引起的缺陷：开裂、剥落和分层。有效控制L-PBF流程是一项极具挑战性的任务，也是英国和全球研究界重要研究的主题。这一挑战的一个方面在过去几年中已变得明显，那就是需要在过程中条件监测和计量方面进行步骤改变和改进。在线控制的关键参数是熔池温度、粉末床层温度以及铺粉和激光熔化阶段是否存在物理缺陷。巩固粉末的激光聚变事件发生在几百纳秒内，这使得实时观察和控制变得非常困难。幸运的是，在核聚变留下的固结表面上可以观察到大量关于熔化条件的信息，即所谓的过程签名或指纹。通过捕获有关零件表面的形状和纹理的信息，可以确定是否正确选择了激光和扫描参数，更重要的是，还可以监控是否发生了任何重大缺陷。AM工艺，包括L-PBF，还不够成熟，质量可以得到保证。每台机器都会有略有不同的性能特征，零件质量可能每天都会发生变化，环境、粉末质量或激光条件的变化都很小。AM要得到更广泛的应用，行业需要有保证，这意味着过程中测量的健壮性很强。目前的过程中测量方法是不够的；2D成像方法不能识别所有常见的缺陷或测量过程指纹中的表面纹理。已经演示的少数商用前3D测量系统无法适应L PBF观察到的极端范围的纹理。简单地说，对于一些方法来说，表面要么太反射，要么对于其他方法来说太分散，经常产生误导性的成像伪影或遗漏重大缺陷。缺乏强有力的过程中计量，阻碍了L-PBF的发展和更广泛的采用。所需要的是对金属粉末床层的形状、织构和热分布的稳健测量。这项提议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，将提供迄今为止可实现的最完整的过程测量。该多传感器系统将对L PBF过程的过程控制产生深远的影响，并为今后的研究提供丰富的过程数据。

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.