Eradicating hydrofluoric acid from metal etching

在过去的50年里，制造商准备金属高价值零件表面的方式几乎没有变化，依赖于在大量腐蚀性和通常有毒的酸中进行基于浴的化学蚀刻，然后人工目视检查大缺陷。这产生了大量难以处理的废物，同时对成品零件应用了过于慷慨的安全系数，因为目前并非所有存在的缺陷都可以在生产线过程中识别和量化。这首先表明在产生大量废物方面效率低下，尽管环境和用户可能会接触腐蚀性和有毒化学品。其次，由于零件寿命明显缩短，装载条件比可能的更轻，这增加了维护干预，从而导致效率低下。我们将创建一套新的工艺，通过使用少量无害化学品（电解质）施加有针对性的带电流体射流，可以蚀刻相同的材料。这些电解液将被再循环，并将创建一个自动健康监测系统，以确保在零件表面保持适当的蚀刻反应，并确保资源效率。废电解液将被过滤，含金属的碎片将返回到制造供应链，大大减少化学品的数量，并确保所应用的化学品对环境和最终用户的风险大大降低。我们将在蚀刻期间和之后观察生成的表面，并通过量化表面的各个方面，我们将获得对材料和先前制造过程成功的宝贵见解。我们将获得的信息与材料的排列（微观结构）和表面缺陷的存在有关。这两种情况都会影响最终零件的质量，目前，具有大缺陷或不适当微观结构的零件通常在昂贵的制造工艺之后被报废。我们将创建决策系统，与合作伙伴一起使用自动化方法，使用可在工厂中应用的快速技术来识别和量化微观结构、缺陷尺寸及其在零件表面上的发生率。根据这些特征，机器主导的决策将驱动处理策略。从该步骤中提取的信息将反馈到电化学喷射系统，以实现有针对性的返工。在这里，通过将给定部件上的缺陷位置和尺寸提供回新的蚀刻系统，可以通过选择性电化学蚀刻去除表面缺陷。这将使用配备自动蚀刻的机器人进行，并将利用电化学喷射技术的能力来执行不同的材料去除模式并产生不同的表面响应。通过在一个单一的制造步骤中识别、量化和消除零件中的缺陷，预计该系统将能够以相对较低的成本和制造商要求的时间表显著降低高价值零件的报废率。此外，还将提取与缺陷和微观结构有关的信息，并为制造商和操作员提供信息，通过允许特定部件的使用寿命和负载条件来优化效率。因此，该项目旨在实现可持续发展目标，同时为高价值制造商提供改变游戏规则的技术。

The ways in which manufacturers prepare the surfaces of metal high-value parts has changed little over the last 50 years, reliant on bath-based chemical etching in large volumes of corrosive and often toxic acids, followed by manual visual inspection for large defects. This creates large amounts of waste that is difficult to handle, while overly generous safety factors are applied to finished parts as currently not all present defects can be identified and quantified in production line processes. This represents inefficiency firstly in the generation of large volumes of waste, notwithstanding the potential for environmental and user exposure to corrosive and toxic chemicals. Secondly, inefficiency arises from the part lifetimes being significantly shorter and loading conditions lighter than possible, which increases the maintenance intervention.We will create a new set of processes that can etch the same materials by applying targeted electrically charged fluid jets using small volumes of non-hazardous chemicals (electrolytes). These electrolytes will be recirculated and an automatic health monitoring system will be created to ensure appropriate etching response is maintained at the part surface, and ensure resource efficiency. Waste electrolyte will be filtered and metal-containing debris will be returned to the manufacturing supply chain, significantly reducing the volumes of chemicals, and ensuring that the chemicals applied present much reduced risk to the environment and the end user. We will observe generated surfaces during and following etching, and by quantifying aspects of the surface, we will gain a valuable insight into the material and the success of the preceding manufacturing process. The information we will acquire relates to the arrangement of the material (the microstructure) and the presence of surface defects. Both of these can affect the quality of the final part and currently, parts with large defects or inappropriate microstructures are often scrapped, often after expensive manufacturing processes. We will create decision-making systems, using automation approaches with our partners to identify and quantify microstructures, and defect sizes and their occurrence over the part surface using fast techniques that can be applied in the factory. From these characteristics, machine led decision making will drive the processing strategy. Information extracted from this step will be fed back to the electrochemical jet system to enable targeted reworking. Here, surface defects can be removed by selective electrochemical etching, by supplying defect locations and sizes on a given part back to the new etching system. This will be performed using an automated etching equipped robot and will exploit the electrochemical jet technique's capability to perform different modes of material removal and create different surface responses. By identifying, quantifying and removing defects within parts in one single manufacturing step, it is expected that the system will be capable of significantly reducing scrappage rates of high-value parts at a relatively low cost point and on timescales demanded by manufacturers. Furthermore, information pertaining to defects and microstructures will be extracted and provide information to both the manufacturer and the operator, optimising efficiency by allowing part-specific lifetimes and loading conditions. Hence this project with deliver against a sustainability objective while providing a game changing technology for high value manufacturers.