人工智能工程（AIE）软件公司Monolith AI和Imperial College Londonhave received a £500,000 grant from the UK’s innovation agencyInnovate UKto build a new type of AI tool capable of assessing the manufacturability of metal components.
The goal of the project is to revolutionize Computer-Aided Engineering (CAE) within the manufacturing industry through building a new version of ‘explainable AI’ that can provide clear feedback to engineers on why a part may not be manufacturable.
“CAE has done a fantastic job advancing component manufacturing, but there are still many areas where physical simulations still cannot capture the true complexity of components,” said Dr Richard Ahlfeld, CEO and Founder of Monolith AI. “Large engineering companies collect a lot of data when assessing manufacturability and our goal is to make that data work to their advantage.
“This latest funding will allow us to explore this possibility and drive not only the automotive industry, but other sectors, forwards.”
AI-driven 3D printing
Over the past year, substantial progress has been made in the development of machine learning (ML) and AI-driven 3D printing technologies. In fact, AI was named alongside 3D printing, green hydrogen, and autonomous sensors in勒克斯研究’stop12 emerging technologies to watchin 2021, and more recently has been projected to continue to play a key role over the next year by additive manufacturing leaders sharing their2022 3D printing trends.
AI software firmOqton, nowacquired by 3D printer manufacturer 3D Systems, is one of those leading the charge in this field. ItsML and AI-powered software platform能够通过简化生产工作流程来自动化，加速和优化制造公司的吞吐量。
金属和复合3D打印机制造商标记has also embraced AI with the launch of itsAI-based Blacksmith softwarefor use with its X7 3D printer. The software deploys a patented scanning algorithm that measures the precision of parts as they are being printed and collects data to improve the quality of future jobs.
在过去的一年中，3D打印数据专家Senvolbegin developing an具有“其他功能”的ML软件解决美国国防部’s(DoD) production needs, and researchers atOak Ridge National Laboratory(ORNL) unveil theirPeregrine AI-driven real-time monitoring software他们声称这可能会将系统变成“自我校正机器”。
在其他地方，软件开发人员Autodesk已经成为一个founding partner of the nFrontier Emerging Technology Center, a dynamic lab environment seeking tointegrate the “Emerging Eight Technologies”，其中AI是一个，在一个屋顶下。Fraunhofer ILThas also recently leveraged the benefits of AI to develop a 3D printed sensor system capable of intelligently maintaining train components, calledSenseTrAIn.
评估零件的制造性
With the Innovate UK grant, Monolith AI and Imperial College London will work with a cluster of industrial partners to build their novel AI tool over the next 18 months. By the end of the project, the partners hope to have developed an AI tool that will be able to assess if metal components are manufacturable and, if they are not, be capable of explaining why this is the case.
从本质上说,该项目将寻求建立的capabilities of current CAE simulations to help manufacturers not only predict whether a part can be successfully manufactured or not, but to assess the simulation results through ‘explainable AI.’
项目负责人乔尔·亨利（JoëlHenry）博士说：“知道一扇门是不够的。”“您需要了解原因，甚至更重要的是如何更改设计和操作条件以使其可制造。”
Once built, it is hoped the AI tool will be able to provide clear feedback to engineers on how it arrived at its conclusions in order to remove what the project partners call the ‘black box’ dilemma. The partners also hope to streamline the manufacturing process by leveraging AI learnings from what could be manufactured in the past to predict what would be best for new components and provide a new competitive advantage to high-volume manufacturers.
Using the AI tool, engineers could potentially build expert simulations based on repetitive tasks and historic data, and run complex manufacturability assessments in seconds rather than weeks. This would in turn free up engineering skills for other important tasks within the manufacturing workflow.
关于AI工具与3D打印的潜力，Ahlfeld说：“该技术在3D打印中的一种可能应用是根据CAD文件进行评估，是否可以通过打印设施打印此几何形状。想象一个在线原型网站，您可以在其中上传文件 - 该解决方案可以告诉您是否可以从以前的设计中学到几何形状。
“More, it could even highlight the parts of the geometry that could not be printed and explain why.”
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特色图片显示Dr Richard Ahlfeld, CEO and Founder of Monolith AI. Photo via Monolith AI.
