Development of advanced part recognition toolkit for automated additive manufacturing post-processing system

增材制造技术（AMT）是一家位于谢菲尔德的增材制造（AM）智能后处理系统制造商。近年来，AMT吸引了数百万磅的投资，用于开发自动表面平滑，脱粉和着色机器。AMT的愿景是创建一个数字化制造系统（DMS），包括智能测量和人工智能控制的后处理模块。该项目旨在将几何测量和机器学习集成到AMT的DMS系统中。AMT需要一个分析工具包来分析各种状态的零件，包括粉末化、去粉末化、未加工、后加工以及各种几何形状和打印方法。这需要研究适当的机器学习算法，能够在真实的时间内识别和分类表面，同时使用有限的计算能力。这种机器学习的任务之一是AM零件表面几何形状的质量控制，涉及内部和难以接近的区域。机器学习将引导DMS每个模块的参数控制。将生成表面处理数据库，用于后处理阶段的智能自动控制。该工艺将允许通过迭代自学习进行平滑，着色，功能涂层或表面形态操作，使其成为AM表面工程和数字制造的改变游戏规则的技术。该工艺将使新一代增材制造部件能够用于现有应用，例如电池/电容器组件、卫星涂层、抗菌医疗组件和新结构纤维的制造。

Additive Manufacturing Technologies (AMT) is a Sheffield based manufacturer of smart post-processing systems for additive manufacturing (AM). During recent years, AMT has attracted multi-million-pound investment for the development of automatic surface smoothing, de-powdering and colouring machines. AMT's vision is to create a Digital Manufacturing System (DMS), involving smart metrology and AI controlled post-processing modules.This project aims to develop geometry measurement and machine learning integration into AMT's DMS system. AMT require an analysis toolkit for parts at various states, including powdered, de-powdered, un-processed, post-processed, as well as various geometries and printing methods. This requires research of appropriate machine learning algorithms able to recognise and categorise the surfaces in real time while using limited computational power. Among the tasks for such machine learning is quality control of the geometry of AM part surfaces, involving internal and difficult-to-access areas.The machine learning will steer the parameter controls for each module of the DMS. Surface processing databases will be generated for smart automated control of post-processing stages. The process will allow smoothing, colouring, functional coating or surface morphology manipulation by iterative self-learning, making it a game-changing technology for AM surface engineering and digital manufacturing. The process will enable a new generation of AM parts to be used in existing applications, e.g. battery/capacitor assemblies, satellite coatings, antimicrobial medical components and creation of new structural fibres.