Inside-out: Statistical methods for Computed Tomography validation of complex structures in Additive Layer Manufacturing

增材层制造（ALM）是一种“3D打印”技术，通过逐层添加材料，直接从数字设计数据开发产品。它被广泛认为具有巨大的前景，特别是因为它能够经济有效地响应不断变化的客户需求，并且能够创建具有复杂内部结构的对象。目前，阻碍ALM的一个主要困难是确定数字化设计在多大程度上被正确实现的问题：直接验证通常涉及使用计算机断层扫描（CT）对单个制造对象进行冗长的分析，这往往会削弱ALM在一般用途上的优势。本项目的目的是探索使质量保证过程更迅速地进行的方法。这项调查将由华威大学的工程师和统计学家密切合作，使用包括随机场、错误发现率方法和随机几何思想在内的统计技术进行。

Additive layer Manufacturing (ALM) is a "3D printing" technique which develops products directly from their digital design data by the layer-wise addition of material. It is widely regarded as having great promise, especially for its capabilities to respond cost-effectively to changing customer demand and its ability to create objects with complex internal structure. At present a major difficulty holding back ALM is the problem of determining the extent to which the digital design has been correctly realized by the process: direct verification typically involves lengthy analysis of individual manufactured objects using Computed Tomography (CT) scans, tending to vitiate the advantages of ALM for general purposes. The purpose of this project is to explore methods by which this quality assurance process may be carried out more rapidly. The investigation will be carried out by a close collaboration between engineers and statisticians at Warwick using statistical techniques including random fields, false discovery rate methods, and ideas from stochastic geometry.