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Optimised machining strategies for near net shape components

近净形部件的优化加工策略

基本信息

批准号：
2902143
负责人：
金额：
--
依托单位：
University of Sheffield
依托单位国家：
英国
项目类别：
Studentship
财政年份：
2023
资助国家：
英国
起止时间：
2023 至无数据
项目状态：
未结题

来源：
https://gtr.ukri.org/projects?ref=studentship-2902143
关键词：
Optimised machining strategies near net

项目摘要

In order for the high value manufacturing sector to support the global drive towards net zero, manufacturers need to rapidly implement a step change in how they can supply products in a more responsible and sustainable way. Current industry-ready solutions include providing parts in near-net forms such that minimal further machining processes are required; provision of material that contains 100% recycled feedstock; and implementing the use of more adaptable systems such as robotics or parallel kinematic machining centres. However, these solutions provide their own challenges when considered as a complete package when attempting to meet stringent sector requirements in terms of quality, cost and rate. When combined with sustainability targets it may well have to be accepted that current state of the art solutions may in fact lead to decreases in productivity. The current class of commercially available simulation models are not keeping pace with the developments of tooling design and machining strategies. Therefore the focus of this PhD project will be to advance our simulation capability taking into account inherent process variability such as material condition of supply, cutting tool geometry and form error, machine tool kinematics/dynamics, and part fixturing, to provide solutions that can be directly demonstrated on a machine centre.

为了让高价值制造业支持全球实现净零排放的努力，制造商需要迅速实施一个步骤，改变他们如何以更负责任和可持续的方式提供产品。目前的工业就绪解决方案包括提供近净形式的零件，这样就需要最少的进一步加工过程;提供含有100%回收原料的材料;以及使用更具适应性的系统，如机器人或并联运动加工中心。然而，这些解决方案在试图满足质量、成本和速率方面的严格行业要求时，作为一个完整的解决方案来考虑时，也会带来自身的挑战。当与可持续性目标相结合时，很可能不得不承认，目前最先进的解决方案实际上可能导致生产力下降。目前市场上的仿真模型已经跟不上模具设计和加工策略的发展。因此，这个博士项目的重点将是提高我们的仿真能力，同时考虑到固有的过程可变性，如材料供应条件，刀具几何形状和形状误差，机床运动学/动力学和零件夹具，以提供可以直接在加工中心上演示的解决方案。