Metal ALM Process Parameter Optimisation - MALM-PPO

金属 ALM 工艺参数优化 - MALM-PPO

• 批准号: 10039714
• 金额: $ 2.29万
• 依托单位: THE PLASTIC ECONOMY LTD
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2022
• 资助国家: 英国
• 起止时间: 2022 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10039714
• 关键词: Metal; ALM; Process; Parameter; Optimisation

Metal additive manufacturing is the process of building up parts in a layerwise process, rather than machining them from initial homogeneous bulk material. By selectively adjusting the machine parameters it is possible to include multiple material properties within a single part, enabling a wider range of more optimised designs than has previously been possible. There is an ever-expanding range of Additive processes and materials, enabling totally new performing parts that are lighter and have novel functions.Additive Flow is the leading software provider for multi-property optimisation and has the capability of generating new ways of manufacturing with multi-properties, and multiple process parameters. This is a fresh new area for growth within engineering in the UK and internationally. In order to unlock the potential of this multi-property optimisation, new ways of testing and gathering data for components that have multiple material properties are needed.In collaboration with the National Physical Laboratory a series of multi-property components will be created which will then be tested and the data will be fed back into the existing software that will improve engineering performance and cost savings for manufacturing. Additional benefits include reducing complexity for users within a multi-scale and multi-disciplinary engineering design space increasing accessibility and adoption of new technologies.Additive Flow's optimisation software determines trade-offs between manufacturing speed and cost against the function and performance of the final part. This can allow more novel parts to be produced quicker and more cost-effectively, enabling greater exploitation of the benefits of AM. However, many of the resulting designs result in inhomogeneous material for which accurate material property data is lacking. The lack of data has resulted in sub-optimal optimisation due to the need to be sufficiently cautious to avoid part failure and subsequently the certification is also expensive.This project will take approaches to measure and evaluate the physical dynamic material properties of heterogeneous structures and use this data to validate processing parameters predicted by the digital simulation. Since surface roughness is a major influencing factor for fatigue, different parameters will be explored to purposely exhibit target varying fatigue values enabling AM to take a major step towards controlling fatigue.This has benefits to the development of the UK industry, where the solution would greatly improve design optimisation processes and have positive economic, social, and environmental implications because material wastage is minimised and process failure is avoided.

金属增材制造是在分层过程中构建零件的过程，而不是从初始均匀的散装材料加工它们。通过选择性地调整机器参数，可以在单个零件中包含多种材料特性，从而实现比以前更广泛的优化设计。增材工艺和材料的范围不断扩大，使全新的性能部件更轻，具有新的功能。Additive Flow是多属性优化的领先软件供应商，有能力产生具有多属性和多工艺参数的新制造方法。这是英国和国际工程领域的一个新的增长领域。为了释放这种多属性优化的潜力，需要为具有多种材料属性的组件提供新的测试和收集数据的方法。与国家物理实验室合作，将创建一系列多属性组件，然后对其进行测试，并将数据反馈到现有的软件中，以提高工程性能并节省制造成本。其他好处包括在多尺度和多学科的工程设计空间内降低用户的复杂性，增加新技术的可访问性和采用性。Additive Flow的优化软件确定制造速度和成本与最终零件的功能和性能之间的权衡。这可以使更多的新部件更快，更经济地生产，从而更好地利用AM的优势。然而，许多由此产生的设计导致材料不均匀，缺乏准确的材料特性数据。数据的缺乏导致了次优优化，因为需要足够谨慎以避免零件故障，随后的认证也很昂贵。该项目将采取措施测量和评估异质结构的物理动态材料特性，并使用这些数据来验证数字模拟预测的工艺参数。由于表面粗糙度是疲劳的主要影响因素，因此将探索不同的参数，有目的地显示目标变化的疲劳值，使AM朝着控制疲劳迈出重要一步。这有利于英国行业的发展，该解决方案将大大改善设计优化过程，并具有积极的经济，社会，和环境影响，因为材料浪费最小化并且避免了工艺故障。