Scalable AM Rule Creation & Dissemination (SAMRCD)

可扩展的 AM 规则创建

• 批准号: 10002048
• 金额: $ 180.49万
• 依托单位: AUTHENTISE
• 依托单位国家: 英国
• 项目类别: Collaborative R&D
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=10002048
• 关键词: Scalable; AM; Rule; Creation; Dissemination

Metals production, from mining ore through manufacturing parts, accounts for 7% of global energy use. While metal additive manufacturing (AM) has been promoted as a way to help us reduce our carbon footprint, this has not been well demonstrated with clear and complete information. Furthermore, there lacks a comprehensive comparison of energy consumption by the different AM processes. To optimize when, where, which, and how to implement AM, we must be able to assess its environmental impact and compare this to conventional manufacturing processes like CNC Machining.For effective analysis, we must consider the whole manufacturing lifecycle. This includes all the steps from feedstock manufacturing, printing, post-processing, and any material reuse along the way. Continuing studies and analysis will only achieve so much, the need to implement digital tools that can monitor, analyse, predict and alert a range of impact and deviations in standard operating procedures is fundamental to continue the maturing of a manufacturing process which has already had an impact on material efficiency. The process of AM is sensitive to many factors, and while AM opens many design efficiencies, such as part consolidation, the energy impact from materials requiring conditioning, not meeting required standards and the time taken to develop build parameters to ensure build by build stability is key to reducing energy use. A print failure has tremendous energy impact. A CNC machine will use 23 KWh per Kg of material removed, with a high rate of success in part quality. Compared to AM and L-PBF which uses on average 80.5 KWh per Kg of material added. Part acceptance rates for L-PBF are lower than a CNC Machine. For every 100kg of material processed, assuming an equal 10% part-failure rate, 805 KWh of energy would be wasted versus the 230KWh for CNC.The development of the tools proposed within the SAMCRD project would make a profound impact in energy reduction and accelerate additive manufacturing as a viable sustainable production process as part of the UK's manufacturing capabilities.

金属生产，从开采矿石到制造零件，占全球能源消耗的7%。虽然金属增材制造（AM）已被推广为帮助我们减少碳足迹的一种方式，但这并没有得到清晰完整的信息的充分证明。此外，缺乏对不同AM工艺的能量消耗的全面比较。为了优化何时、何地、何种以及如何实施增材制造，我们必须能够评估其对环境的影响，并将其与CNC加工等传统制造工艺进行比较。为了进行有效的分析，我们必须考虑整个制造生命周期。这包括从原料制造、印刷、后处理到任何材料再利用的所有步骤。持续的研究和分析只能达到这么多，需要实施数字化工具，可以监测，分析，预测和警告标准操作程序中的一系列影响和偏差，这对于继续成熟已经对材料效率产生影响的制造过程至关重要。AM的过程对许多因素都很敏感，虽然AM带来了许多设计效率，例如零件合并、需要调节的材料对能源的影响、不满足所需标准以及开发构建参数以确保逐个构建稳定性所需的时间是减少能源使用的关键。打印故障会产生巨大的能量影响。数控机床每去除一公斤材料将消耗23千瓦时，零件质量的成功率很高。与AM和L-PBF相比，其平均使用80.5KWh/Kg添加的材料。L-PBF的零件接受率低于CNC机床。对于每100公斤的材料加工，假设10%的零件故障率相等，805千瓦时的能源将被浪费，而CNC为230千瓦时。SAMCRD项目中提出的工具的开发将对能源减少产生深远的影响，并加速增材制造作为英国制造能力的一部分的可行的可持续生产工艺。