Research and Development of a Smart Filament Management Platform
Research and Development of a Smart Filament Management Platform
批准号:
2442369
负责人:
金额:
$0.0万
依托单位:
依托单位国家:
英国
项目类别:
Studentship
财政年份:
2020
资助国家:
英国
项目状态:
已结题
起止时间:
2020 至 --
中文摘要
先前的研究结果表明,虽然FDM 3D打印变得越来越容易获得,但存在一些技术问题以及偏离正确的操作和维护程序,这些问题通常会导致打印失败或机器损坏。尽管该技术已被证明在打印农场场景中有效,但在此类农场的自动化方面进展甚微。虽然一些带有打印弹出机构或带式床与多材料附件相结合的打印机可以在没有人为干预的情况下连续使用,但目前还没有针对专门存储、保存、跟踪和自动分配灯丝到几台打印机的解决方案。尽管如此,这种设备将有助于实现连续生产,而不需要人类在生产现场。在之前的研究中已经注意到,具有3D打印能力的学校和大学研讨会,通常是FDM类型,经常努力保持打印机连续工作。这在很大程度上是由于操作人员的错误,但也可能导致严重的停机时间或零件质量差,以及对工艺的总体不满。如果这个过程更加自动化,就会减少人为错误的空间,因为最终用户和机器之间的交互被最小化了。这种系统的好处是可以在教育、专业和商业环境中可靠地使用FDM 3D打印机,并且具有更高的效率和质量。需要进一步研究这项技术的自动化如何影响各个部门。此外,分析可用的FDM打印机的各种品牌和型号以及它们如何与线材加工系统相互作用是很重要的。最后,识别和解决材料浪费问题至关重要,这将提高效率并降低成本。主要项目研究显示了其他几个与灯丝相关的问题,这些问题经常导致材料浪费或损坏机器或打印部件。这个博士学位的目标是进一步探索这些问题和潜在的解决方案,就像在主要项目中提出的那样。最初开发的系统很好地证明了同时在多台打印机之间进行自动灯丝加工的可能性。这种上料、下料、切割和验证细丝的机制是整个细丝管理系统的重要组成部分。最终的系统将包括额外的组件,以保持灯丝质量,跟踪灯丝的使用,允许文件处理和打印机控制以及其他旨在自动化过程的解决方案。博士的研究将集中于解决持续生产和质量改进的最普遍的障碍。识别FDM 3D打印过程中的弱点和潜在原因将允许进行改进,以实现在各种环境下的连续制造。
英文摘要
Previous findings show that while FDM 3D printing is becoming increasingly more accessible, there are several technical issues and deviations from correct operating and maintenance procedures which can often lead to print failures or damage to the machine. Although the technology has been proven to work in print farm scenarios, little advancement has been made in terms of automation of such farms. While some printers with print ejection mechanism or belt type bed coupled with a multimaterial accessory can be used continuously without human intervention, there are no solutions yet aimed at specifically storing, preserving, tracking and distributing filament it to several printers automatically. Nevertheless, such a device would contribute towards enabling continuous manufacturing without the need for human presence at manufacturing site. It has been noted in previous research that school and university workshops with 3D printing capability, which is typically of the FDM type, often struggle with keeping printers working continuously. This is largely due to operator error but can cause significant downtime or poor part quality as well as an overall dissatisfaction with the process. If the process were to be more automated, there would be less room for human error since the interaction between the end user and the machine is minimised. The benefit of such system would be the possibility of reliably using FDM 3D printers in educational, professional and commercial settings with much greater efficiency and quality. Further research needs to be conducted into how automation of this technology could impact various sectors. In addition, it is important to analyse the various makes and models of available FDM printers and how these would interact with filament processing system. Finally, it is vital to identify and resolve issues of material wastage which would boost efficiency and reduce cost. The Major Project research has shown several other filament related issues that often lead to material wastage or damage to machine or printed part. The goal of this PhD would be to further explore such issues and potential solutions like those proposed in the Major Project. The system developed initially is a good demonstrator of the possibility to automate filament processing to and from several printers at once. Such mechanism of loading, unloading, cutting and verifying filament could be a vital part of an overall system of filament management. The final system would include additional components to preserve filament qualities, track filament usage, allow for file processing and printer control and other solutions aimed at automating the process. The research of the PhD would focus on solving the most prevalent roadblocks to continuous production and quality improvement. Identification of the weakest points and potential causes in the process of FDM 3D printing would allow to make improvements to enable continuous manufacturing in various environments.
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水稻边界发育缺陷突变体abnormal boundary development(abd)的基因克隆与功能分析
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批准号:32070202
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项目类别:面上项目
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资助金额:58.0万元
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批准年份:2020
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负责人:汪泉
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依托单位:
Development of a Linear Stochastic Model for Wind Field Reconstruction from Limited Measurement Data
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批准号:--
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项目类别:--
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资助金额:40万元
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批准年份:2020
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负责人:Vikrant Gupta
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依托单位: