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Micro Milling Process Optimization (Micro-O)

微铣削工艺优化 (Micro-O)

基本信息

批准号：
262399201
负责人：
Professor Dr.-Ing. Eckart Uhlmann
金额：
--
依托单位：
Fachgebiet Werkzeugmaschinen und Fertigungstechnik
依托单位国家：
德国
项目类别：
Research Grants
财政年份：
2014
资助国家：
德国
起止时间：
2013-12-31 至 2020-12-31
项目状态：
已结题

来源：
https://gepris.dfg.de/gepris/projekt/262399201?language=en
关键词：
Micro Milling Process Optimization

项目摘要

The research project aims at improving the micro-production chain to generate knowledge about related process stages, including potential improvements of productivity and quality. It is intended to deepen the use of simulation methods in process optimisation. First, the process planning will be focussed on the analysis of significant impact factors in micro-machining and on the reduction of processing times. Secondly, the process and machine setup and the micro-machining itself will be investigated focusing on its improvement by using enhanced monitoring and simulation techniques. Finally, the part control will be improved regarding measurement methodologies to effectively and accurately provide part information. In order to consider all these different aspects and their impact on the micro-milling chain, the partners will join their forces and bring their specific knowledge and experience from different disciplines for jointly contributing to the improvement of micro-milling processes based on their particular expertise. The knowledge and results gained in the fundamental research activities and through the planned cooperation will considerably improve the competitiveness of the research partners together with the possibilities to spread this knowledge and technology to support micro-manufacturing industries in both countries to introduce novel machining processes. This will help micro-manufacturing and especially the mould making industry to reach superior surface quality, tight machining tolerance, shorter machining time with less wear and tear on their machines and tooling. In summary, this project focuses on the development of knowledge and solutions for innovating critical aspects of micro-milling processes, concentrating on the production of moulds for micro-featured products, targeting the improvement of productivity, efficiency and on the advancement of strategies for optimising costs and quality. The envisaged research project faces some important challenges described in the scope and framework of the BRAGECRIM and contributes to the objectives expressed in this research initiative and the interests of Brazil and Germany to improve competitiveness and the level in production technology.

该研究项目旨在改进微型生产链，以产生有关工艺阶段的知识，包括生产力和质量的潜在改进。它旨在深化模拟方法在工艺优化中的应用。首先，工艺规划将侧重于分析微加工中的重要影响因素和减少加工时间。其次，工艺和机器设置和微加工本身将进行调查，重点是通过使用增强的监控和仿真技术来改善。最后，将在测量方法方面改进零件控制，以有效和准确地提供零件信息。为了考虑所有这些不同的方面及其对微铣削链的影响，合作伙伴将联合他们的力量，并带来他们来自不同学科的特定知识和经验，共同为基于他们特定专业知识的微铣削工艺的改进做出贡献。在基础研究活动中获得的知识和成果以及通过计划中的合作将大大提高研究伙伴的竞争力，并有可能传播这种知识和技术，以支持两国的微型制造业引入新的加工工艺。这将有助于微型制造业，特别是模具制造业，以达到上级表面质量，严格的加工公差，更短的加工时间，更少的磨损和撕裂的机器和工具。总之，该项目的重点是开发知识和解决方案，以创新微铣削工艺的关键方面，专注于微特征产品的模具生产，旨在提高生产力，效率和优化成本和质量的战略。设想的研究项目面临BRAGECRIM范围和框架中所述的一些重要挑战，并有助于实现这一研究倡议中所表达的目标以及巴西和德国提高竞争力和生产技术水平的利益。

项目成果

期刊论文数量（8）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

In-situ magnetic inspection of the part fixture and the residual stress in micromilled hot-work tool steel

微铣削热作工具钢零件夹具和残余应力的原位磁力检测

DOI：
10.1016/j.ndteint.2017.05.006
发表时间：
2017
期刊：
Ndt & E International
影响因子：
4.2
作者：
Camposa;del Conte
通讯作者：
del Conte

A method for monitoring and diagnosing the circular trajectory error in micromilling

DOI：
10.1109/tla.2016.7816991
发表时间：
2016-12
期刊：
IEEE Latin America Transactions
影响因子：
1.3
作者：
Bruna Castilho dos Santos;Gabriel de Andrade;E. G. Conte
通讯作者：
Bruna Castilho dos Santos;Gabriel de Andrade;E. G. Conte

Barkhausen Noise Analysis as an Alternative Method to Online Monitoring of Milling Surfaces

DOI：
10.1109/tmag.2016.2514739
发表时间：
2016-01
期刊：
IEEE Transactions on Magnetics
影响因子：
2.1
作者：
Erik Gustavo Del Conte;J. C. Teixeira;M. A. Campos;H. A. Piccolo;D. A. O. Oliva;L. R. Rodrigues
通讯作者：
Erik Gustavo Del Conte;J. C. Teixeira;M. A. Campos;H. A. Piccolo;D. A. O. Oliva;L. R. Rodrigues

A hybrid monitoring-simulation system for contour error prediction on complex surfaces manufacturing