Prozessoptimierung von Mikrofräsprozessen - BRAGECRIM
Zusammenfassung der Projektergebnisse
The second phase of the Micro-O project was highlighted by the manufacturing of micro-molds for micro-injection molding by applying results to a use case with practical relevance. The project was focused on finding a methodology to concentrate on the significant impact factors with regard to the targeted optimization aim given by the amount of necessary accuracy and productivity. First, influences exerted within the CAM processing were further analyzed. The improvement of tool path planning used the virtual machine, which observes critical movements to avoid critical moments, tests different cutting strategies, illustrates and studies stock removal. A reduction of 16.4 % in machining time tm with a maximum error of errmax = 3 % of an example mold was achieved. Second, the process set-up impact was investigated as well as the truly applied process parameters during machining were optimized. Steps experiments and wall experiments were conducted to evaluate the influence of the cutting parameters on the surface roughness of the mold floor and mold wall. The biggest correlation to the surface roughness Ra, Rz and Rt was found to the spindle speed n. The cutting depth ap showed only a small dependency and the cutting width ae didn’t correlate with the surface roughness. The results were used to find sets of cutting parameters that result in required surface roughness. Afterwards, the tool wear was investigated. Tool wear leads to tool diameter reduction dr, which was the main parameter due to its influence on component tolerance, surface quality, production time tp and costs. The ANOVA method was applied to the full factorial DOE. The results showed that feed per tooth ft, spindle speed n, cutting length lc as well as the interactions between feed per tooth ft and cutting length lc and the interactions between spindle speed n and cutting length lc are significant impact factors for tool wear. A diameter reduction model was found, which is based on linear regression. This allows the prediction of tool diameter reduction dr, which leads to higher surface precision. Furthermore, the conditions for process stability were also investigated. The materials X40CrMoV5-1 as well as X33CrS16 with different stages of hardness were used for the investigation. To evaluate instable milling processes on the KERN Evo, KERN Microtechnik GmbH, Eschenlohe, Germany, the cantilever length needed to be increased from lca = 20 mm to lca = 35 mm for the milling tool with a tool diameter d = 1 mm. The investigation showed clear differences for different hardness stages. Where especially the hardened materials showed an unexpected behavior, with no clear boundary and more stable processes with increasing cutting depth ap. The findings are used for mold machining with demand of high surface quality. The found data will be added to the project library to further enhance the virtual machine. To predict and enhance part quality a FE-simulation of the demolding process was conducted. A numerical model has been found to determine the demolding forces Fd. The influence of surface roughness on the mold wall and mold structures with different wall angles αw were investigated. The influence of surface roughness is considered in the simulation by a regression equation, which adapts simulated results. A difference in wall angle αw showed an impact on the demolding force Fd. For structures with angled walls less demolding force Fd was needed to demold the part. The results are used for future machining process and design of mold cavities to minimize demolding forces Fd. Finally, the improvements and methodologies were applied in real cases, such as the ones exemplified in section 2.5, demonstrating that results obtained within this project can be transferred to industry in distinct levels according to individual applications, which will have own specific challenges. During the four-year period of the Micro-O project, intensive technical discussions have been realized, which resulted in advances in the development of the project concepts and in the implementation of partial solutions. Such strong research efforts have been directly transferred to several publications prepared afterwards. Within the project, 20 joint publications have been achieved (10 in Journals and 10 in Conferences). The project was also marked by the intense exchange of personnel between the Brazilian and German partner universities, guaranteeing an important flow of information and knowledge. Therefore, this project contributed to the production of practical knowledge in addition to the formation of qualified researchers.
Projektbezogene Publikationen (Auswahl)
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A hybrid monitoring-simulation system for contour error prediction on complex surfaces manufacturing. International Journal of Advanced Manufacturing Technology, 77(1), 2015, pp. 321 – 329
Del Conte, E. G.; Schützer, K.; Abackerli, A. J.
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Automatisierte Qualitätskontrolle. wt Werkstattstechnik online, 105(6), 2015, pp. 384 – 389
Uhlmann, E.; Kuche, Y.; Oberschmidt, D.; Löwenstein, L.; Wiemann, S.
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Schneidkantenpräparation von VHM-Mikrofräsern - Vergleich unterschiedlicher Feinbearbeitungsverfahren. wt Werkstattstechnik online, 105(11/12), 2015, pp. 805 – 811
Uhlmann, E.; Oberschmidt, D.; Löwenstein, A.; Polte, M.; Winker, I.
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A method for monitoring and diagnosing the circular trajectory error in micromilling. Revista IEEE América Latina, 14, 2016, pp. 4,639 – 4,645
Dos Santos, B. C.; De Andrade, G.; Del Conte, E. G.
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Barkhausen noise analysis as an alternative method to online monitoring of milling surfaces. IEEE Transactions on magnetics, 52(5), 2016, pp. 1 – 4
Del Conte, E.; Teixeira, J. C.; Alberteris, C. M.; Piccolo, H.; Oliva, D.; Rodrigues, L.
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Automatic design and synthesis of control for a plug and play active vibration control module. Journal of vibration and control, 2017
Uhlmann, E.; Kushwaha, S.; Mewis, J.; Richarz, S.
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In-situ magnetic inspection of the part fixture and the residual stress in micro-milled hot-work tool steel. International Journal of Nondestructive Testing and Evaluation, 90, 2017, pp. 33 – 38
Camposa, M. A.; Mewis, J.; del Conte, E. G.
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Simulation tool for prediction of cutting forces and surface quality of micro-milling processes. International Journal of Advanced Manufacturing Technology, 99, 2018, pp. 225 – 232
Schützer, K., da Silva de Luca Ramos, L. W., Mewis, J.
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Tool wear modelling using micro tool diameter reduction for micro-end-milling of tool steel H13. International Journal of Advanced Manufacturing Technology, 105, 2019, pp. 2,531 – 2,542
Manso, C. S.; Thom, S.; Uhlmann, E.; De Assis, C. L. F.; Del Conte, E. G.
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Investigation of micro milled tool steel H13 using tungsten carbide micro-end mills. International Journal of Advanced Manufacturing Technology, 107, 2020, pp. 1,179 – 1,189
Manso, C. S.; Thom, S.; Uhlmann, E.; De Assis, C. L. F.; Del Conte, E. G.
