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dc.contributor.authorDenkena, Berend
dc.contributor.authorWichmann, Marcel
dc.contributor.authorMalek, Talash
dc.contributor.authorNguyen, Hai Nam
dc.contributor.authorKato, Makoto
dc.contributor.authorIsshiki, Kaito
dc.contributor.authorKoike, Ryo
dc.contributor.authorKakinuma, Yasuhiro
dc.date.accessioned2024-12-24T19:11:05Z
dc.date.available2024-12-24T19:11:05Z
dc.date.copyright5/21/2024 12:00:00 AM
dc.date.issued2024
dc.identifier.issn1087-1357
dc.identifier.othermanu_146_7_071004.pdf
dc.identifier.urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4303448
dc.description.abstractAdditive and subtractive (Add/Sub) manufacturing processes are increasingly being combined to produce complex parts with unique geometries and properties. However, the design of such combined processes is often challenging as it requires a deep understanding of the interaction between the different processes. On the other hand, digital twin (DT) technology has become a powerful tool in recent years for optimizing manufacturing processes. This article explores the use of the digital twin technology for a holistic process planning of combined additive and subtractive processes. The article describes the integration of laser metal deposition (LMD) and micro-milling prediction models of resulting geometry (width and height), hardness, and surface roughness into the digital twin. This is then used for combined process planning to achieve different target values regarding resulting geometry and surface roughness. For the planning of this combined process chain, further criteria such as tool life, energy, and process time are considered in the optimization, showing the potential for sustainable and efficient production. Sensorless cutting force estimation is also used to detect small cutting forces, with the potential to use this as a soft sensor for roughness estimation. The measured width, height, and roughness as a result of the process parameters suggested by the optimization algorithms showed a mean absolute percentage error (MAPE) of 4, 17, and 16%, respectively.
dc.publisherThe American Society of Mechanical Engineers (ASME)
dc.titleDigital Twin in Process Planning of the Additive and Subtractive Process Chain for Laser Metal Deposition and Micro Milling of Stainless Steel
dc.typeJournal Paper
dc.journal.volume146
dc.journal.issue7
dc.journal.titleJournal of Manufacturing Science and Engineering
dc.identifier.doi10.1115/1.4065415
dc.journal.fristpage71004-1
dc.journal.lastpage71004-11
dc.page11
dc.treeJournal of Manufacturing Science and Engineering:;2024:;volume( 146 ):;issue: 007
dc.contenttypeFulltext


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