A4 Vertaisarvioitu artikkeli konferenssijulkaisussa
Towards a Framework for Self-Evolving Products in Additive Manufacturing
Tekijät: Savolainen, Jyrki; Urbani, Michele; Piili, Heidi
Toimittaja: Sgarbossa, Fabio; Panagou, Sotirios; Alfnes, Erlend; Dolgui, Alexandre; Ivanov, Dmitry; Battini, Daria
Konferenssin vakiintunut nimi: IFAC Conference on Manufacturing Modelling, Management and Control
Kustantaja: Elsevier B.V.
Julkaisuvuosi: 2025
Lehti:: IFAC-PapersOnLine
Kokoomateoksen nimi: 11th IFAC Conference on Manufacturing Modelling, Management and Control MIM 2025
Vuosikerta: 59
Numero: 10
Aloitussivu: 1277
Lopetussivu: 1282
ISSN: 2405-8971
eISSN: 2405-8963
DOI: https://doi.org/10.1016/j.ifacol.2025.09.215
Verkko-osoite: https://doi.org/10.1016/j.ifacol.2025.09.215
Rinnakkaistallenteen osoite: https://research.utu.fi/converis/portal/detail/Publication/504915978
In critical industrial applications, enhancing existing custom-designed products throughout their life cycles is crucial for improving user value while managing the costs of continuous design iterations. Additive manufacturing has demonstrated significant improvements in product performance through optimized designs, but implementing these improvements in scale requires excessive design efforts. In this paper, we address this gap by presenting a digital twin (DT)-based product design framework for additively manufactured parts that makes the design of the physical parts independently to adapt into their industrial application environments. The methodology is based on efficiently utilizing data in the intersection of application-specific DT model and the CAD (Computer-Aided Design). It is proposed that with the smart utilization of Evolutionary Algorithms (EA), most of the manual labor involved in drafting performance-improving revisions of design of part geometry could be eliminated. The proposition is evaluated from the business model point of view highlighting the potential for novel, mutually beneficial supplier-customer relationships in advanced industrial equipment solutions.
Ladattava julkaisu This is an electronic reprint of the original article. |  |
Julkaisussa olevat rahoitustiedot:
This work was supported by The Strategic Research Council (SRC) at the Academy of Finland under Grant 313396
(Manufacturing 4.0), and by the Academy of Finland under Grant 325003 (ReGold-AM).
