Sequential process optimization for a digital light processing system to minimize trial and error
Jae Won Choi, Gyeong-Ji Kim, Sukjoon Hong and 3 more
Scientific Reports · 2022
doi:10.1038/s41598-022-17841-5 (opens in a new tab)
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Abstract
Abstract In additive manufacturing, logical and efficient workflow optimization enables successful production and reduces cost and time. These attempts are essential for preventing fabrication problems from various causes. However, quantitative analysis and integrated management studies of fabrication issues using a digital light processing (DLP) system are insufficient. Therefore, an efficient optimization method is required to apply several materials and extend the application of the DLP system. This study proposes a sequential process optimization (SPO) to manage the initial adhesion, recoating, and exposure energy. The photopolymerization characteristics and viscosity of the photocurable resin were quantitatively analyzed through process conditions such as build plate speed, layer thickness, and exposure time. The ability of the proposed SPO was confirmed by fabricating an evaluation model using a biocompatible resin. Furthermore, the biocompatibility of the developed resin was verified through experiments. The existing DLP process requires several trials and errors in process optimization. Therefore, the fabrication results are different depending on the operator’s know-how. The use of the proposed SPO enables a systematic approach for optimizing the process conditions of a DLP system. As a result, the DLP system is expected to be more utilized.
Abstract licence: CC BY-NC-ND
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