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Related Concept Videos

Upsampling01:22

Upsampling

302
Managing signal sampling rates is essential in digital signal processing to maintain signal integrity. A decimated signal, characterized by a reduced frequency range due to its lower sampling rate, can be upsampled by inserting zeros between each sample. This upsampling process expands the original spectrum and introduces repeated spectral replicas at intervals dictated by the new Nyquist frequency. To refine this zero-inserted sequence, it is passed through a lowpass filter with a cutoff...
302

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Related Experiment Video

Updated: Sep 2, 2025

Author Spotlight: Quantitative Characterization of Liquid Photosensitive Bioink Properties for Continuous Digital Light Processing Based Printing
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Sequential process optimization for a digital light processing system to minimize trial and error.

Jae Won Choi1,2, Gyeong-Ji Kim3, Sukjoon Hong2

  • 1Advanced Joining and Additive Manufacturing R&D Department, Korea Institute of Industrial Technology, 113-58, Seohaean-ro, Siheung-si, 15014, Republic of Korea.

Scientific Reports
|August 8, 2022
PubMed
Summary
This summary is machine-generated.

Sequential process optimization (SPO) streamlines digital light processing (DLP) additive manufacturing by analyzing resin properties and optimizing parameters. This reduces errors and enhances DLP system utilization for various materials.

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Area of Science:

  • Additive Manufacturing
  • Materials Science
  • Biotechnology

Background:

  • Workflow optimization is crucial for cost-effective and successful additive manufacturing.
  • Quantitative analysis of fabrication issues in digital light processing (DLP) systems is lacking.
  • Current DLP processes rely heavily on operator expertise, leading to inconsistent results.

Purpose of the Study:

  • To develop an efficient sequential process optimization (SPO) method for DLP systems.
  • To enable the application of diverse materials and expand the use of DLP technology.
  • To systematically manage critical process parameters like initial adhesion, recoating, and exposure energy.

Main Methods:

  • Quantitative analysis of photopolymerization characteristics and resin viscosity.
  • Optimization of process conditions including build plate speed, layer thickness, and exposure time.
  • Fabrication and biocompatibility testing of an evaluation model using a biocompatible resin.

Main Results:

  • The proposed SPO method systematically optimizes DLP process conditions.
  • Successful fabrication of an evaluation model using a biocompatible resin was achieved.
  • The developed resin demonstrated verified biocompatibility.

Conclusions:

  • The sequential process optimization (SPO) offers a systematic approach to DLP process control.
  • This method reduces trial-and-error, operator dependency, and improves fabrication consistency.
  • The optimized DLP system is expected to see increased utilization across various applications.