Multi-objective optimization of DLP 3D printing for dental application: a Taguchi-gray approach to enhancing efficiency, accuracy and strength
Source abstract
Abstract
Purpose Dental schools and dental laboratories can access entry-level Digital Light Processing (DLP) three-dimensional (3D) printers at low cost but are still not able to achieve print efficiency, dimensional accuracy and mechanical strength. This study aims to enhance these metrics of performance using multi-objective process parameter optimization for dental applications. Design/methodology/approach A Taguchi L16 (44) orthogonal array was used to evaluate four key parameters: layer height (0.02–0.1 mm), bottom layer count (4–10), exposure time (5–12.5 s) and bottom exposure time (20–35 s), with three replications per run. Gray Relational Analysis consolidated three performance metrics: building time, dimensional accuracy and compressive strength, into a single Gray Relational Grade. Dimensional deviation was analyzed using Python scripts in Jupyter Notebook to compare original and scanned STL files and CloudCompare software for visual alignment. Scanning was conducted with a MEDIT T310 scanner using Medit Scan for Labs software. Findings The optimal parameters were: layer height 0.02 mm, bottom layer count 4, exposure time 12.5 s and bottom exposure time 35 s. Experimental validation showed improvements in building time, dimensional accuracy and compressive strength. Analysis of variance determined layer height and exposure time as the most important parameters, contributing 43.79% and 38.92% to total variation, respectively, and bottom layer count and bottom exposure time contributing 9.43% and 6.78%. Originality/value The present research offers a structured multiresponse optimization method for enhancing the quality of dental parts produced with entry-level DLP 3D printers. It also highlights the practicable worth of statistical design of experiments in overcoming low-cost equipment restrictions, as well as ease of application in broader utilizations in clinics and academic institutions.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Additive Manufacturing and 3D Printing Technologies · Dental materials and restorations · 3D Printing in Biomedical Research
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
National Taipei University of Technology Graduate Institute of Manufacturing Technology, , Taipei City, , and Politeknik Perkapalan Negeri Surabaya, Surabaya, Indonesia
National Yang Ming Chiao Tung University Department of Dentistry, , Hsinchu, , and Department of Stomatology, Taipei City Hospital Yangming Branch, Taipei City, Taiwan
Gdansk University of Technology Faculty of Mechanical Engineering and Ship Technology, , Gdańsk,
Czech Technical University in Prague Faculty of Mechanical Engineering, , Prague,
National Taipei University of Technology Department of Mechanical Engineering, , Taipei City, , and High-Value Biomaterials Research and Commercialization Center, National Taipei University of Technology, Taipei City, Taiwan
Flinders University College of Science and Engineering, , Adelaide, , and Department of Mechanical Engineering, Auckland University of Technology, Auckland, New Zealand
Funding
National Science and Technology Council · National Taipei University of Technology and Gdańsk University of Technology
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