A ubiquitous healthcare system of 3D printing facilities for making dentures: Application of type-II fuzzy logic

A ubiquitous healthcare (UH) system of multiple 3D printing facilities is established in this study for making dentures. The UH system receives orders from dental clinics, and then distributes the dentures to be printed among 3D printing facilities to save time. Compared with existing systems for si...

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Bibliographic Details
Published in:Digital health Vol. 8; p. 205520762210925
Main Authors: Chiu, Min-Chi, Chen, Tin-Chih Toly
Format: Journal Article
Language:English
Published: London, England SAGE Publications 01.04.2022
Sage Publications Ltd
SAGE Publishing
Subjects:
3-D printers
Case Study
Dentures
Home delivery services
Linear programming
Ubiquitous healthcare
denture
type-II fuzzy logic
3D printing
ISSN:2055-2076, 2055-2076
Online Access:Get full text
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Summary:A ubiquitous healthcare (UH) system of multiple 3D printing facilities is established in this study for making dentures. The UH system receives orders from dental clinics, and then distributes the dentures to be printed among 3D printing facilities to save time. Compared with existing systems for similar purposes, the UH system has two novel features. The first is the consideration of the possibility of reprinting in formulating the plan to avoid replanning. The other is the cooperation with home delivery services that have gradually become popular during the COVID-19 pandemic to save transportation time. The new features are subject to considerable uncertainties. To account for the uncertainties, both printing time and transportation time are modelled using interval type-II trapezoidal fuzzy numbers. Subsequently, an interval type-II fuzzy mixed integer-linear programming (FMILP) model is formulated and optimized to plan the operations of the UH system. A case study has been conducted to illustrate the applicability of the proposed methodology. According to experimental results, the proposed methodology was able to shorten the order fulfillment time by up to 9%.
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ISSN:2055-2076
2055-2076
DOI:10.1177/20552076221092540