Using 3D-printing in disaster response: The two-stage stochastic 3D-printing knapsack problem

Tönissen, Denise; Schlicher, Loe

doi:10.1016/j.cor.2021.105356

Cited by 10 publications

(3 citation statements)

References 61 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Many further (case) studies have proven that AM already is a very useful and feasible way to improve disaster relief and humanitarian aid (James and Gilman, 2015;James and James, 2016;Saripalle et al, 2016;Rodríguez-Espíndola et al, 2020;Tönissen and Schlicher, 2021) and that vulnerable communities in particular can be helped by AM-supported disaster relief (Yu and Khan, 2015;Mohammed et al, 2018b). Examples of additive manufactured goods in humanitarian aid are spare parts for hospital equipment (Saripalle et al, 2016) and pipe fittings for water supply (Mohammed et al, 2018b).…”

Section: Sdg : No Povertymentioning

confidence: 99%

Putting 3D printing to good use—Additive Manufacturing and the Sustainable Development Goals

2023

View full text Add to dashboard Cite

Additive Manufacturing (AM), often referred to as 3D printing, is expected to have a high impact on the manufacturing industry as well as on society. The inherent characteristics of AM make it possible to help solve global challenges, which can be explored in reference to the 17 Sustainable Development Goals (SDGs) of the United Nations. This is the first paper that examines the connection of AM and the 17 SDGs through a literature review. In this work, it is outlined which SDGs have a high, moderate or low potential to be fostered by AM. The SDGs are introduced and corresponding studies relevant to the respective SDG are presented. It is found that six out of 17 SDGs have high potential to be promoted by AM. These are SDG 1 (No poverty), SDG 3 (Good Health and Wellbeing), SDG 4 (Quality Education), SDG 9 (Industry, Innovation, and Infrastructure), SDG 12 (Responsible Consumption and Production), and SDG 14 (Life below Water). Furthermore, two SDGs have been identified that have moderate potential to be cultivated by AM. These are SDG 7 (Affordable and Clean Energy) and SDG 10 (Reduced Inequalities).

show abstract

Section: Sdg : No Povertymentioning

confidence: 99%

Putting 3D printing to good use—Additive Manufacturing and the Sustainable Development Goals

2023

View full text Add to dashboard Cite

show abstract

“…3D printers have been discussed for their potential to reduce logistics, material waste, and overproduction, as well as to increase product lifespan and enable on-demand production (Khosravani and Reinicke, 2020;Molitch-Hou, 2020). Especially in light of the COVID-19 pandemic, 3D printing has emerged as a novel approach for communities to rapidly respond to disasters and crises, satisfying global and local needs (Dartnell and Kish, 2021;Newman, 2020;Tönissen and Schlicher, 2021). Further, 3D printing facilitates recycling processes for certain materials, such as lithium batteries and metal components (Berger, 2019;Giurco et al, 2014), hence promoting end-of-life systems and supporting localisation (Ralph, 2021).…”

Section: D Printers As Benchmarks For Degrowth and Localisationmentioning

confidence: 99%

Tracing sustainable production from a degrowth and localisation perspective: A case of 3D printers

Priavolou

Troullaki

Tsiouris

et al. 2022

Journal of Cleaner Production

View full text Add to dashboard Cite

“…The findings of the research well demonstrate the effective use of AM capacities in responding to social crises and managing potential disasters. Other studies by Tönissen and Schlicher (2020) and Tatham et al (2015) examined the potential of AM technology to support preparedness and rapid response to a natural disaster or complex emergency and showed how AM potential improves the efficiency and effectiveness of humanitarian logistics operations. In other studies, Corsini et al (2020), Rodríguez-Espíndola et al (2020) and Wankmüller and Reiner (2020) examined the effects of AM in helping to manage humanitarian crises.…”

Section: Literature Reviewmentioning

confidence: 99%

Analysis of optimized response time in a new disaster management model by applying metaheuristic and exact methods

Mahmoodi

Zergani

Hashemi

et al. 2022

SRT

View full text Add to dashboard Cite

Purpose The purpose of this paper is to maximize the total demand covered by the established additive manufacturing and distribution centers and maximize the total literal weight assigned to the drones. Design/methodology/approach Disaster management or humanitarian supply chains (HSCs) differ from commercial supply chains in the fact that the aim of HSCs is to minimize the response time to a disaster as compared to the profit maximization goal of commercial supply chains. In this paper, the authors develop a relief chain structure that accommodates emerging technologies in humanitarian logistics into the two phases of disaster management – the preparedness stage and the response stage. Findings Solving the model by the genetic and the cuckoo optimization algorithm (COA) and comparing the results with the ones obtained by The General Algebraic Modeling System (GAMS) clear that genetic algorithm overcomes other options as it has led to objective functions that are 1.6% and 24.1% better comparing to GAMS and COA, respectively. Originality/value Finally, the presented model has been solved with three methods including one exact method and two metaheuristic methods. Results of implementation show that Non-dominated sorting genetic algorithm II (NSGA-II) has better performance in finding the optimal solutions.

show abstract

Using 3D-printing in disaster response: The two-stage stochastic 3D-printing knapsack problem

Cited by 10 publications

References 61 publications

Putting 3D printing to good use—Additive Manufacturing and the Sustainable Development Goals

Putting 3D printing to good use—Additive Manufacturing and the Sustainable Development Goals

Tracing sustainable production from a degrowth and localisation perspective: A case of 3D printers

Analysis of optimized response time in a new disaster management model by applying metaheuristic and exact methods

Contact Info

Product

Resources

About