3D Printing in the Context of Cloud Manufacturing

2022 ◽  
Vol 74 ◽  
pp. 102256
Author(s):  
Jin Cui ◽  
Lei Ren ◽  
Jingeng Mai ◽  
Pai Zheng ◽  
Lin Zhang
Keyword(s):  
3D Printing ◽  
Cloud Manufacturing

scholarly journals Cloud Manufacturing, Internet of Things-Assisted Manufacturing and 3D Printing Technology: Reliable Tools for Sustainable Construction

2021 ◽  
Vol 13 (13) ◽  
pp. 7327
Author(s):  
Rajesh Singh ◽  
Anita Gehlot ◽  
Shaik Vaseem Akram ◽  
Lovi Raj Gupta ◽  
Manoj Kumar Jena ◽  
...  
Keyword(s):  
3D Printing ◽  
Internet Of Things ◽  
Materials Science ◽  
Predictive Analytics ◽  
Residential Buildings ◽  
Three Dimensional ◽  
Cloud Manufacturing ◽  
Service Evaluation ◽  
Sustainable Construction ◽  
Access Technology

The United Nations (UN) 2030 agenda on sustainable development goals (SDGs) encourages us to implement sustainable infrastructure and services for confronting challenges such as large energy consumption, solid waste generation, depletion of water resources and emission of greenhouse gases in the construction industry. Therefore, to overcome challenges and establishing sustainable construction, there is a requirement to integrate information technology with innovative manufacturing processes and materials science. Moreover, the wide implementation of three-dimensional printing (3DP) technology in constructing monuments, artistic objects, and residential buildings has gained attention. The integration of the Internet of Things (IoT), cloud manufacturing (CM), and 3DP allows us to digitalize the construction for providing reliable and digitalized features to the users. In this review article, we discuss the opportunities and challenges of implementing the IoT, CM, and 3D printing (3DP) technologies in building constructions for achieving sustainability. The recent convergence research of cloud development and 3D printing (3DP) are being explored in the article by categorizing them into multiple sections including 3D printing resource access technology, 3D printing cloud platform (3D–PCP) service architectures, 3D printing service optimized configuration technology, 3D printing service evaluation technology, and 3D service control and monitoring technology. This paper also examines and analyzes the limitations of existing research and, moreover, the article provides key recommendations such as automation with robotics, predictive analytics in 3DP, eco-friendly 3DP, and 5G technology-based IoT-based CM for future enhancements.

3D Printing in Cloud Manufacturing: Model and Platform Design

2016 ◽  
Author(s):  
Lei Ren ◽  
Shicheng Wang ◽  
Yijun Shen ◽  
Shikai Hong ◽  
Yudi Chen ◽  
...  
Keyword(s):  
3D Printing ◽  
Cloud Model ◽  
Cloud Manufacturing ◽  
Architecture Design ◽  
Know How ◽  
Platform Architecture ◽  
Service Oriented ◽  
Geographically Distributed ◽  
3D Printers ◽  
Advanced Model

Although 3D printing has attracted remarkable attention from both industry and academia society, still only a relatively small number of people have access to required 3D printers and know how to use them. One of the challenges is that how to fill the gap between the unbalanced supply of various 3D printing capabilities and the customized demands from geographically distributed customers. The integration of 3D printing into cloud manufacturing may promote the development of future smart networks of virtual 3D printing cloud, and allow a new service-oriented 3D printing business model to achieve mass customization. This paper presents a primary 3D printing cloud model and an advanced 3D printing cloud model, and analyzes the 3D printing service delivery paradigms in the models. Further, the paper proposes a 3D printing cloud platform architecture design to support the advanced model. The proposed advanced 3D printing cloud model as well as the architecture design can provide a reference for the development of various 3D printing clouds.

USA² — Ubiquitous and Robot Assisted Cloud Manufacturing in an Ageing Society

2015 ◽  
Vol 27 (1) ◽  
pp. 109-109 ◽  
Author(s):  
Thomas Linner ◽  
◽  
Jörg Güttler ◽  
Christos Georgoulas ◽  
Thomas Bock
Keyword(s):  
3D Printing ◽  
Cloud Manufacturing ◽  
Cooperative Robotics ◽  
Robot Assisted ◽  
Ageing Society ◽  
Novel Technologies

<div class=""abs_img""><img src=""[disp_template_path]/JRM/abst-image/00270001/16.jpg"" width=""300"" />Micro home factory in future</div> In the project USA² (Ubiquitäres und Selbstständiges Arbeiten in einer alternden Gesellschaft), a robotic, mini-factory-like workspace was developed which integrates novel technologies from the field of telepresence, cooperative robotics, seamless interaction, 3D printing and cloud manufacturing. </span>

A probabilistic-based extendable quantitative evaluation method for 3D printing service in cloud manufacturing

2021 ◽  
pp. 095440542110159
Author(s):  
Jin Cui ◽  
Lin Zhang
Keyword(s):  
3D Printing ◽  
Quantitative Evaluation ◽  
Probabilistic Models ◽  
Evaluation Method ◽  
Evaluation Model ◽  
Multinomial Distribution ◽  
Cloud Manufacturing ◽  
Consumer Products ◽  
Cloud Services ◽  
Weighting Method

By enabling consumer products to be produced on demand and eliminating waste caused by excessive production and transportation, 3D Printing Cloud Services (3DPCSs) are increasingly welcomed by non-professional customers. With more and more 3D printers becoming available on various 3DPCS platforms, the evaluation and selection problem of 3DPCS has attracted much attention for both novices and experienced users. In this paper, we propose a probabilistic-based extendable quantitative evaluation method for 3DPCS evaluation. This method combines the advantages of the information transformation technique, the multinomial distribution probabilistic model, and the uncertainty based weighting method. Evaluation factors, the major attributes that significantly affect the performance of a 3DPCS, are modeled using probabilistic models. At the same time, historical service data is introduced to dynamically identify and update the evaluation factors. Based on these parameters, the proposed quantitative evaluation method can support the evaluation and comparison of 3DPCSs. Numerical simulation experiments are designed and implemented. The corresponding results verify the effectiveness of the proposed evaluation model. The presented evaluation method can serve as the basis of service evaluation and selection on a 3DPCS platform. Although the focus of this work is on 3DPCS, the idea can apply to other types of cloud manufacturing services.

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