Research on Profit Mechanism of 3D Printing Cloud Platform Based on Customized Products

Liu, Xiao Wei; Yang, Yun; Xu, Xiao Dong; Li, Chang Chun; Ran, Ling Peng

doi:10.4028/www.scientific.net/amm.703.318

Cited by 8 publications

(5 citation statements)

References 3 publications

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“…15,16 These researches consist mainly of 3D printing cloud platform architecture, 17 3D printing resource access, 18 3D printing processing monitoring, 19 3D printing resource optimal allocation, 20 and 3D printing service evaluation. 12 Besides, there also research work focus on profit mechanism 21 for the 3D printing cloud platform. Existing 3D printing service evaluation approaches can be generally classified into two categories, standard testing component-based method as well as expert knowledge and experiencebased method.…”

Section: Related Workmentioning

confidence: 99%

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

Cui

Zhang

2021

Proceedings of the Institution of Mechanical Engineers, Part B:

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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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Section: Related Workmentioning

confidence: 99%

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

Cui

Zhang

2021

Proceedings of the Institution of Mechanical Engineers, Part B:

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“…where j p t represents the j-th MFG task of p t , which is decomposed according to the task type, where (1, 2, ..., ) j n  and n is the number of MFG task types (Liu, et al 2014). Fig.…”

Section: ) Task Decomposition and Expressionmentioning

confidence: 99%

Architecture of Cloud 3D Printing Task Modeling for Nodes Dynamic Scheduling and Coupling Based on Complex Networks

Zhang

Liu

et al. 2020

IEEE Access

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To study the variation in resource allocation efficiency in a cloud 3D printing (C3DP) manufacturing grid, C3DP task modeling for a complex network model was established based on the dynamic coupling of nodes, taking cloud manufacturing resource characteristics such as distribution and diversity into account. Based on this idea, we propose an architecture of C3DP task modeling for complex networks based on the dynamic coupling of nodes. First, the model calculates the initial tasks and services by evaluating the quality of the manufacturing resources, and then, according to the strength of the correlations among various tasks and among services and tasks, a multiplex network model based on cloud tasks and services is constructed. Then, according to the description and its constraint structure definition of the C3DP order tasks, by using the intercept method for complex networks, this paper identifies the work breakdown structure of coupling task sets, simplifies the optimization process, and proposes a C3DP order task (C3DPOT) network modeling method. Third, on the basis of the formal description of C3DP service resources, an architecture of C3DP order task methods for complex networks based on the dynamic coupling of nodes is proposed. Finally, a Service_Net model example is designed to verify the feasibility of the method.

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“…Liu et al [155] present a study on profit mechanisms associated with cloud 3D printing platforms predominantly in China. They argue that such services can enable small and medium sized enterprises (SME) to produce prototypes more rapidly and cheaper thus increasing their competitiveness.…”

Section: Rapid Prototypingmentioning

confidence: 99%

Additive Manufacturing, Cloud-Based 3D Printing and Associated Services—Overview

Baumann

Roller

2017

JMMP

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Cloud Manufacturing (CM) is the concept of using manufacturing resources in a service-oriented way over the Internet. Recent developments in Additive Manufacturing (AM) are making it possible to utilise resources ad-hoc as replacements for traditional manufacturing resources in case of spontaneous problems in the established manufacturing processes. In order to be of use in these scenarios, the AM resources must adhere to a strict principle of transparency and service composition in adherence to the Cloud Computing (CC) paradigm. With this review, we provide an overview of CM, AM and relevant domains as well as presenting the historical development of scientific research in these fields, from 2002 to 2016. Part of this work is also a meta-review on the domain to further detail its development and structure.

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Research on Profit Mechanism of 3D Printing Cloud Platform Based on Customized Products

Cited by 8 publications

References 3 publications

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

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

Architecture of Cloud 3D Printing Task Modeling for Nodes Dynamic Scheduling and Coupling Based on Complex Networks

Additive Manufacturing, Cloud-Based 3D Printing and Associated Services—Overview

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