Service architecture and evaluation model of distributed 3D printing based on cloud manufacturing

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

Sustainability ◽

10.3390/su13137327 ◽

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.

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Multiobjective Optimization Model of Production Planning in Cloud Manufacturing Based on TOPSIS Method with Combined Weights

Complexity ◽

10.1155/2019/7503176 ◽

2019 ◽

Vol 2019 ◽

pp. 1-15

Author(s):

Zhiru Li ◽

Wei Xu ◽

Huibin Shi ◽

Qingshan Zhang ◽

Fengyi He

Keyword(s):

Multiobjective Optimization ◽

Production Planning ◽

Mass Customization ◽

Evaluation Model ◽

Cloud Manufacturing ◽

Production Plan ◽

Topsis Method ◽

Nsga Ii ◽

Optimal Production ◽

Planning Scheme

Combined with the research of mass customization and cloud manufacturing mode, this paper discussed the production planning of mass customization enterprises in the context of cloud manufacturing in detail, analyzed the attribute index of manufacturing resource combination, and given a system considering the characteristics of batch production in mass customization and the decentralization of manufacturing resources in cloud manufacturing environment. Then, a multiobjective optimization model has been constructed according to the product delivery date, product cost, and product quality that customers care most about. The Pareto solution set of production plan has been obtained by using NSGA-II algorithm. This paper established a six-tier attribute index system evaluation model for the optimization of production planning scheme set of mass customization enterprises in cloud manufacturing environment. The weight coefficients of attribute indexes were calculated by combining subjective and objective weights with analytic hierarchy process (AHP) and entropy weight method. Finally, the combined weights calculated were applied to the improved TOPSIS method, and the optimal production planning scheme has been obtained by ranking. This paper validated the effectiveness and feasibility of the multiobjective model and NSGA-II algorithm by the example of company A. The Pareto effective solution has been obtained by solving the model. Then the production plan set has been sorted synthetically according to the comprehensive evaluation model, and the optimal production plan has been obtained.

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Adaptive Effect Evaluation Model of Composite Cloud Service in Cloud Manufacturing Environment

2020 IEEE 6th International Conference on Computer and Communications (ICCC) ◽

10.1109/iccc51575.2020.9345222 ◽

2020 ◽

Author(s):

Le Wei ◽

Qiuyun Zhao ◽

Yu Chang ◽

Hongping Shu

Keyword(s):

Evaluation Model ◽

Cloud Service ◽

Cloud Manufacturing ◽

Effect Evaluation ◽

Manufacturing Environment ◽

Adaptive Effect

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A hierarchical and configurable reputation evaluation model for cloud manufacturing services based on collaborative filtering

The International Journal of Advanced Manufacturing Technology ◽

10.1007/s00170-017-0662-x ◽

2017 ◽

Vol 94 (9-12) ◽

pp. 3327-3343 ◽

Cited By ~ 6

Author(s):

Yu Feng ◽

Biqing Huang

Keyword(s):

Collaborative Filtering ◽

Evaluation Model ◽

Cloud Manufacturing

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A 3D Printing Task Packing Algorithm Based on Rectangle Packing in Cloud Manufacturing

Lecture Notes in Electrical Engineering - Proceedings of 2017 Chinese Intelligent Systems Conference ◽

10.1007/978-981-10-6499-9_3 ◽

2017 ◽

pp. 21-31

Author(s):

Zhen Zhao ◽

Lin Zhang ◽

Jin Cui

Keyword(s):

3D Printing ◽

Cloud Manufacturing ◽

Rectangle Packing ◽

Packing Algorithm

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3D Printing in Cloud Manufacturing: Model and Platform Design

Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing ◽

10.1115/msec2016-8669 ◽

2016 ◽

Cited By ~ 6

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.

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