3D Printing Cloud Research Articles

Evaluation of cloud 3D printing services oriented toward the product life cycle based on a triangular fuzzy number complementary judgment matrix

Evaluation of cloud 3D printing services oriented toward the product life cycle based on a triangular fuzzy number complementary judgment matrix

Task Scheduling Strategy for 3DPCP Considering Multidynamic Information Perturbation in Green Scene

The 3D printing cloud platform (3DPCP) plays a pivotal role in breaking down the information silos between supply and demand, effectively reducing waste through information integration and intelligent production. However, due to the complexity of 3DPCP scheduling in green scenes and the multidynamic information perturbations, unveils problems in traditional task scheduling methods in 3DPCP. These issues manifest as incomplete considerations, subpar green performance, and weak adaptability to dynamic changes. There is an urgent need to design practical methods to realize the multidynamic information perturbations in green scenes within 3DPCP. Therefore, this article first defines the 3DPCP task scheduling problem for multidynamic information perturbation in green scenes. Second, the article proposes a task scheduling model and a heuristic task scheduling strategy to minimize both the average cost and carbon dioxide (CO2) emissions per unit of quality product. Finally, the article validates effectiveness and superiority of the proposed strategy through simulation experiments.

Cloud 3D Printing Information Research

3D printing technology, as a major technological change in the global manufacturing industry, has gradually become the trend of The Times. As a service-oriented intelligent manufacturing system, cloud manufacturing has been widely studied by scholars at home and abroad in recent years. This paper takes cloud manufacturing as the carrier, studies the informatization of 3D printing service under cloud environment, elaborates the construction of 3D printing service information model in detail, and instantiates through Agent mapping model. This paper creates an implementation path for cloud 3D printing to provide on-demand precision manufacturing services.

Research on a supply–demand matching method for cloud 3D printing services based on complex networks

Research on a supply–demand matching method for cloud 3D printing services based on complex networks

3D Printing in the Context of Cloud Manufacturing

3D printing has drawn tremendous attention in Industry 4.0. Nowadays, with the ever-increasing consumers’ requests for 3D printing services, there lies a big challenge to eliminate the unbalanced demands and supplies of 3D printing resources in a geographically distributed environment. Cloud manufacturing, as a newly emerged service-oriented manufacturing paradigm, provides a promising way to overcome the challenge by integrating 3D printing into the cloud-based context, which may flourish the development of smart networks of virtual 3D printing cloud and also promote a novel 3D printing service business model to achieve mass customization. This paper presents a comprehensive study of 3D printing in cloud manufacturing environment. Two typical models of 3D printing, i.e. primary 3D printing cloud model and advanced 3D printing cloud model are presented and compared. The system architecture design of a 3D printing cloud platform is proposed to support the latter model. Furthermore, a series of key enabling technologies are presented based on the proposed system architecture. Finally, a prototype of 3D printing cloud platform is deployed with a case study of an aircraft engine part. The research will provide valuable theoretical and practical references to the future development of 3D printing clouds.

A Modeling and Semantic Description Method of Cloud 3D Printing Order Task Ontology Based on Multidimensional Features

A Modeling and Semantic Description Method of Cloud 3D Printing Order Task Ontology Based on Multidimensional Features

A modelling and semantic description method of cloud 3D printing order task ontology based on multidimensional features

A modelling and semantic description method of cloud 3D printing order task ontology based on multidimensional features

Research on Task-Service Network Node Matching Method Based on Multi-Objective Optimization Model in Dynamic Hyper-Network Environment.

In order to reduce the cost of manufacturing and service for the Cloud 3D printing (C3DP) manufacturing grid, to solve the problem of resources optimization deployment for no-need preference under circumstance of cloud manufacturing, consider the interests of enterprises which need Cloud 3D printing resources and cloud platform operators, together with QoS and flexibility of both sides in the process of Cloud 3D printing resources configuration service, a task-service network node matching method based on Multi-Objective optimization model in dynamic hyper-network environment is built for resource allocation. This model represents interests of the above-mentioned two parties. In addition, the model examples are solved by modifying Mathematical algorithm of Node Matching and Evolutionary Solutions. Results prove that the model and the algorithm are feasible, effective and stable.

Evaluation of Cloud 3D Printing Order Task Execution Based on the AHP-TOPSIS Optimal Set Algorithm and the Baldwin Effect.

Focusing on service control factors, rapid changes in manufacturing environments, the difficulty of resource allocation evaluation, resource optimization for 3D printing services (3DPSs) in cloud manufacturing environments, and so on, an indicator evaluation framework is proposed for the cloud 3D printing (C3DP) order task execution process based on a Pareto optimal set algorithm that is optimized and evaluated for remotely distributed 3D printing equipment resources. Combined with the multi-objective method of data normalization, an optimization model for C3DP order execution based on the Pareto optimal set algorithm is constructed with these agents’ dynamic autonomy and distributed processing. This model can perform functions such as automatic matching and optimization of candidate services, and it is dynamic and reliable in the C3DP order task execution process based on the Pareto optimal set algorithm. Finally, a case study is designed to test the applicability and effectiveness of the C3DP order task execution process based on the analytic hierarchy process and technique for order of preference by similarity to ideal solution (AHP-TOPSIS) optimal set algorithm and the Baldwin effect.

Research on 3D printing platform of blockchain for digital spare parts management

In the era of digital manufacturing, 3D printing has great potential in the spare parts supply chain due to its characteristics of real-time response manufacturing. In order to improve the docking efficiency of the supply and demand sides in 3D printing, the development of 3D printing cloud platform has received more and more attention. However, the traditional 3D printing platform can neither meet the needs of rapid production in actual production scenes nor create a safe and efficient data sharing mode. In order to meet these challenges, this paper proposes a 3D printing platform based on blockchain. First of all, the production standard identification and coordination solutions of spare parts suppliers are established to carry on the rapid qualification certification to the supplier. Secondly, the blockchain technology on-chain off-chain storage scheme is developed to achieve efficient sharing of 3D printed digital files under the premise of full property rights protection. Third, the product traceability service is developed to ensure the safety and transparency of spare parts. Finally, the effectiveness of the blockchain 3D printing platform is confirmed through the development of the prototype system.

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

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.

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

Overall structure design of model management and data protection system based on STL

This paper realizes the development of STL model management and data protection system for 3D printing cloud platform. Firstly, the 3D printing cloud platform is briefly introduced, and the system requirements analysis, system technical architecture construction, system flow and system database design are completed. Then, based on ASP.NET, database and other technologies, combined with C# language, Web development is carried out. Finally, from the perspective of tourist users, registered users and background administrators, the functions of their respective modules are realized.

Research on 3D Printing Resource cloud Platform Technology based on dynamic Service Composition

To improve the improve the management and matching of 3D printing resources, a 3Dprinting cloud platform based on dynamic service composition technology is established, and the 3D printing composite service is optimized. First, cloud computing is combined with 3D printing to establish cloud manufacturing mode. According to the characteristics of each stage, the dynamic service composition technology under cloud manufacturing mode is divided into three stages. Then, dynamic service composition technology of 3D printing resource is established. Based on the logical relationship between services, breadth algorithm and depth algorithm are used to find the optimal service composition path in the search graph to meet the different needs of users. The experimental results show that the relationship between user requirements and services can be obtained by calculating the quality of service. In the case, the service quality required by users is less than 20, and service 1 and 3 can meet the needs of users. This exploration provides a reference for the study of 3D printing resources dynamic service composition.

Research on 3D printing service model for innovation, entrepreneurship, and universal applications

In recent years, the attention of 3D printing technology has been increasing. With the development of the Internet, domestic 3D printing cloud platform services have begun to emerge. The emergence of 3D printing service platform solves the problems of equipment dispersion and talent shortage in the 3D printing industry as much as possible, and further promotes the promotion and development of 3D printing in China. Through the analysis of the existing 3D printing service platform in China and the innovation of Maker, the authors propose a 3D printing service model supporting innovation, entrepreneurship and popular applications. To design a 3D printing service platform with product customisation application, creative trading, printing services, and other functions, Spring MVC and Three.js technologies are used. After the later testing, the platform can complete the corresponding printing tasks according to user requirements.

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

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.

Modeling of Cloud 3D Printing Service Hyper-Network in Service-Oriented Manufacturing Systems

According to the theory of a complex network, the overall characteristics are derived from complex interactions among its components, that is, network structure. For its service network, its overall characteristics are its functions. In view of the coordinated linkage between the 3D printing industry and the logistics industry, 3D printing is deeply integrated with Internet technology, digital casting technology and Internet + service platforms. We propose a hyper-network model of raw material suppliers, semi-finished product processors and finished product manufacturers that realize on-demand customization. To analyse, design, and build the cloud 3D printing manufacturing capability service competition network, we propose a 3D printing service node structure model based on a super network using a reference and cloud manufacturing service model. The model's mathematical structure is given in detail. Under this condition, it is necessary to discuss the interaction between the logistics service level, productivity level and product processing quantity. The process of the proposed model and method is given, and the validity is proven with a case study of a Cloud 3D printing service hyper-network in service-oriented manufacturing systems.

A dynamic and static data based matching method for cloud 3D printing

Abstract 3D printing is widely used in such sectors as industry, medical, sports and education with the rapid development 3D printing technology and continual breakthrough of new material technology. Faced with the continual expansion of 3D printing market and the diversity and rapid growth of the scale of 3D printing devices, efficiently manage 3D print resources in the environment of distributed network manufacturing is a critical problem urgently to resolve. As a novel business paradigm, Cloud manufacturing can effectively integrate and manage manufacturing resources. Therefore, based on the cloud manufacturing paradigm, this study focuses on dynamic and static data based matching method for cloud 3D printing. In this paper, we propose a modeling framework to describe two models of the print task and print resource by model-based systems engineering. This modeling framework can support the efficient matching of the two types of models. Finally, the dynamic and static data based matching method can realistically simulate the supply-demand matching process of cloud 3D printing platform and provide a technical solution for quick supply-demand matching of large-scale resources in the environment of cloud manufacturing. During in the modeling process, we not only consider the static characteristics of 3D printers and analyze quantitatively all the parameter indicators of static characteristics, but also consider the dynamic characteristics of 3D printers to establish a universal dynamic data acquisition system, which can be used for real-time monitoring and automatic diagnosis of the health status of 3D printers. Therefore, this matching method has important theoretical significance and engineering value.

A cloud service platform for the seamless integration of digital design and rapid prototyping manufacturing

At present, some service platforms for 3D manufacturing encounter problems, including the low level of integration with digital design ability, the single character of cooperative printings, the uneven distribution of 3D printing resources, and the high 3D design requirements of users. To overcome these issues, a cloud service platform for the seamless integration of digital design and rapid prototyping manufacturing was established using ASP.NET, WebGL, WebSocket, and SQL Server in combination with C# language and JavaScript. The goals were to realize a design and rapid prototyping of mechanical equipment parts that are browser based and provide online digital design services, such as the parametric design of key parts, downloading of models, format conversion, and virtual assembly. The client application layer, server processing layer, database layer, and working machine end application layer of this cloud 3D printing platform were set up. The result of the design module could be printed remotely in 3D. Practical application showed that the platform could effectively improve the R&D and design speed of the parts and components of the mechanical equipment and reduce the effort of designers. In particular, this platform would be suitable for users without a 3D design background. The design and rapid prototyping parts of the platform satisfied the dimensional precision required by enterprises, which provides an important basis for the further verification of the design correctness for small- and medium-sized enterprises and has high application value.

Combination of cloud manufacturing and 3D printing: research progress and prospect

The development of information, materials science, and technology has led to profound changes in manufacturing. Many new ideas and technologies have emerged in recent years, such as cloud manufacturing and 3D printing. Cloud manufacturing (CM) is a new type of networked manufacturing mode proposed in 2010, and 3D printing is an example of new manufacturing methods. CM and 3D printing both have significant influence in the manufacturing mode and manufacturing method and are already research hotspots in the field of advanced manufacturing technology. What kind of innovations will be produced when they integrate? To explore this issue, this paper first analyses the characteristics of cloud manufacturing and 3D printing. Second, the combination research of cloud manufacturing and 3D printing in recent years is studied, including 3D printing cloud platform (3D–PCP) service architectures, 3D printing resource access technology, 3D printing service optimized configuration technology, 3D printing service control and monitoring technology, and 3D printing service evaluation technology. There are several research achievements and commercial application cases of 3D–PCP, but a true sense of 3D printing cloud ecology from the perspective of a manufacturing system has not been formed to date. On the basis of the survey and analysis, this paper highlights the shortcomings in current research and proposes development suggestions of the combination of 3D printing and cloud manufacturing, including the potential research direction of 3D–PCP system modes, the Internet of Things in 3D printing, and the 3D printing service process control and evaluation.