Research and development of off-line services for the 3D automatic printing machine based on cloud manufacturing

Zhang, Chenglei; Sheng, Buyun; Yin, Xiyan; Zhao, Feiyu; Shu, Yao

doi:10.1007/s12652-017-0615-0

Cited by 16 publications

(8 citation statements)

References 31 publications

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“…A multi-objective hybrid artificial bee colony algorithm was proposed for service composition and optimization selection in cloud manufacturing [231]. An offline 3D automated printer approach to enhance the competitiveness of 3D printing was developed based on the cloud manufacturing service model and the 3D printing cloud service platform [232]. The optimal choice of a cloud service portfolio in cloud manufacturing was studied, and a cloud service category and a service quality index were established [233].…”

Section: Collaborative Manufacturingmentioning

confidence: 99%

Digital twin-based sustainable intelligent manufacturing: a review

2020

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As the next-generation manufacturing system, intelligent manufacturing enables better quality, higher productivity, lower cost, and increased manufacturing flexibility. The concept of sustainability is receiving increasing attention, and sustainable manufacturing is evolving. The digital twin is an emerging technology used in intelligent manufacturing that can grasp the state of intelligent manufacturing systems in real-time and predict system failures. Sustainable intelligent manufacturing based on a digital twin has advantages in practical applications. To fully understand the intelligent manufacturing that provides the digital twin, this study reviews both technologies and discusses the sustainability of intelligent manufacturing. Firstly, the relevant content of intelligent manufacturing, including intelligent manufacturing equipment, systems, and services, is analyzed. In addition, the sustainability of intelligent manufacturing is discussed. Subsequently, a digital twin and its application are introduced along with the development of intelligent manufacturing based on the digital twin technology. Finally, combined with the current status, the future development direction of intelligent manufacturing is presented.

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Section: Collaborative Manufacturingmentioning

confidence: 99%

Digital twin-based sustainable intelligent manufacturing: a review

2020

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“…Here, task-order requirement agents: each agent is registered and released to all the requirements as the condition attribute and forms a meta-model corresponding to the task-order demand; task-order decomposition agent: According to the task decomposition strategy of the C3DPD Platform, this meta-model

is expressed by the discrete attributes values of the decision table; Search-matching agent: this agent is a domain

of feasible solutions of the corresponding service resource candidate service subset [ 22 ]. Therefore,

is a subset of candidate services, and these are matched by the atomic task

; Service resource agent: according to the weight indicators of the domain

of feasible solutions, it corresponds to some subsets of candidate services by the Pareto optimal optimization algorithm, also supported to this C3DPS platform; Evaluation agent: the domain

of feasible solutions are solved that it corresponds to some subsets of this candidate services.…”

Section: Framework For Cloud Service Evaluation Based On a Hybrid Multi-objective Bm-mopso Evaluation Modelmentioning

confidence: 99%

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

Zhang

Zhuang

et al. 2021

Micromachines

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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.

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“…It is an organic collection of those services' and tasks' active objects (such as order type, processing process, delivery time, and product material) on time, information, and physical flow [18]. The modelling and digital description of C3DP tasks and services are the basis for information monitoring and processing in the execution process of C3DP tasks based on order-driven tasks [19]. This order tasks model and services model can formally represent its information and effectively integrate and manage the data of those service and manufacturing tasks.…”

Section: Introductionmentioning

confidence: 99%

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

2020

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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. INDEX TERMS Complex network, manufacturing resource services, service-oriented manufacturing (SOM), cloud manufacturing, cloud 3D printing, order-driven.

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Research and development of off-line services for the 3D automatic printing machine based on cloud manufacturing

Cited by 16 publications

References 31 publications

Digital twin-based sustainable intelligent manufacturing: a review

Digital twin-based sustainable intelligent manufacturing: a review

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

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

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