scholarly journals Modelling of cross organizational manufacturing resource service chain based on service supply-demand dynamic matching network

2019 ◽  
Vol 277 ◽  
pp. 01005
Author(s):  
Qingqing Yang ◽  
Jia Liu ◽  
Kewei Yang
Keyword(s):  
Network Theory ◽  
Service Composition ◽  
Manufacturing Systems ◽  
Dynamic Scheduling ◽  
Cloud Manufacturing ◽  
Cloud Services ◽  
Matching Network ◽  
Dynamic Matching ◽  
Composition Problem ◽  
Resource Service

In the cloud manufacturing systems, both manufacturing tasks and manufacturing services are in a dynamic environment. How could cloud manufacturing platform optimizes manufacturing cloud services based on QoS, matching an optimal service composition for manufacturing tasks has become an urgent problem at present. In view of this problem, we study the matching of manufacturing tasks and manufacturing services from the perspective of complex network theory. On the basis of manufacturing task network and manufacturing service network, a dynamic matching network theory model of manufacturing task-service is constructed. And then, we take a dynamic assessment of QoS. Finally, we use load and dynamic QoS as the optimization objectivities, transform the optimal manufacturing service composition problem into the shortest path problem, and the dynamic scheduling of manufacturing services is realized.

Interoperability in Cloud Manufacturing and Practice on Private Cloud Structure for SMEs

2017 ◽  
Author(s):  
Xi Vincent Wang ◽  
Lihui Wang
Keyword(s):  
Manufacturing Systems ◽  
Manufacturing System ◽  
Research Work ◽  
Cloud Manufacturing ◽  
Cloud Services ◽  
Security Requirements ◽  
Research Trend ◽  
Safety Regulations ◽  
Multiple Challenges ◽  
New Research

In recent years, Cloud manufacturing has become a new research trend in manufacturing systems leading to the next generation of production paradigm. However, the interoperability issue still requires more research due to the heterogeneous environment caused by multiple Cloud services and applications developed in different platforms and languages. Therefore, this research aims to combat the interoperability issue in Cloud Manufacturing System. During implementation, the industrial users, especially Small- and Medium-sized Enterprises (SMEs), are normally short of budget for hardware and software investment due to financial stresses, but they are facing multiple challenges required by customers at the same time including security requirements, safety regulations. Therefore in this research work, the proposed Cloud manufacturing system is specifically tailored for SMEs.

scholarly journals Composition of Resource-Service Chain Based on Evolutionary Algorithm in Distributed Cloud Manufacturing Systems

IEEE Access ◽  
2020 ◽  
Vol 8 ◽  
pp. 19911-19920 ◽  
Author(s):  
Haibo Li ◽  
Shaoyuan Weng ◽  
Juncheng Tong ◽  
Ting He ◽  
Wenyun Chen ◽  
...  
Keyword(s):  
Evolutionary Algorithm ◽  
Manufacturing Systems ◽  
Cloud Manufacturing ◽  
Service Chain ◽  
Distributed Cloud ◽  
Resource Service

scholarly journals Dynamic mutual manufacturing and transportation routing service selection for cloud manufacturing with multi-period service-demand matching

2021 ◽  
Vol 7 ◽  
pp. e461
Author(s):  
Seyed Ali Sadeghi Aghili ◽  
Omid Fatahi Valilai ◽  
Alireza Haji ◽  
Mohammad Khalilzadeh
Keyword(s):  
Service Composition ◽  
Large Scale ◽  
Business Models ◽  
Service Providers ◽  
Service Selection ◽  
Cloud Service ◽  
Cloud Manufacturing ◽  
Architecture Model ◽  
Logistics Service ◽  
Composition Problem

Recently, manufacturing firms and logistics service providers have been encouraged to deploy the most recent features of Information Technology (IT) to prevail in the competitive circumstances of manufacturing industries. Industry 4.0 and Cloud manufacturing (CMfg), accompanied by a service-oriented architecture model, have been regarded as renowned approaches to enable and facilitate the transition of conventional manufacturing business models into more efficient and productive ones. Furthermore, there is an aptness among the manufacturing and logistics businesses as service providers to synergize and cut down the investment and operational costs via sharing logistics fleet and production facilities in the form of outsourcing and consequently increase their profitability. Therefore, due to the Everything as a Service (XaaS) paradigm, efficient service composition is known to be a remarkable issue in the cloud manufacturing paradigm. This issue is challenging due to the service composition problem’s large size and complicated computational characteristics. This paper has focused on the considerable number of continually received service requests, which must be prioritized and handled in the minimum possible time while fulfilling the Quality of Service (QoS) parameters. Considering the NP-hard nature and dynamicity of the allocation problem in the Cloud composition problem, heuristic and metaheuristic solving approaches are strongly preferred to obtain optimal or nearly optimal solutions. This study has presented an innovative, time-efficient approach for mutual manufacturing and logistical service composition with the QoS considerations. The method presented in this paper is highly competent in solving large-scale service composition problems time-efficiently while satisfying the optimality gap. A sample dataset has been synthesized to evaluate the outcomes of the developed model compared to earlier research studies. The results show the proposed algorithm can be applied to fulfill the dynamic behavior of manufacturing and logistics service composition due to its efficiency in solving time. The paper has embedded the relation of task and logistic services for cloud service composition in solving algorithm and enhanced the efficiency of resulted matched services. Moreover, considering the possibility of arrival of new services and demands into cloud, the proposed algorithm adapts the service composition algorithm.

scholarly journals A Smart Cloud-Based System for the WEEE Recovery/Recycling

2015 ◽  
Vol 137 (6) ◽  
Author(s):  
Xi Vincent Wang ◽  
Brenda N. Lopez N ◽  
Winifred Ijomah ◽  
Lihui Wang ◽  
Jinhui Li
Keyword(s):  
Manufacturing Systems ◽  
Service Oriented Architecture ◽  
Intelligent System ◽  
Cloud Manufacturing ◽  
Cloud Services ◽  
Electronic Equipment ◽  
Data Management System ◽  
Component Level ◽  
Recovery System ◽  
Service Oriented

Waste electrical and electronic equipment (WEEE) is both valuable and harmful since it contains a large number of profitable and hazardous materials and elements at the same time. At component level, many parts of the discarded equipment are still functional and recoverable. Thus, it is necessary to develop a distributed and intelligent system to support WEEE component recovery and recycling. In recent years, the Cloud concept has gained increasing popularity since it provides a service-oriented architecture (SOA) that integrates various resources over the network. Cloud manufacturing systems are proposed worldwide to support operational manufacturing processes. In this research, Cloud manufacturing is further extended to the WEEE recovery and recycling context. The Cloud services are applied in WEEE recovery and recycling processes by tracking and management services. These services include all the stakeholders from the beginning to the end of life of the electric and electronic equipment. A Cloud-based WEEE recovery system is developed to provide modularized recovery services on the Cloud. A data management system is developed as well, which maintains the knowledge throughout the product lifecycle. A product tracking mechanism is also proposed with the help of the Quick Respond code method.

Research on the Relationships of Customized Service Attributes in Cloud Manufacturing

2016 ◽  
Author(s):  
Longfei Zhou ◽  
Lin Zhang ◽  
Yuyan Xu
Keyword(s):  
Service Composition ◽  
Fitness Function ◽  
Cloud Service ◽  
Cloud Manufacturing ◽  
Task Completion ◽  
Dynamic Nature ◽  
Dimensional Classification ◽  
Resource Service ◽  
The Relationship ◽  
Service Attribute

Cloud manufacturing (CMfg) aims to meet the customization demand of resource service demander (RSD) effectively. This article investigates the relationship between cloud service attributes and task completion from several aspects and a multi-dimensional classification scheme of cloud service attributes is established. Key service attributes of manufacturing cloud service are categorized in six aspects including role oriented, dynamic nature of data, steps of service composition, correlation between service attribute and fitness function of service composition, value types and dimension. From the perspective of attribute indexes, the relationship between service attributes and different demands of personalized customized are analysed and elaborated, and the corresponding objective functions are proposed.

scholarly journals Blockchain-based cloud manufacturing platforms: A novel idea for service composition in XaaS paradigm

2021 ◽  
Vol 7 ◽  
pp. e743
Author(s):  
Seyyed-Alireza Radmanesh ◽  
Alireza Haji ◽  
Omid Fatahi Valilai
Keyword(s):  
Service Composition ◽  
Manufacturing Systems ◽  
Large Scale ◽  
Manufacturing System ◽  
Service Oriented Architecture ◽  
Time Synchronization ◽  
Main Idea ◽  
Cloud Manufacturing ◽  
Blockchain Technology ◽  
Service Oriented

Cloud manufacturing is a new globalized manufacturing framework which has improved the performance of manufacturing systems. The service-oriented architecture as the main idea behind this framework means that all resources and capabilities are considered as services. The agents interact by way of service exchanging, which has been a part of service composition research topics. Service allocations to demanders in a cloud manufacturing system have a dynamic behavior. However, the current research studies on cloud-based service composition are mainly based on centralized global optimization models. Therefore, a distributed deployment and real-time synchronization platform, which enables the globalized collaboration in service composition, is required. This paper proposes a method of using blockchain to solve these issues. Each service composition is considered as a transaction in the blockchain concept. A block includes a set of service compositions and its validity is confirmed by a predefined consensus mechanism. In the suggested platform, the mining role in blockchain is interpreted as an endeavor for proposing the proper service composition in the manufacturing paradigm. The proposed platform has interesting capabilities as it can increase the response time using the blockchain technology and improve the overall optimality of supply-demand matching in cloud manufacturing. The efficiency of the proposed model was evaluated by investigating a service allocation problem in a cloud manufacturing system in four large scale problems. Each problem is examined in four centralized modes, two, three and four solvers in blockchain-based model. The simulation results indicate the high quality of the proposed solution. The proposed solution will lead to at least 15.14% and a maximum of 34.8 percent reduction in costs and 20 to 68.4 percent at the solving time of the problem. It is also observed that with increasing the number of solvers (especially in problems with larger dimensions) the solution speed increases sharply (more than 68% improvement in some problems), which indicates the positive effect of distribution on reducing the problem-solving time.

Research on the Measurement Method of Flexibility of Resource Service Composition in Cloud Manufacturing

2010 ◽  
Vol 139-141 ◽  
pp. 1451-1454 ◽  
Author(s):  
Hua Guo ◽  
Lin Zhang ◽  
Fei Tao ◽  
Lei Ren ◽  
Yong Liang Luo
Keyword(s):  
Service Composition ◽  
Measurement Method ◽  
Cloud Manufacturing ◽  
Added Value ◽  
Optimal Selection ◽  
Dynamic Changes ◽  
Service Oriented ◽  
Manufacturing Resource ◽  
Resource Service ◽  
Selection Of

In order to overcome the bottlenecks of traditional network manufacturing, a new service-oriented networked manufacturing model, i.e. the cloud manufacturing (CMfg), was proposed recently. As an effective method for the realization of the added value of manufacturing resource, resource service composition (RSC) plays an important role in the implementation of CMfg. In view of the issue of dynamic changes occurred during RSC in CMfg, this paper presents the concept of flexibility of RSC as well as the idea of optimal-selection of RSC based on flexibility, which can enable RSC to have the ability to adapt to the dynamic changes. Meantime, the measurement method of flexibility of RSC is investigated. The optimal-selection of RSC based on flexibility can be achieved through quantitative evaluation of flexibility.

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