Pricing strategy and system performance in a cloud-based manufacturing system built on blockchain technology

Zhu, Xiaobao; Shi, Jing; Xie, Fangxia; Song, Rouqi

doi:10.1007/s10845-020-01548-3

Cited by 16 publications

(11 citation statements)

References 61 publications

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“…Lack of confidence is a huge hamper on developing collaboration and it affects its performance. Scoring the trust rate for companies in a standard way might bring confidence and better operational and business performance on inter-organizational collaboration (Zhu et al 2020a ). Therefore, the semantic delamination of “trust” under collaboration is necessary (Yang et al 2019 ).…”

Section: State Of the Artmentioning

confidence: 99%

A blockchain technology based trust system for cloud manufacturing

Barenji

2021

J Intell Manuf

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Cloud manufacturing (CM) is a new networked manufacturing model that delivers various on-demand manufacturing capabilities to the consumers from the providers. In this model, the provider and consumer never meet each other, thus "trust" is the major enabler for starting a collaboration. In another word, a user must be sure that the requested capability will not be provided with malicious results, and the provider should ensure that the payment will be made on time. In this paper, a novel Blockchain Technology (BCT)-based trust system called "Blocktrust" is proposed to address the trust problem of the CM. First, the CM framework that contains the digital firm, capability pool, and digital certificate issuing units is developed, and then, the private blocktrust peer-to-peer network is proposed and implemented based on Hyperledger fabric. Finlay, the feasibility of the blocktrust is examined under different testing scenarios. The reason for using a private network instead of the public is placing restrictions on who is allowed to participate in the network and also enjoying a network with fast transaction speed. Experiments show that the proposed blocktrust embedded CM is credible and practical.

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Section: State Of the Artmentioning

confidence: 99%

A blockchain technology based trust system for cloud manufacturing

Barenji

2021

J Intell Manuf

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“…The fundamental methodology of service provision, which Cloud manufacturing works upon, is that the entire supply network is deemed the aggregation of modules and blocks that can be outsourced and provided in perhaps diversely located service points and fulfilled by different service providers. These service providers will then collaborate to fulfill an order by collaborating their resources ( Tao et al, 2017 ; Zhu et al, 2020c ). This service composition approach for fulfilling complicated orders is believed to result in higher quality, productivity, and versatility ( Lasi et al, 2014 ; Saldivar et al, 2015 ; Tao & Qi, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

“…Cloud manufacturing, is mainly referred to and elaborated with the help of the Everything as a Service (XaaS) concept. This concept persuades service providers to deploy the most state-of-the-art high-tech and cybernetics, namely Internet of Things (IoT) and Blockchain ( Zhu et al, 2020c ; Li, Barenji & Huang, 2018 ; Zhu et al, 2020b ). On the other hand, this enables clients to access a wide range of services to select from and compose them to fit best their requirements ( Saldivar et al, 2015 ; Qi & Tao, 2019 ).…”

Section: Introductionmentioning

confidence: 99%

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

Aghili

Valilai

Haji

et al. 2021

PeerJ Computer Science

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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.

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“…The fundamental methodology of service provision, which Cloud manufacturing works upon, is that the entire supply network is deemed the aggregation of modules and blocks that can be outsourced and provided in perhaps diversely located service points and fulfilled by different service providers. These service providers will then collaborate to fulfill an order by collaborating their resources (Tao et al, 2017;Zhu et al, 2020c). This service composition approach for fulfilling complicated orders is believed to result in higher quality, productivity, and versatility (Lasi et al, 2014;Saldivar et al, 2015;.…”

Section: Introductionmentioning

confidence: 99%

“…Cloud manufacturing, is mainly referred to and elaborated with the help of the Everything as a Service (XaaS) concept. This concept persuades service providers to deploy the most state-of-the-art high-tech and cybernetics, namely Internet of Things (IoT) and Blockchain (Zhu et al, 2020c;Li, Barenji & Huang, 2018;Zhu et al, 2020b). On the other hand, this enables clients to access a wide range of services to select from and compose them to fit best their requirements (Saldivar et al, 2015;.…”

Section: Introductionmentioning

confidence: 99%

Figure 10: The depiction of the sample problem solved by the developed algorithm (Number of Operations, Number of Sub-operations, Number of planned Sub-operations, Number of Totally planned operations).

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Pricing strategy and system performance in a cloud-based manufacturing system built on blockchain technology

Cited by 16 publications

References 61 publications

A blockchain technology based trust system for cloud manufacturing

A blockchain technology based trust system for cloud manufacturing

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

Figure 10: The depiction of the sample problem solved by the developed algorithm (Number of Operations, Number of Sub-operations, Number of planned Sub-operations, Number of Totally planned operations).

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