Evaluating of dynamic service matching strategy for social manufacturing in cloud environment

Xue, Xiao; Wang, Shufang; Zhang, Lejun; Feng, Zhiyong

doi:10.1016/j.future.2018.08.028

Cited by 37 publications

(10 citation statements)

References 30 publications

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“…Jiang and Leng [ 32 ] introduced the concepts and characteristics of social manufacturing. Social manufacturing has three characteristics, namely, social-oriented interconnection, service-oriented transformation, and IoT-oriented production structure [ 33 ]. Social manufacturing was viewed as cyber–physical–social connected and service-oriented.…”

Section: Related Workmentioning

confidence: 99%

Understanding Data-Driven Cyber-Physical-Social System (D-CPSS) Using a 7C Framework in Social Manufacturing Context

Yin

Ming

Zhang

2020

Sensors

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The trend towards socialization, personalization and servitization in smart manufacturing has attracted the attention of researchers, practitioners and governments. Social manufacturing is a novel manufacturing paradigm responding to this trend. However, the current cyber–physical system (CPS) merges only cyber and physical space; social space is missing. A cyber–physical–social system (CPSS)-based smart manufacturing is in demand, which incorporates cyber space, physical space and social space. With the development of the Internet of Things and social networks, a large volume of data is generated. A data-driven view is necessary to link tri-space. However, there is a lack of systematical investigation on the integration of CPSS and the data-driven view in the context of social manufacturing. This article proposes a seven-layered framework for a data-driven CPSS (D-CPSS) along the data–information–knowledge–wisdom (DIKW) pyramid under a social manufacturing environment. The evolution, components, general model and framework of D-CPSS are illustrated. An illustrative example is provided to explain the proposed framework. Detailed discussion and future perspectives on implementation are also presented.

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Section: Related Workmentioning

confidence: 99%

Understanding Data-Driven Cyber-Physical-Social System (D-CPSS) Using a 7C Framework in Social Manufacturing Context

Yin

Ming

Zhang

2020

Sensors

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“…From the perspective of the relationship between production capacity sharing related technologies and sustainability development, Xue et al [37] and Ren et al [38] found that the technologies for matching and control on platforms could render the process more efficient and secure. According to the previous research [39,40], products via platforms can be characterized by sustainability because the production process via the platform is guaranteed in terms of quality and delivery time and produced by surplus production capacity, using the related technologies.…”

Section: Literature On Production Capacity Sharingmentioning

confidence: 99%

Channel Selection and Pricing Decisions Considering Three Charging Modes of Production Capacity Sharing Platform: A Sustainable Operations Perspective

et al. 2019

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In the context of sharing economy, a manufacturer can source from two alternative channels: sharing and traditional, when facing production capacity constraints and sustainably conscious consumers. The aim of the paper is to analyze channel selection and pricing strategies of the manufacturer for achieving sustainable operations, to investigate the operations of the platform regarding charging modes, access requirements, and commission rates in different stages of development, and to discuss the interaction among all stakeholders for sustainability in the whole system. The game-theoretic approach is adopted. The results provide references for decisions of the manufacturer and surplus production capacity supplier to join in the sharing, as well as corresponding optimal pricing strategies, which guides platforms to keep a balance between profitability and attracting participants by relatively low access requirements and commission rates. Moreover, developing platforms prefer to charge suppliers and set low access requirements while relatively developed platforms tend to charge bilateral sides or manufacturers and set high access requirements. Charging the manufacturer encourages the bilateral participation of the platform most. In addition, as charging mode changes, the trend of changes in consumer surplus and social welfare is the same as that in the market share of products from the sharing channel.More specifically, from the perspective of actual operations, production capacity sharing brings new directions to sustainable supply chain management issues. For example, as consumers have become more sustainably concerned [16,17], production capacity sharing on the platforms is an effective alternative for manufacturing enterprises to ensure competitive advantage by meeting demands of the market, reduce their risk of wasting capacity, no longer face with the selection limitations, optimize business scheduling, and gain new revenue streams [13]. However, production capacity sharing mechanism design considering sharing features is challenging. For example, a capacity-constrained manufacturer or an overcapacity supplier needs to decide whether to join in the sharing considering the cost of the sharing and consumer's consciousness of sustainability comprehensively. In addition, a platform operator needs to design appropriate operational mechanisms particularly the charging mechanisms to balance the relationship between attracting participants of the platform and gaining profits, considering its own development levels and operational goals. Therefore, with regards to production capacity sharing, how to make channel selection decisions and corresponding optimal pricing strategies for manufacturing enterprises and how to design operational mechanisms for platforms from a sustainable operations perspective is important, urgent, and promising. In other words, the aims of this paper are to explore the behaviors of the overcapacity manufacturer and capacity supplier in traditional and sharing manufacturing environments and the ...

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“…Li et al [7] proposed an intelligent search and matching method for CMfg services based on a formal description of CMfg services. Xue et al [8][9] proposed a computational experiment-based evaluation framework to analyze the evolution of manufacturing service ecosystems, which can simulate all kinds of actual scenarios to verify the performance of service matching strategies. Joseph et al [10] formulated the resource allocation problem as a bipartite matching problem and analyzed four bipartite matching mechanisms, namely, deferred acceptance (DA), top trading cycle (TTC), Munkres, and FCFS, with respect to the desired properties of the mechanisms, such as individual rationality, stability, strategy proofness, consistency, monotonicity and Pareto efficiency.…”

Section: Introductionmentioning

confidence: 99%

A Comparative Study on the Impact of One-Way and Two-Way Matching Strategies on the Evolution of Cloud Manufacturing Ecosystems

et al. 2021

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The supply-demand matching (SDM) strategy is an important part of the transaction mechanism design of cloud manufacturing (CMfg) platforms, which has a significant impact on the evolution trend of cloud manufacturing ecosystems (CMEs). To help CMfg platform operators choose the appropriate SDM strategy, first, the evolution process of the CME was qualitatively analyzed, and the evolution process was divided into three stages: the germination period, the growth period and the stable period. Then, three types of market agent behavior models, service demanders (SDs), service providers (SPs) and platform operators (POs), were established, and a multiagent behavior simulation experiment was conducted. Finally, the evolution of CMEs with one-way and two-way SDM strategies for POs was compared and analyzed from three aspects: the overall utilization rate of SPs, the diversity of CMEs and the total output of CMEs. Simulation experiments show that, compared with the CME that adopts the one-way SDM strategy, the CME that adopts the two-way SDM strategy is approximately 33% faster to reach ecological balance, the overall utilization rate is approximately 98.7% higher, the diversity is approximately 6% higher, and the total output is approximately 91% higher. The two-way SDM strategy that comprehensively considers the respective preferences of SDs and SPs is more conducive to the healthy development of CMEs.

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Evaluating of dynamic service matching strategy for social manufacturing in cloud environment

Cited by 37 publications

References 30 publications

Understanding Data-Driven Cyber-Physical-Social System (D-CPSS) Using a 7C Framework in Social Manufacturing Context

Understanding Data-Driven Cyber-Physical-Social System (D-CPSS) Using a 7C Framework in Social Manufacturing Context

Channel Selection and Pricing Decisions Considering Three Charging Modes of Production Capacity Sharing Platform: A Sustainable Operations Perspective

A Comparative Study on the Impact of One-Way and Two-Way Matching Strategies on the Evolution of Cloud Manufacturing Ecosystems

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