A Blockchainbased Framework for Collaborative Production in Distributed and Social Manufacturing In recent years, novel collaborative production paradigms, such as (re)distributed manufacturing and social manufacturing, have attracted intensive attention due to their potential of further changing the existing manufacturing modes and industrial structures. Blockchain, as a new distributed computing architecture, is expected to be successfully used in manufacturing, and help solve issues related to interoperability and collaboration, security and supervision, marketization and protocol, democratic organization and global value chain governance, and so on. In this paper, a blockchainbased framework for collaborative production is proposed, aiming at providing novel ideas for the design, implementation and optimization of collaborative production, and also inspiring the upgrading and transformation of manufacturing industries.

Consensusoriented cloud manufacturing based on blockchain technology: An exploratory study Abstract   In the era of cloud computing and Industry 4.0, significant research efforts on cloud manufacturing have been witnessed in recent years. Nevertheless, challenges, such as issues of trust, safety, payment, remain in this emerging area, which cause less confidence for industry to adopt cloud manufacturing. In this regard, the recent development of blockchain technology provides a potential viable solution thanks to its unique advantages in decentralization and security. As such, we propose a new framework of cloud manufacturing by integrating the blockchain technology. In essence, consensusoriented mechanisms are employed to generate the operating standards for the blockchain cloud manufacturing model. Moreover, based on the open source Ethereum code, we construct a simulation case study for 3D printing services using the proposed framework. A consortium or federated blockchain is simulated which uses ProofofAuthority (PoA) as the consensus algorithm of block generation. The simulation involves 939 job requests from 100 users, as well as 10 service providers. The knearest neighbors (KNN) algorithm is employed to recommend the service provider for each request. The results show that the providerxe2x80x99s score of service evaluation tends to be stabilize, and 934 requests for service are successfully fulfilled by the appropriate providers while the remaining 5 requests fail to be serviced.