文章摘要
Martin Westerkamp,Friedhelm Victor,Axel Küpper.[J].重庆邮电大学新办英文刊,2020,(2):167-176
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Service-centric Networking, Telekom Innovation Laboratories, Technische Universitat Berlin, 10587, Berlin, Germany
Received: October 01, 2018  Revised: December 17, 2018
DOI:https://doi.org/10.1016/j.dcan.2019.01.007
中文关键词: 
英文关键词: Supply chain;Traceability;Blockchain;Distributed ledger technology;Smart contract
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AuthorInstitutionE-mail
Martin Westerkamp Tracing manufacturing processes using blockchain-based token compositions westerkamp@tu-berlin.de 
Friedhelm Victor Tracing manufacturing processes using blockchain-based token compositions  
Axel Küpper Tracing manufacturing processes using blockchain-based token compositions  
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中文摘要:
      
英文摘要:
      Supply chain traceability is one of the most promising use cases to benefit from characteristics of blockchain, such as decentralization, immutability and transparency, not required to build prior trust relationships among entities. A plethora of supply chain traceability solutions based on blockchain has been proposed recently. However, current systems are limited to tracing simple goods that have not been part of the manufacturing process. We recommend a method that allows for the traceability of manufactured goods, including their components. Products are represented using non-fungible digital tokens that are created on a blockchain for each batch of manufactured products. To create a link between a product and the components that are needed to produce it, we propose “token recipes” that define the amount of tokenized goods required for minting a new token. As input tokens are automatically and transparently consumed when creating a product token, the physical process of producing a new item out of existing components is projected onto the ledger. This ultimately leads to the complete traceability of goods, including the origin of inputs. Evaluating the performance of the system, we show that a prototypical implementation for the Ethereum Virtual Machine (EVM) scales linearly with the amount of the input and goods tracked.