SmartQC: An Extensible DLT-Based Framework for Trusted Data Workflows in Smart Manufacturing (2402.17868v1)
Abstract: Recent developments in Distributed Ledger Technology (DLT), including Blockchain offer new opportunities in the manufacturing domain, by providing mechanisms to automate trust services (digital identity, trusted interactions, and auditable transactions) and when combined with other advanced digital technologies (e.g. machine learning) can provide a secure backbone for trusted data flows between independent entities. This paper presents an DLT-based architectural pattern and technology solution known as SmartQC that aims to provide an extensible and flexible approach to integrating DLT technology into existing workflows and processes. SmartQC offers an opportunity to make processes more time efficient, reliable, and robust by providing two key features i) data integrity through immutable ledgers and ii) automation of business workflows leveraging smart contracts. The paper will present the system architecture, extensible data model and the application of SmartQC in the context of example smart manufacturing applications.
- BigchainDB, Bigchaindb: The blockchain database. (2023). URL https://www.bigchaindb.com
- J. Kwon, Tendermint: Consensus without mining (2023). URL https://tendermint.com/static/docs/tendermint.pdf
- H. Community, Hyperledger fabric (2021). URL https://github.com/hyperledger/fabric
- I. Community, Iota (2023). URL https://www.iota.org,Online22/02/2023
Collections
Sign up for free to add this paper to one or more collections.
Paper Prompts
Sign up for free to create and run prompts on this paper using GPT-5.
