Dataset for Leveraging Blockchain to Improve Automotive Supply Chain Traceability

Published: 25 Mar 2019 | Version 2 | DOI: 10.17632/n24z7r2z28.2
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Description of this data

The data set contains support documents and file for the project: Leveraging Blockchain to Improve Automotive Supply Chain Traceability

Abstract -

The automotive industry worldwide seems to be spontaneously changing with supply chain improvement being one of the main focus areas along with cost reduction, process optimization and enhancing timely throughput. The general success parameter for achieving a better output in all the said focus areas is having an effective traceability system in place. Traceability for the automotive industry is a system documenting the genealogy of parts involved in manufacturing a specific product. Even with companies having an enormous amount of capital invested for perfecting their supply chain and achieving traceability, it is seen that they still have limited visibility and insight into their supply chain at a given instance. This study aims to leverage blockchain technology to eliminate inefficiencies of the conventional automotive supply chains for increasing transparency, streamlining processes and decentralizing network while providing stakeholders and companies with a host of value-adding features that ensure smoother and faster transaction. The study demonstrates the advantages of blockchain enabled automotive supply chain. Hyperledger Composer is used for deployment of the said network.

Experiment data files

Latest version

  • Version 2

    2019-03-25

    Published: 2019-03-25

    DOI: 10.17632/n24z7r2z28.2

    Cite this dataset

    Kulkarni, Soham; Kulkarni, Chaitanya (2019), “Dataset for Leveraging Blockchain to Improve Automotive Supply Chain Traceability”, Mendeley Data, v2 http://dx.doi.org/10.17632/n24z7r2z28.2

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Institutions

VIT University School of Mechanical Engineering

Categories

Industrial Engineering, Supply Chain Management, Automotive Industry, Global Supply Chain Strategies

Licence

CC BY 4.0 Learn more

The files associated with this dataset are licensed under a Creative Commons Attribution 4.0 International licence.

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This dataset is licensed under a Creative Commons Attribution 4.0 International licence. What does this mean? You can share, copy and modify this dataset so long as you give appropriate credit, provide a link to the CC BY license, and indicate if changes were made, but you may not do so in a way that suggests the rights holder has endorsed you or your use of the dataset. Note that further permission may be required for any content within the dataset that is identified as belonging to a third party.

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