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Related Experiment Video

Updated: Dec 20, 2025

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Data Handling in Industry 4.0: Interoperability Based on Distributed Ledger Technology.

Shengjing Sun1, Xiaochen Zheng1,2, Javier Villalba-Díez1,3,4

  • 1Escuela Técnica Superior de Ingenieros Industriales (ETSII), Universidad Politécnica de Madrid, José Gutiérrez Abascal 2, 28006 Madrid, Spain.

Sensors (Basel, Switzerland)
|May 31, 2020
PubMed
Summary
This summary is machine-generated.

This study enhances Industry 4.0 frameworks by integrating diverse data sources, including operator input, for improved information transparency and data fusion. A novel, encrypted data management solution ensures privacy and enables semantic data treatment for connected environments.

Keywords:
GDPRLASFA.RAMI 4.0digital twindistributed ledger technologyindustry 4.0interoperabilityreference architecture model

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Area of Science:

  • Industrial Engineering
  • Information Science
  • Computer Science

Background:

  • Industry 4.0 necessitates information-intensive transformation for connected processes, systems, and people.
  • Existing frameworks require enhancement to manage diverse knowledge sources and technological layers effectively.
  • Data interconnection and information transparency are critical for advanced manufacturing environments.

Purpose of the Study:

  • To propose an extension of an existing framework for enhanced data access and knowledge integration.
  • To develop an interoperability principle through a secure, public, and encrypted data management solution.
  • To ensure information transparency and enable semantic data treatment and data fusion, incorporating Privacy by Design.

Main Methods:

  • Framework extension incorporating knowledge access to diverse data sources, including operator data.
  • Development of a public and encrypted data management solution for information transparency.
  • Implementation of semantic data treatment and data fusion capabilities with Privacy by Design considerations.

Main Results:

  • The proposed framework extension facilitates access to heterogeneous data sources.
  • A secure data management solution was implemented, ensuring information transparency and enabling semantic analysis.
  • The system supports data fusion, providing context for improved decision-making.

Conclusions:

  • The enhanced framework improves knowledge integration and data interoperability in Industry 4.0.
  • The proposed data management solution effectively balances information transparency with privacy.
  • The application in construction logistics demonstrates the practical benefits of shared knowledge architecture.