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Enriching Analytics Models with Domain Knowledge for Smart Manufacturing Data Analysis.

Heng Zhang1, Utpal Roy1, Yung-Tsun Tina Lee2

  • 1Department of Mechanical and Aerospace Engineering, Syracuse University, Syracuse, NY, USA.

International Journal of Production Research
|December 11, 2020
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Summary
This summary is machine-generated.

This study introduces a method to integrate domain knowledge into data analytics models for Smart Manufacturing. Enriched models improve the efficiency of developing complex analytics, like Bayesian Networks.

Keywords:
Bayesian NetworkData AnalyticsDomain KnowledgeInteroperabilitySmart ManufacturingTraceability

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Area of Science:

  • Manufacturing Engineering
  • Data Science
  • Artificial Intelligence

Background:

  • Data analytics is crucial for decision-making in Smart Manufacturing.
  • Integrating domain knowledge into analytics models is challenging, leading to interoperability and traceability issues.
  • Current practices often leave domain knowledge undocumented or poorly integrated.

Purpose of the Study:

  • To propose a methodology for enriching analytics models with domain knowledge.
  • To address the limitations of current data analytics projects in Smart Manufacturing.
  • To enhance the integration and utilization of domain expertise in model development.

Main Methods:

  • Development of a novel methodology to enrich analytics models with domain knowledge.
  • Implementation of a case study to demonstrate the methodology's application.
  • Utilizing a Bayesian Network model for illustrating the enriched analytics approach.

Main Results:

  • The proposed methodology successfully enriches analytics models with domain knowledge.
  • The case study demonstrated the practical application and benefits of the enriched model.
  • Significant improvements in the efficiency of developing Bayesian Network models were observed.

Conclusions:

  • Enriching analytics models with domain knowledge is feasible and beneficial.
  • The methodology enhances interoperability and traceability of domain knowledge in analytics.
  • This approach improves the efficiency and effectiveness of data analytics in Smart Manufacturing.