Enhancing data quality and process optimization for smart manufacturing lines in industry 4.0 scenarios.

Simon Paasche, Sven Groppe

Abstract

An essential component of today's industry is data, which is generated during manufacturing. The goal of industry 4.0 is efficient collection, processing and analysis of this data. In our work, we address these three tasks and present an extensible system to solve them. To the best of our knowledge, the combination of a consistency checker (CC) for data preparation and a digital twin (DT) for analysis activities represents a novel approach. Consistency checking in combination with a DT leads to increased data quality, which in turn has a positive effect on analyses, like reducing errors to decrease costs, identifying relevant parameters to increase the productivity, and determining the bottleneck of a manufacturing line for enhanced production planning.
Original languageEnglish
Pages9:1-9:7
Number of pages7
DOIs
Publication statusPublished - 12.06.2022

Research Areas and Centers

  • Centers: Center for Artificial Intelligence Luebeck (ZKIL)
  • Research Area: Intelligent Systems

DFG Research Classification Scheme

  • 409-04 Operating, Communication, Database and Distributed Systems

Fingerprint

Dive into the research topics of 'Enhancing data quality and process optimization for smart manufacturing lines in industry 4.0 scenarios.'. Together they form a unique fingerprint.

Cite this