A systematic survey on complex network visualization in industrial manufacturing and production

This paper presents a systematic survey of the visualization and visual analysis of complex networks as generated in studies on industrial manufacturing and production problems. We provide a description and categorization of the types of networks found in this area. We also investigate the concepts used for revealing structural properties needed to explore information relevant to industrial manufacturing and production. We discuss the requirements for visualizing complex networks in this domain so as to achieve a meaningful representation of industrial knowledge for different users. Additionally, we focus on immersive visualization for networks, due to its growing importance in recent years, as well as the wide range of opportunities that come with it. We highlight the distinct challenges associated with this area, which are primarily related to rendering, navigation, and interaction along the reality-virtuality continuum. Finally, a categorization into three types of layout algorithms is presented, allowing for intuitive and systematic visualization of complex and large networks. This provides insights beyond mere node and edge visualization by including key topological characteristics, measures, and comparative analysis methods. These algorithms enable fast optimization of the coordinates of the network vertices. This paper thus discusses the types of networks found in industrial manufacturing and production, their construction, as well as the visual exploration of respective networks, in order to explore such networks in terms of their structural properties using conventional and immersive visualization techniques.

Authors

Institutions

Publication Details

Journal
Applied Network Science
Published
2026-09-25
DOI
https://doi.org/10.1007/s41109-026-00834-y
Primary Topic
Data Visualization and Analytics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
article

A systematic survey on complex network visualization in industrial manufacturing and production

Bernhard Fröhler, Herbert Jodlbauer, Christoph Heinzl, Shailesh Tripathi
Applied Network Science
Data Visualization and Analytics
article

A systematic survey on complex network visualization in industrial manufacturing and production

Bernhard Fröhler, Herbert Jodlbauer, Christoph Heinzl, Shailesh Tripathi
article en

Abstract

This paper presents a systematic survey of the visualization and visual analysis of complex networks as generated in studies on industrial manufacturing and production problems. We provide a description and categorization of the types of networks found in this area. We also investigate the concepts used for revealing structural properties needed to explore information relevant to industrial manufacturing and production. We discuss the requirements for visualizing complex networks in this domain so as to achieve a meaningful representation of industrial knowledge for different users. Additionally, we focus on immersive visualization for networks, due to its growing importance in recent years, as well as the wide range of opportunities that come with it. We highlight the distinct challenges associated with this area, which are primarily related to rendering, navigation, and interaction along the reality-virtuality continuum. Finally, a categorization into three types of layout algorithms is presented, allowing for intuitive and systematic visualization of complex and large networks. This provides insights beyond mere node and edge visualization by including key topological characteristics, measures, and comparative analysis methods. These algorithms enable fast optimization of the coordinates of the network vertices. This paper thus discusses the types of networks found in industrial manufacturing and production, their construction, as well as the visual exploration of respective networks, in order to explore such networks in terms of their structural properties using conventional and immersive visualization techniques.

Applied Network Science
University of Passau (DE), Fraunhofer Institute for Integrated Circuits (DE), University of Applied Sciences Upper Austria (AT)
Industry, innovation and infrastructure
Openalex Percentile: Top 14%
Data Visualization and Analytics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.