Towards integrated digital twins for industrial products: Case study on an overhead crane

Juuso Autiosalo*, Riku Ala-Laurinaho, Joel Mattila, Miika Valtonen, Valtteri Peltoranta, Kari Tammi

*Corresponding author for this work

Research output: Contribution to journalArticleScientificpeer-review

8 Citations (Scopus)
80 Downloads (Pure)

Abstract

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The initial version of a digital twin for an overhead crane with the main focus on providing data for machine designers and maintainers to support decision making and additional features for operation.

Industrial Internet of Things practitioners are adopting the concept of digital twins at an accelerating pace. The features of digital twins range from simulation and analysis to real-time sensor data and system integration. Implementation examples of modeling-oriented twins are becoming commonplace in academic literature, but information management-focused twins that combine multiple systems are scarce. This study presents, analyzes, and draws recommendations from building a multi-component digital twin as an industry-university collaboration project and related smaller works. The objective of the studied project was to create a prototype implementation of an industrial digital twin for an overhead crane called "Ilmatar", serving machine designers and maintainers in their daily tasks. Additionally, related cases focus on enhancing operation. This paper describes two tools, three frameworks, and eight proof-of-concept prototypes related to digital twin development. The experiences show that good-quality Application Programming Interfaces (APIs) are significant enablers for the development of digital twins. Hence, we recommend that traditional industrial companies start building their API portfolios. The experiences in digital twin application development led to the discovery of a novel API-based business network framework that helps organize digital twin data supply chains.

Original languageEnglish
Article number683
Pages (from-to)1-35
Number of pages35
JournalApplied Sciences (Switzerland)
Volume11
Issue number2
DOIs
Publication statusPublished - 12 Jan 2021
MoE publication typeA1 Journal article-refereed

Keywords

  • API
  • Crane
  • Digital twins
  • Integration
  • Machine design
  • Maintenance
  • Open source
  • Operation

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