Abstract
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.
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Reference64 articles.
1. IEEE Computer Society’s Top 12 Technology Trends for 2020
https://www.computer.org/press-room/2019-news/ieee-computer-societys-top-12-technology-trends-for-2020
2. Digital Twin: Mitigating Unpredictable, Undesirable Emergent Behavior in Complex Systems
3. DRAFT Modeling, Simulation, Information Technology & Processing Roadmap Technology Area 11;Shafto,2010
4. Digital twin-driven product design, manufacturing and service with big data
5. Digital Twin and Big Data Towards Smart Manufacturing and Industry 4.0: 360 Degree Comparison
Cited by
32 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献