ReviewSensors (Basel, Switzerland)2021
A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics.
Review in Sensors (Basel, Switzerland), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
21 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Human-Centric Digital Twins in Industry: A Comprehensive Review of Enabling Technologies and Implementation Strategies.Sensors (Basel, Switzerland) · 2023Pooled it
- Industry 4.0: A Proposal of Paradigm Organization Schemes from a Systematic Literature Review.Sensors (Basel, Switzerland) · 2021Pooled it
- Trajectory Planning for a Spraying Robotic Arm Using a Digital Twin and an Improved SAC Algorithm.Sensors (Basel, Switzerland) · 2026Article
- Digital twin- enabled intelligent HMI for real-time industrial automation systems.Scientific reports · 2026Article
- An Integrated Cyber-Physical Digital Twin Architecture with Quantitative Feedback Theory Robust Control for NIS2-Aligned Industrial Robotics.Sensors (Basel, Switzerland) · 2026Article
- Artificial Intelligence in Pharmaceutical Drug Development: Transforming Formulation and Innovation.Current drug discovery technologies · 2026Review
- AI-Driven Digital Twins for Manufacturing: A Review Across Hierarchical Manufacturing System Levels.Sensors (Basel, Switzerland) · 2025Review
- Methodology and pilot implementation of modular educational-development platform for Interoperable Digital Twin.Scientific reports · 2025Article
- Smart Manufacturing for High-Performance Materials: Advances, Challenges, and Future Directions.Materials (Basel, Switzerland) · 2025Review
- Autonomous Navigation of Mobile Robots: A Hierarchical Planning-Control Framework with Integrated DWA and MPC.Sensors (Basel, Switzerland) · 2025Article
- Digital twin for personalized medicine development.Frontiers in digital health · 2025Review
- Article
- Artificial Intelligence in Medical Metaverse: Applications, Challenges, and Future Prospects.Current medical science · 2024Review
- Special Issue: Artificial Intelligence and Smart Sensor-Based Industrial Advanced Technology.Sensors (Basel, Switzerland) · 2024Article
- Artificial Intelligence (AI) Applications in Drug Discovery and Drug Delivery: Revolutionizing Personalized Medicine.Pharmaceutics · 2024Review
- Towards a Human-Centric Digital Twin for Human-Machine Collaboration: A Review on Enabling Technologies and Methods.Sensors (Basel, Switzerland) · 2024Review
- Innovative Metaheuristic Optimization Approach with a Bi-Triad for Rehabilitation Exoskeletons.Sensors (Basel, Switzerland) · 2024Article
- The impact of digital twins on the evolution of intelligent manufacturing and Industry 4.0.Advances in computational intelligence · 2023Article
- Hybrid Virtual Commissioning of a Robotic Manipulator with Machine Vision Using a Single Controller.Sensors (Basel, Switzerland) · 2022Article
- Digital Twin and Smart Manufacturing in Industries: A Bibliometric Analysis with a Focus on Industry 4.0.Sensors (Basel, Switzerland) · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Digital twin (DT) and artificial intelligence (AI) technologies have grown rapidly in recent years and are considered by both academia and industry to be key enablers for Industry 4.0. As a digital replica of a physical entity, the basis of DT is the infrastructure and data, the core is the algorithm and model, and the application is the software and service. The grounding of DT and AI in industrial sectors is even more dependent on the systematic and in-depth integration of domain-specific expertise. This survey comprehensively reviews over 300 manuscripts on AI-driven DT technologies of Industry 4.0 used over the past five years and summarizes their general developments and the current state of AI-integration in the fields of smart manufacturing and advanced robotics. These cover conventional sophisticated metal machining and industrial automation as well as emerging techniques, such as 3D printing and human-robot interaction/cooperation. Furthermore, advantages of AI-driven DTs in the context of sustainable development are elaborated. Practical challenges and development prospects of AI-driven DTs are discussed with a respective focus on different levels. A route for AI-integration in multiscale/fidelity DTs with multiscale/fidelity data sources in Industry 4.0 is outlined.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.