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Artificial Intelligence on the Shop Floor: A Comprehensive Review of Literature

https://doi.org/10.2139/ssrn.6098259
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Inferred edges come from two machine sources: sweeps of open repository metadata (mostly SSRN and Zenodo), and a bulk OpenAlex citation snapshot. Every row below is labelled with the one it came from. Neither is a complete citation index — absence here is not evidence of absence.

1 of the 45 references listed on this page is in the Retraction Watch database as retracted (export 2026-11-11): 10.1371/journal.pone.0253428 (notice 2024-05-08).

Dataset join, best-effort; this page does not check the publisher record. Retraction Watch data via Crossref Labs, used with credit; OpenCitations Index (CC0) and Meta (CC BY 4.0); dataset doi:10.7910/DVN/WT8VOA (CC BY 4.0).

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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/s00521-021-05848-4openalex-snapshot
Reinforcement learning methods based on GPU accelerated industrial control hardware
inferredcites →https://doi.org/10.1007/s10994-021-06065-9openalex-snapshot
Generating probabilistic safety guarantees for neural network controllers
inferredcites →https://doi.org/10.1007/s11554-017-0702-7openalex-snapshot
Suitability of GPUs for real-time control of large astronomical adaptive optics instruments
inferredcites →https://doi.org/10.1016/j.comnet.2021.108338openalex-snapshot
Performance evaluation of CoAP and MQTT with security support for IoT environments
inferredcites →https://doi.org/10.1016/j.csi.2013.06.004openalex-snapshot
Analysis of OPC UA performances
inferredcites →https://doi.org/10.1016/j.future.2024.107645openalex-snapshot
Secure integration of 5G in industrial networks: State of the art, challenges and opportunities
inferredcites →https://doi.org/10.1016/j.ifacol.2024.07.365openalex-snapshot
From Detection to Action: Implementing Deep Learning Inference in PLC Systems via Docker Services
inferredcites →https://doi.org/10.1016/j.mfglet.2022.07.016openalex-snapshot
Streaming Machine Generated Data via the MQTT Sparkplug B Protocol for Smart Factory Operations
inferredcites →https://doi.org/10.1016/j.procir.2023.06.024openalex-snapshot
A Hybrid, Distributed Condition Monitoring System using MEMS Microphones, Artificial Neural Networks, and Cloud Computing
inferredcites →https://doi.org/10.1016/j.procs.2021.01.171openalex-snapshot
Implications of embedded artificial intelligence - machine learning on safety of machinery
inferredcites →https://doi.org/10.1017/err.2023.1openalex-snapshot
Risk Management in the Artificial Intelligence Act
inferredcites →https://doi.org/10.1108/imds-07-2021-0419openalex-snapshot
Artificial intelligence in safety-critical systems: a systematic review
inferredcites →https://doi.org/10.1109/etfa.2018.8502479openalex-snapshot
Open Source OPC UA PubSub Over TSN for Realtime Industrial Communication
inferredcites →https://doi.org/10.1109/icit.2019.8755050openalex-snapshot
OPC UA versus ROS, DDS, and MQTT: Performance Evaluation of Industry 4.0 Protocols
inferredcites →https://doi.org/10.1109/incit60207.2023.10413160openalex-snapshot
Performance Evaluation of OPC UA and MQTT for ETAT Smart Lab (ESL)
inferredcites →https://doi.org/10.1109/les.2019.2953253openalex-snapshot
A Safe, Secure, and Predictable Software Architecture for Deep Learning in Safety-Critical Systems
inferredcites →https://doi.org/10.1109/mc.2023.3236523openalex-snapshot
On Neural Networks Redundancy and Diversity for Their Use in Safety-Critical Systems
inferredcites →https://doi.org/10.1109/percom59722.2024.10494460openalex-snapshot
Adopting User-Space Networking for DDS Message-Oriented Middleware
inferredcites →https://doi.org/10.1109/tii.2016.2530404openalex-snapshot
RESTful Industrial Communication With OPC UA
inferredcites →https://doi.org/10.1145/2168260.2168268openalex-snapshot
FORMS
inferredcites →https://doi.org/10.1145/3297663.3309670openalex-snapshot
Bottleneck Identification and Performance Modeling of OPC UA Communication Models
inferredcites →https://doi.org/10.1145/3444692openalex-snapshot
A Survey on Edge Performance Benchmarking
inferredcites →https://doi.org/10.1145/3549526openalex-snapshot
GPU Devices for Safety-Critical Systems: A Survey
inferredcites →https://doi.org/10.1145/3695248openalex-snapshot
Time-Sensitive Networking (TSN) for Industrial Automation: Current Advances and Future Directions
inferredcites →https://doi.org/10.11591/ijres.v12.i1.pp135-148openalex-snapshot
Cloud-based control systems: a systematic literature review
inferredcites →https://doi.org/10.1371/journal.pone.0253428openalex-snapshot
A security technology of power relay using edge computing
inferredcites →https://doi.org/10.14445/22315381/ijett-v73i1p110openalex-snapshot
Latency Analysis of WebSocket and Industrial Protocols in Real-Time Digital Twin Integration
inferredcites →https://doi.org/10.21014/acta_imeko.v8i2.648openalex-snapshot
On the performance of OPC UA and MQTT for data exchange between industrial plants and cloud servers
inferredcites →https://doi.org/10.21595/jmai.2024.24656openalex-snapshot
Experimental optimal control of servo-pneumatic with sliding mode and GA-fuzzy-PID-PWM
inferredcites →https://doi.org/10.23919/ecc55457.2022.9838217openalex-snapshot
On feedforward control using physics–guided neural networks: Training cost regularization and optimized initialization
inferredcites →https://doi.org/10.23919/iccas50221.2020.9268300openalex-snapshot
Impact Force Minimization Algorithm for Collaborative Robots Using Impact Force Prediction Model
inferredcites →https://doi.org/10.3389/fpace.2024.1475139openalex-snapshot
ML meets aerospace: challenges of certifying airborne AI
inferredcites →https://doi.org/10.3390/a11050065openalex-snapshot
Control Strategy of Speed Servo Systems Based on Deep Reinforcement Learning
inferredcites →https://doi.org/10.3390/automation6030037openalex-snapshot
Enabling Intelligent Industrial Automation: A Review of Machine Learning Applications with Digital Twin and Edge AI Integration
inferredcites →https://doi.org/10.3390/computers11050065openalex-snapshot
Comparison of REST and GraphQL Interfaces for OPC UA
inferredcites →https://doi.org/10.3390/iot3040027openalex-snapshot
Performance Analysis of OPC UA for Industrial Interoperability towards Industry 4.0
inferredcites →https://doi.org/10.3390/machines12070462openalex-snapshot
Cloud-Based Remote Real-Time Monitoring and Control System for Spring Fatigue Testing Machine
inferredcites →https://doi.org/10.3390/math13193066openalex-snapshot
Hybrid Adaptive MPC with Edge AI for 6-DoF Industrial Robotic Manipulators
inferredcites →https://doi.org/10.3390/s20226441openalex-snapshot
Edge-Computing Architectures for Internet of Things Applications: A Survey
inferredcites →https://doi.org/10.3390/s21227760openalex-snapshot
DDS and OPC UA Protocol Coexistence Solution in Real-Time and Industry 4.0 Context Using Non-Ideal Infrastructure
inferredcites →https://doi.org/10.3390/s25020537openalex-snapshot
Integrating Machine Learning for Predictive Maintenance on Resource-Constrained PLCs: A Feasibility Study
inferredcites →https://doi.org/10.3390/sym16121573openalex-snapshot
GRouteNet: A GNN-Based Model to Optimize Pathfinding and Smart Charging Management for Autonomous Guided Vehicles
inferredcites →https://doi.org/10.5220/0009907001430150openalex-snapshot
Performance Analysis of AMQP Protocol for Patient Health Data in IoT Case
inferredcites →https://doi.org/10.5220/0012683600003687openalex-snapshot
Exploring the Impact of Dataset Accuracy on Machinery Functional Safety: Insights from an AI-Based Predictive Maintenance System
inferredcites →https://doi.org/10.5220/0013142000003928openalex-snapshot
Optimising IIoT Control Systems at Demcon: Integrating MQTT, Sparkplug B, and ISA-88 for Unified Automation
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