Maintenance Planning

Maintenance planning aims to optimize maintenance schedules and actions to minimize costs, downtime, and safety risks across diverse systems, from industrial machinery to infrastructure. Current research heavily utilizes machine learning, particularly deep reinforcement learning (DRL) and Bayesian neural networks, often coupled with advanced models like transformers and Monte Carlo tree search, to predict failures and develop proactive maintenance strategies. These data-driven approaches offer significant improvements over traditional methods by enabling more accurate predictions, cost-effective scheduling, and individualized maintenance plans tailored to specific asset characteristics, leading to enhanced operational efficiency and resource allocation.

Papers

November 7, 2024

LLM-R: A Framework for Domain-Adaptive Maintenance Scheme Generation Combining Hierarchical Agents and RAG
Laifa Tao, Qixuan Huang, Xianjun Wu, Weiwei Zhang, Yunlong Wu, Bin Li, Chen Lu, Xingshuo Hai
New Framework Medical LLM Retrieval Augmented Generation Predictive Maintenance Maintenance Required Hierarchical Agent Maintenance Planning Mixed Data

October 4, 2024

Consultation on Industrial Machine Faults with Large language Models
Apiradee Boonmee, Kritsada Wongsuwan, Pimchanok Sukjai
Fault Diagnosis Maintenance Planning

July 17, 2024

Maintenance Strategies for Sewer Pipes with Multi-State Degradation and Deep Reinforcement Learning
Lisandro A. Jimenez-Roa, Thiago D. Simão, Zaharah Bukhsh, Tiedo Tinga, Hajo Molegraaf, Nils Jansen, Marielle Stoelinga
Deep Reinforcement Learning Degradation Model Maintenance Planning Sewer Defect Degradation Pattern

May 6, 2024

Causal inference approach to appraise long-term effects of maintenance policy on functional performance of asphalt pavements
Lingyun You, Nanning Guo, Zhengwu Long, Fusong Wang, Chundi Si, Aboelkasim Diab
System Performance Causal Inference Maintenance Planning Asphalt Pavement Pavement Challenge Long Term Effect Pavement Performance

April 20, 2024

Revolutionizing System Reliability: The Role of AI in Predictive Maintenance Strategies
Michael Bidollahkhani, Julian M. Kunkel
Artificial Intelligence Integral Role Performance Improvement Predictive Maintenance Maintenance Planning System Reliability Computing Continuum

December 22, 2023

An investigation of belief-free DRL and MCTS for inspection and maintenance planning
Daniel Koutas, Elizabeth Bismut, Daniel Straub
Deep Reinforcement Learning Monte Carlo Tree Search Comprehensive Investigation Sequential Decision Belief State Visual Inspection Model Free Deep Reinforcement Learning Minimax McTs Maintenance Planning

December 16, 2023

Do Bayesian Neural Networks Improve Weapon System Predictive Maintenance?
Michael Potter, Miru Jun
Bayesian Neural Network Bayesian Inference Maintenance Planning Time Varying Covariates Right Censored Reliability Diagram

September 29, 2023

TranDRL: A Transformer-Driven Deep Reinforcement Learning Enabled Prescriptive Maintenance Framework
Yang Zhao, Jiaxi Yang, Wenbo Wang, Helin Yang, Dusit Niyato
Reinforcement Learning Deep Reinforcement Learning Transformer Model Predictive Maintenance Industrial Machine Maintenance Planning

July 19, 2023

A Decision Making Framework for Recommended Maintenance of Road Segments
Haoyu Sun, Yan Yan
New Framework Decision Relevant Information Maintenance Required Maintenance Planning Pavement Condition Road Segment Maintenance Decision

July 16, 2023

POMDP inference and robust solution via deep reinforcement learning: An application to railway optimal maintenance
Giacomo Arcieri, Cyprien Hoelzl, Oliver Schwery, Daniel Straub, Konstantinos G. Papakonstantinou, Eleni Chatzi
Reinforcement Learning Deep Reinforcement Learning Application Proficiency Markov Decision Process POMDP Policy Maintenance Planning Robust Solution POMDP Solver Continuous POMDP

July 7, 2023

Reinforcement and Deep Reinforcement Learning-based Solutions for Machine Maintenance Planning, Scheduling Policies, and Optimization
Oluwaseyi Ogunfowora, Homayoun Najjaran
Reinforcement Learning Optimization Purpose Deep Reinforcement Scheduling Policy Maintenance Planning

December 15, 2022

Bridging POMDPs and Bayesian decision making for robust maintenance planning under model uncertainty: An application to railway systems
Giacomo Arcieri, Cyprien Hoelzl, Oliver Schwery, Daniel Straub, Konstantinos G. Papakonstantinou, Eleni Chatzi
Markov Decision Process Model Uncertainty High Speed Train System Partially Observable Markov Decision Process POMDP Policy Maintenance Planning POMDP Solver Bayesian Decision

August 8, 2022

Dynamic Maintenance of Kernel Density Estimation Data Structure: From Practice to Theory
Jiehao Liang, Zhao Song, Zhaozhuo Xu, Junze Yin, Danyang Zhuo
Theoretical Understanding Practice Mode Kernel Density Kernel Function Maintenance Planning Adversarial Question

August 1, 2022

A Maintenance Planning Framework using Online and Offline Deep Reinforcement Learning
Zaharah A. Bukhsh, Nils Jansen, Hajo Molegraaf
Deep Reinforcement Learning Deep Q Learning Online Service Conservative Q Learning Offline Deep Reinforcement Learning Maintenance Planning

June 3, 2022

Prescriptive maintenance with causal machine learning
Toon Vanderschueren, Robert Boute, Tim Verdonck, Bart Baesens, Wouter Verbeke
Causal Machine Learning Maintenance Planning

May 30, 2022

Multi-Fault Diagnosis Of Industrial Rotating Machines Using Data-Driven Approach: A Review Of Two Decades Of Research
Shreyas Gawde, Shruti Patil, Satish Kumar, Pooja Kamat, Ketan Kotecha, Ajith Abraham
Narrative Review DH Research Data Driven Approach Smart Manufacturing Fault Diagnosis Industrial Machine Maintenance Planning

May 19, 2022

Predictive Maintenance using Machine Learning
Archit P. Kane, Ashutosh S. Kore, Advait N. Khandale, Sarish S. Nigade, Pranjali P. Joshi
Machine Learning Predictive Maintenance Industrial Machine Maintenance Planning

Maintenance Planning

Papers

LLM-R: A Framework for Domain-Adaptive Maintenance Scheme Generation Combining Hierarchical Agents and RAG

Consultation on Industrial Machine Faults with Large language Models

Maintenance Strategies for Sewer Pipes with Multi-State Degradation and Deep Reinforcement Learning

Causal inference approach to appraise long-term effects of maintenance policy on functional performance of asphalt pavements

Revolutionizing System Reliability: The Role of AI in Predictive Maintenance Strategies

An investigation of belief-free DRL and MCTS for inspection and maintenance planning

Do Bayesian Neural Networks Improve Weapon System Predictive Maintenance?

TranDRL: A Transformer-Driven Deep Reinforcement Learning Enabled Prescriptive Maintenance Framework

A Decision Making Framework for Recommended Maintenance of Road Segments

POMDP inference and robust solution via deep reinforcement learning: An application to railway optimal maintenance

Reinforcement and Deep Reinforcement Learning-based Solutions for Machine Maintenance Planning, Scheduling Policies, and Optimization

Bridging POMDPs and Bayesian decision making for robust maintenance planning under model uncertainty: An application to railway systems

Dynamic Maintenance of Kernel Density Estimation Data Structure: From Practice to Theory

A Maintenance Planning Framework using Online and Offline Deep Reinforcement Learning

Prescriptive maintenance with causal machine learning

Multi-Fault Diagnosis Of Industrial Rotating Machines Using Data-Driven Approach: A Review Of Two Decades Of Research

Predictive Maintenance using Machine Learning