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Predictive maintenance is a key strategy for ensuring the reliability and efficiency of industrial systems. This study investigates the use of supervised learning models to diagnose the condition of electric motors, categorizing them as…

Machine Learning · Computer Science 2025-04-08 Amir Hossein Baradaran

In this paper we introduce a new model where the concept of condition-based maintenance is combined in a network setting with dynamic spare parts management. The model facilitates both preventive and corrective maintenance of geographically…

Optimization and Control · Mathematics 2020-04-07 Dmitrii Usanov , Peter van de Ven , Rob van der Mei

This survey note describes a brief systemic view to approaches for evaluation of hierarchical composite (modular) systems. The list of considered issues involves the following: (i) basic assessment scales (quantitative scale, ordinal scale,…

Artificial Intelligence · Computer Science 2013-05-22 Mark Sh. Levin

Automatic parameter tuning methods for planning algorithms, which integrate pipeline approaches with learning-based techniques, are regarded as promising due to their stability and capability to handle highly constrained environments. While…

Robotics · Computer Science 2025-03-25 Lu Wangtao , Wei Yufei , Xu Jiadong , Jia Wenhao , Li Liang , Xiong Rong , Wang Yue

The need for maintenance is based on the wear of components of machinery. If this need can be defined reliably beforehand so that no unpredicted failures take place then the maintenance actions can be carried out economically with mini-mum…

Signal Processing · Electrical Eng. & Systems 2019-04-01 Erkki Jantunen , Urko Zurutuza , Luis Lino Ferreira , Pal Varga

This paper presents a novel reinforcement learning (RL)-based planning scheme for optimized robotic management of biotic stresses in precision agriculture. The framework employs a hierarchical decision-making structure with conditional…

Prognostic Health Management aims to predict the Remaining Useful Life (RUL) of degrading components/systems utilizing monitoring data. These RUL predictions form the basis for optimizing maintenance planning in a Predictive Maintenance…

Applications · Statistics 2023-10-17 Antonios Kamariotis , Konstantinos Tatsis , Eleni Chatzi , Kai Goebel , Daniel Straub

This paper presents a novel architecture for model predictive control (MPC) based indoor climate control of multi-zone buildings to provide energy efficiency. Unlike prior works we do not assume the availability of a high-resolution…

Systems and Control · Electrical Eng. & Systems 2021-02-15 Naren Srivaths Raman , Rahul Umashankar Chaturvedi , Zhong Guo , Prabir Barooah

The macroscopic properties of materials that we observe and exploit in engineering application result from complex interactions between physics at multiple length and time scales: electronic, atomistic, defects, domains etc. Multiscale…

Linear-Rate Multi-Mode Systems is a model that can be seen both as a subclass of switched linear systems with imposed global safety constraints and as hybrid automata with no guards on transitions. We study the existence and design of a…

Formal Languages and Automata Theory · Computer Science 2013-02-19 Dominik Wojtczak

Statistical inference of the dependence between objects often relies on covariance matrices. Unless the number of features (e.g. data points) is much larger than the number of objects, covariance matrix cleaning is necessary to reduce…

Risk Management · Quantitative Finance 2021-06-09 Christian Bongiorno , Damien Challet

Condition-based and predictive maintenance enable early detection of critical system conditions and thereby enable decision makers to forestall faults and mitigate them. However, decision makers also need to take the operational and…

Multiagent Systems · Computer Science 2020-09-29 Pegah Rokhforoz , Blazhe Gjorgiev , Giovanni Sansavini , Olga Fink

Downtime of industrial assets such as wind turbines and medical imaging devices is costly. To avoid such downtime costs, companies seek to initiate maintenance just before failure, which is challenging because: (i) Asset failures are…

Optimization and Control · Mathematics 2024-01-10 Peter Verleijsdonk , Willem van Jaarsveld , Stella Kapodistria

The paper introduces a Data-driven Hierarchical Control (DHC) structure to improve performance of systems operating under the effect of system and/or environment uncertainty. The proposed hierarchical approach consists of two parts: 1) A…

Systems and Control · Electrical Eng. & Systems 2020-09-15 Lu Shi , Hanzhe Teng , Xinyue Kan , Konstantinos Karydis

In many engineering systems, proper predictive maintenance and operational control are essential to increase efficiency and reliability while reducing maintenance costs. However, one of the major challenges is that many sensors are used for…

Applications · Statistics 2025-12-09 Boyang Xu , Yunyi Kang , Xinyu Zhao , Hao Yan , Feng Ju

A high-speed train needs high-level maintenance when its accumulated running mileage or time reaches predefined threshold. The date of delivering an Electric Multiple Unit (EMU) train to maintenance ranges within a time window rather than…

Optimization and Control · Mathematics 2017-04-11 Boliang Lin , Ruixi Lin

Inspection and maintenance (I&M) planning involves sequential decision making under uncertainties and incomplete information, and can be modeled as a partially observable Markov decision process (POMDP). While single-agent deep…

Multiagent Systems · Computer Science 2026-03-13 Prateek Bhustali , Pablo G. Morato , Konstantinos G. Papakonstantinou , Charalampos P. Andriotis

Over the past decades, the performance design of closed-chain legged mechanisms (CLMs) has not been adequately addressed. Most existing design methodologies have predominantly relied on trajectory synthesis, which inadvertently prioritizes…

Computational Engineering, Finance, and Science · Computer Science 2025-03-11 Long Guo , Ying Zhang , Qi Qin , Guanjun Liu , Hanyu Chen , Yan-an Yao

High-precision CNC machining of free-form aerospace components requires bounded compensations informed by inspection, simulation, and process knowledge. Off-the-shelf large language model (LLM) assistants can generate text, but they do not…

To maximize its value, the design, development and implementation of Structural Health Monitoring (SHM) should focus on its role in facilitating decision support. In this position paper, we offer perspectives on the synergy between SHM and…