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Journal articles on the topic 'Industrial multi-component systems'

Author: Grafiati

Published: 11 March 2023

Last updated: 31 July 2025

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1

Zhao, Jing Rui, Kai Ming Cheng, Yong Du, and Li Jun Zhang. "Thermodynamic Calculation of Liquidus Projection of Multiple Aluminum Alloys." Materials Science Forum 913 (February 2018): 589–95. http://dx.doi.org/10.4028/www.scientific.net/msf.913.589.

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Most aluminum alloys used in industrial manufacturing are multi-component systems. Unfortunately, multi-component systems are still lack of systematic research. The lack of research is especially evident for the liquidus surface projection of the multi-component system where most of the projections are currently drawn by hand. Thermodynamic calculations were performed for the Al–Cu–Mg–Mn quaternary system and the A1–Cu–Fe–Mg–Mn quinary system. The temperatures and compositions of the liquidus invariant reactions in the A1–rich corner for the two systems were calculated and compared with the ex

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2

Sanieva, Alina D. "CONTROL ALGORITHMS FOR MULTI-COMPONENT ELECTRIC DRIVE SYSTEMS." EKONOMIKA I UPRAVLENIE: PROBLEMY, RESHENIYA 11/9, no. 152 (2024): 11–17. https://doi.org/10.36871/ek.up.p.r.2024.11.09.002.

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The article is devoted to modern control algorithms for multi-component electric drive systems aimed at improving accuracy, reliability and energy efficiency. Basic control prin-ciples, such as synchronization and load distribution between drives, as well as more advanced methods - predictive, adaptive and distributed control are considered. Particular attention is paid to intelligent approaches using neural networks and machine learning algorithms to improve stability and optimize system operation. The prospects for integration with digital twins and the Industrial Internet of Things (IIoT),

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3

Bucaioni, Alessio, Saad Mubeen, Federico Ciccozzi, Antonio Cicchetti, and Mikael Sjödin. "Modelling multi-criticality vehicular software systems: evolution of an industrial component model." Software and Systems Modeling 19, no. 5 (2020): 1283–302. http://dx.doi.org/10.1007/s10270-020-00795-5.

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Abstract Software in modern vehicles consists of multi-criticality functions, where a function can be safety-critical with stringent real-time requirements, less critical from the vehicle operation perspective, but still with real-time requirements, or not critical at all. Next-generation autonomous vehicles will require higher computational power to run multi-criticality functions and such a power can only be provided by parallel computing platforms such as multi-core architectures. However, current model-based software development solutions and related modelling languages have not been desig

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4

Hashemniya, Fatemeh, Erik Frisk, and Mattias Krysander. "Hierarchical Diagnosis Algorithm for Component-Based Multi-Mode Systems." IFAC-PapersOnLine 56, no. 2 (2023): 11317–23. http://dx.doi.org/10.1016/j.ifacol.2023.10.413.

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5

Ul Haque, Fahim, Aizizul Haque Raza, and Dr Md Mosharraf Hossain. "Optimizing Maintenance Cost in A Multi Component Environment." International Journal of Scientific and Management Research 08, no. 01 (2025): 99–120. https://doi.org/10.37502/ijsmr.2025.8105.

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This research presents a cost-centric approach to maintenance scheduling in multi-component systems, aimed at minimizing expenses while optimizing operational efficiency. By integrating predictive analytics and optimization techniques, we conduct a comprehensive analysis of production loss costs for diverse maintenance sequences, employing genetic algorithms to identify the most cost-effective strategy. Through rigorous exploratory data analysis, we refine our model and demonstrate its efficacy in achieving significant cost savings. A comparative case study showcases substantial reductions in

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Assaf, Roy, Phuc Do, Samia Nefti-Meziani, and Philip Scarf. "Wear rate–state interactions within a multi-component system: a study of a gearbox-accelerated life testing platform." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 232, no. 4 (2018): 425–34. http://dx.doi.org/10.1177/1748006x18764061.

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The degradation process of complex multi-component systems is highly stochastic in nature. A major side effect of this complexity is that components of such systems may have unexpected reduced life and faults and failures that decrease the reliability of multi-component systems in industrial environments. In this work, we provide maintenance practitioners with an explanation of the nature of some of these unpredictable events, namely, the degradation interactions that take place between components. We begin by presenting a general wear model where the degradation process of a component may be

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7

Niu, Gang, and Junjie Jiang. "Prognostic control-enhanced maintenance optimization for multi-component systems." Reliability Engineering & System Safety 168 (December 2017): 218–26. http://dx.doi.org/10.1016/j.ress.2017.04.011.

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Kramer, Vivian, and Annemarie Reimschuessel. "Characterization of multi-component polymer blends by multi-step staining techniques." Proceedings, annual meeting, Electron Microscopy Society of America 46 (1988): 930–31. http://dx.doi.org/10.1017/s0424820100106715.

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Morphology is one of the important parameters that affects polymer properties and performance. A standard procedure used when characterizing the morphology of many polymer blends by TEM is to stain one of the components with a heavy element rendering it opaque to the electron beam. Among the more common stains used are phosphotungstic acid (PTA) for nylon and OSO4 for unsaturated rubbers. Although these stains work well for simple two component systems, innovative techniques are often essential when the material contains three or more phases, as necessitated by ever expanding industrial demand

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Park, Jong-Kweon, Seung-Kook Ro, Byung-Sub Kim, Woo-Cheol Shin, and Hyeon-Hwa Lee. "Precision Component Technologies for Microfactory Systems Developed at KIMM." International Journal of Automation Technology 4, no. 2 (2010): 127–37. http://dx.doi.org/10.20965/ijat.2010.p0127.

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This paper presents some of the recent research activities in the ongoing project for the development of high-tech component technologies for Microfactories at the Korea Institute of Machinery and Materials. Component technologies for Microfactory systems are key technologies for future development in this area, both in the R&D and industrial sectors, since many components are not currently available on the market. In this project, some key component technologies for Microfactory systems were chosen for development: multi-axis miniature air-bearing stages (including a planar motion stage),

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Adjoul, Oussama, Khaled Benfriha, Chawki El Zant, and Améziane Aoussat. "Algorithmic Strategy for Simultaneous Optimization of Design and Maintenance of Multi-Component Industrial Systems." Reliability Engineering & System Safety 208 (April 2021): 107364. http://dx.doi.org/10.1016/j.ress.2020.107364.

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11

Si, Shubin, Gregory Levitin, Hongyan Dui, and Shudong Sun. "Component state-based integrated importance measure for multi-state systems." Reliability Engineering & System Safety 116 (August 2013): 75–83. http://dx.doi.org/10.1016/j.ress.2013.02.023.

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12

Van Horenbeek, Adriaan, and Liliane Pintelon. "A dynamic predictive maintenance policy for complex multi-component systems." Reliability Engineering & System Safety 120 (December 2013): 39–50. http://dx.doi.org/10.1016/j.ress.2013.02.029.

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13

Zhu, Zhicheng, and Yisha Xiang. "Condition-based maintenance for multi-component systems: Modeling, structural properties, and algorithms." IISE Transactions 53, no. 1 (2020): 88–100. http://dx.doi.org/10.1080/24725854.2020.1741740.

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14

Fu, Yichuan, Zhiwei Gao, Yuanhong Liu, Aihua Zhang, and Xiuxia Yin. "Actuator and Sensor Fault Classification for Wind Turbine Systems Based on Fast Fourier Transform and Uncorrelated Multi-Linear Principal Component Analysis Techniques." Processes 8, no. 9 (2020): 1066. http://dx.doi.org/10.3390/pr8091066.

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In response to the high demand of the operation reliability and predictive maintenance, health monitoring and fault diagnosis and classification have been paramount for complex industrial systems (e.g., wind turbine energy systems). In this study, data-driven fault diagnosis and fault classification strategies are addressed for wind turbine energy systems under various faulty scenarios. A novel algorithm is addressed by integrating fast Fourier transform and uncorrelated multi-linear principal component analysis techniques in order to achieve effective three-dimensional space visualization for

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15

Zinicovscaia, Inga, Alexey Safonov, Varvara Tregubova, et al. "Uptake of Metals from Single and Multi-Component Systems by Spirulina Platensis Biomass." Ecological Chemistry and Engineering S 23, no. 3 (2016): 401–12. http://dx.doi.org/10.1515/eces-2016-0028.

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Abstract Spirulina platensis biomass is widely applied for different technological purposes. The process of lanthanum, chromium, uranium and vanadium accumulation and biosorption by Spirulina platensis biomass from single- and multi-component systems was studied. The influence of multi-component system on the spirulina biomass growth was less pronounced in comparison with the single-component ones. To trace the uptake of metals by spirulina biomass the neutron activation analysis was used. In the experiment on the accumulation the efficiency of studied metal uptake changes in the following ord

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16

Eppert, Joseph J., Richard E. DeVor, Shiv G. Kapoor, and N. Rajagopalan. "The Effect of Chip Adsorption on Selective Depletion From a Multi-Component Synthetic Metalworking Fluid." Journal of Manufacturing Science and Engineering 125, no. 4 (2003): 703–8. http://dx.doi.org/10.1115/1.1615794.

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Certain components found in metalworking fluid formulations are known to be prone to selective depletion via adsorption onto the surfaces of particulate generated during metal cutting operations. The characteristics of adsorption for a multi-component synthetic metalworking fluid are investigated in order to determine the affect that machining particulate contamination has on component depletion from this fluid. Experimental measurements indicate that the corrosion inhibiting component of the formulation is especially prone to depletion via the adsorption mechanism. A Langmuir isotherm/mass ba

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Johny, Joyal, and Suraj Gupta. "(Invited) Multi-Component Electrocatalysts for Pure and Seawater Electrolysis." ECS Meeting Abstracts MA2025-01, no. 10 (2025): 882. https://doi.org/10.1149/ma2025-0110882mtgabs.

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The green hydrogen revolution is driven by the advancements in water electrolysis technology, starting from alkaline water electrolyzers to proton-exchange membrane water electrolyzers and the latest anion-exchange membrane water electrolyzers (AEMWEs). The key component in all these technologies are the electrodes where the actual water-splitting takes place. To improve the electrolyzer efficiencies, designing new electrocatalysts with improved performance (lower hydrogen and oxygen evolution overpotentials) and stability (thousands of hours) at sufficiently high current densities is essentia

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18

Elnur Ahmadzade, Bahram Ismayılov, Elnur Ahmadzade, Bahram Ismayılov. "WAVELET SIGNAL DENOISING: IMPROVED MULTI-SCALE PRINCIPAL ANALYSIS." PAHTEI-Procedings of Azerbaijan High Technical Educational Institutions 49, no. 02 (2025): 179–89. https://doi.org/10.36962/pahtei49022025-179.

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This study presents a fault diagnosis method and system designed to overcome the challenges associated with noise and randomness in process data using an improved wavelet threshold denoising technique. Modern industrial systems have become increasingly complex, necessitating accurate and timely fault detection to ensure production stability and safety. While Principal Component Analysis (PCA) has been a popular multivariate statistical technique for handling high-dimensional, noisy, and highly correlated data, its single-scale limitation restricts its effectiveness in analyzing multi-scale pro

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19

Bian, Linkan, and Nagi Gebraeel. "Stochastic modeling and real-time prognostics for multi-component systems with degradation rate interactions." IIE Transactions 46, no. 5 (2014): 470–82. http://dx.doi.org/10.1080/0740817x.2013.812269.

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20

Islam, Mohammad Ariful, Md Serajul Islam, and Shifat Jahan. "Multi-cycle Deadlock Detection Algorithm for Distributed Systems." Asian Journal of Applied Science and Engineering 5, no. 1 (2016): 125–32. http://dx.doi.org/10.18034/ajase.v5i1.72.

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Deadlock handling is an important component of transaction management in a database system. Though a lot of works have already done for deadlock detection on distributed system. This paper proposes a multi-cycle deadlock detection and recovery mechanism. Our proposed algorithm has modified the probe based distributed algorithm for deadlock detection such as CMH algorithm. But CMH algorithm had some limitation. It can only detect single cycle. But some situation a node is responsible for multi-cycle deadlock detection. In this situation, it can’t detect Multi-cycle deadlock. Besides it can only

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21

Dinh, Duc-Hanh, Phuc Do, and Benoit Iung. "Multi-level opportunistic predictive maintenance for multi-component systems with economic dependence and assembly/disassembly impacts." Reliability Engineering & System Safety 217 (January 2022): 108055. http://dx.doi.org/10.1016/j.ress.2021.108055.

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22

Zaretalab, Arash, Vahid Hajipour, and Madjid Tavana. "Redundancy allocation problem with multi-state component systems and reliable supplier selection." Reliability Engineering & System Safety 193 (January 2020): 106629. http://dx.doi.org/10.1016/j.ress.2019.106629.

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23

Wang, Cheng, Jianxin Xu, Hongjun Wang, and Zhenming Zhang. "A criticality importance-based spare ordering policy for multi-component degraded systems." Eksploatacja i Niezawodnosc - Maintenance and Reliability 20, no. 4 (2018): 662–70. http://dx.doi.org/10.17531/ein.2018.4.17.

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24

Song, Zhihao. "Stacked denoised auto-encoding network-based kernel principal component analysis for cyber physical systems intrusion detection in business management." Computer Science and Information Systems, no. 00 (2024): 55. http://dx.doi.org/10.2298/csis240314055s.

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At present, the network data under the environment of industrial information physical system is larger and more complex. Traditionally, feature extraction by machine learning is cumbersome and computation-intensive, which is not conducive to anomaly detection of industrial network data. To solve the above problems, this paper proposes a stacked denoised auto-encoding network based on kernel principal component analysis for industrial cyber physical systems intrusion detection. Firstly, a novel kernel principal component analysis method is used to reduce the data feature dimension and obtain a

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25

Rath, Markus, and Ernst Kozeschnik. "Coupled Grain Growth and Precipitation Modeling in Multi-Phase Systems." Materials Science Forum 753 (March 2013): 357–60. http://dx.doi.org/10.4028/www.scientific.net/msf.753.357.

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In this work, we utilize recent software for precipitation kinetics simulation and couple it with models for grain growth. Basis of our studies is the thermo-kinetic software MatCalc, which has been designed for simulation of the evolution of precipitates in general multi-component multi-phase alloy systems. Grain growth approaches of different complexity are incorporated into the precipitation kinetics framework, investigated with respect to their coupling behavior with precipitation and precipitate dissolution and, finally, benchmarked on typical grain growth problems of industrial practice.

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26

Barata, J., C. Guedes Soares, M. Marseguerra, and E. Zio. "Simulation modelling of repairable multi-component deteriorating systems for ‘on condition’ maintenance optimisation." Reliability Engineering & System Safety 76, no. 3 (2002): 255–64. http://dx.doi.org/10.1016/s0951-8320(02)00017-0.

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27

Karabağ, Oktay, Önder Bulut, Ayhan Özgür Toy, and Mehmet Murat Fadıloğlu. "An efficient procedure for optimal maintenance intervention in partially observable multi-component systems." Reliability Engineering & System Safety 244 (April 2024): 109914. http://dx.doi.org/10.1016/j.ress.2023.109914.

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28

You, Ming-Yi, and Guang Meng. "A modularized framework for predictive maintenance scheduling." Proceedings of the Institution of Mechanical Engineers, Part O: Journal of Risk and Reliability 226, no. 4 (2011): 380–91. http://dx.doi.org/10.1177/1748006x11431209.

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This paper presents a modularized, easy-to-implement framework for predictive maintenance scheduling. With a modularization treatment of a maintenance scheduling model, a predictive maintenance scheduling model can be established by integrating components’ real-time, sensory-updated prognostics information with a classical preventive maintenance/condition-based maintenance scheduling model. With the framework, a predictive maintenance scheduling model for multi-component systems is established to illustrate the framework’s use; such a predictive maintenance scheduling model for multi-component

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29

Qin, Bo, and Wei Ren. "A Full-Stack Systems Engineering Framework for Complex Systems-of-Systems Simulation." Science Innovation 13, no. 3 (2025): 26–32. https://doi.org/10.11648/j.si.20251303.12.

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This paper presents a comprehensive full-stack systems engineering framework designed to enhance the adaptability, scalability, and interoperability of complex systems across various domains, including defense, transportation, and industrial automation. The proposed framework is organized into five interconnected layers: the Task Layer, which defines mission objectives and stakeholder needs; the System Architecture Layer, which captures high-level system behavior and structural decomposition; the Subsystem Layer, responsible for modeling domain-specific subsystems; the Component Layer, which e

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30

Liu, Qinming, and Wenyuan Lv. "Multi-component manufacturing system maintenance scheduling based on degradation information using genetic algorithm." Industrial Management & Data Systems 115, no. 8 (2015): 1412–34. http://dx.doi.org/10.1108/imds-04-2015-0150.

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Purpose – The traditional maintenance scheduling strategies of multi-component systems may result in maintenance shortage or overage, while system degradation information is often ignored. The purpose of this paper is to propose a multi-phase model that better integrates degradation information, dependencies and maintenance at the tactical level. Design/methodology/approach – This paper proposes first a maintenance optimization model for multi-component systems with economic dependence and structural dependence. The cost of combining maintenance activities is lower than that of performing main

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31

Chang, Fengtian, Guanghui Zhou, Chao Zhang, Zhongdong Xiao, and Chuang Wang. "A service-oriented dynamic multi-level maintenance grouping strategy based on prediction information of multi-component systems." Journal of Manufacturing Systems 53 (October 2019): 49–61. http://dx.doi.org/10.1016/j.jmsy.2019.09.005.

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32

Kim, Mi-Young, Shahin Atakishiyev, Housam Khalifa Bashier Babiker, et al. "A Multi-Component Framework for the Analysis and Design of Explainable Artificial Intelligence." Machine Learning and Knowledge Extraction 3, no. 4 (2021): 900–921. http://dx.doi.org/10.3390/make3040045.

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The rapid growth of research in explainable artificial intelligence (XAI) follows on two substantial developments. First, the enormous application success of modern machine learning methods, especially deep and reinforcement learning, have created high expectations for industrial, commercial, and social value. Second, the emerging and growing concern for creating ethical and trusted AI systems, including compliance with regulatory principles to ensure transparency and trust. These two threads have created a kind of “perfect storm” of research activity, all motivated to create and deliver any s

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33

Liao, Hung-Chang. "Multi-response optimization using weighted principal component." International Journal of Advanced Manufacturing Technology 27, no. 7-8 (2005): 720–25. http://dx.doi.org/10.1007/s00170-004-2248-7.

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34

Piotter, V., J. Prokop, H. J. Ritzhaupt-Kleissl, A. Ruh, and J. Hausselt. "Multi-component microinjection moulding-trends and developments." International Journal of Advanced Manufacturing Technology 47, no. 1-4 (2009): 63–71. http://dx.doi.org/10.1007/s00170-009-1985-z.

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35

Schmidt-Hohagen, Frank, and Ivan Egry. "Surface Tension Measurements of Industrial Alloys." Materials Science Forum 508 (March 2006): 573–78. http://dx.doi.org/10.4028/www.scientific.net/msf.508.573.

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Industrial alloys are generally multi-component systems with volatile and highly reactive components. Consequently, their processing in the liquid state requires special precautions. Therefore, an existing electromagnetic-levitation device with a high-vacuum chamber, designed for surface tension measurements, was modified and improved. For the measurements of the surface tensions with the help of the oscillating drop technique the temperatures and the video sequences of the levitated, molten alloy were recorded without contact by pyrometer and by high-speed camera, respectively. This method yi

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36

Wang, Xiaolin, Min Xie, and Lishuai Li. "On optimal upgrade strategy for second-hand multi-component systems sold with warranty." International Journal of Production Research 57, no. 3 (2018): 847–64. http://dx.doi.org/10.1080/00207543.2018.1488087.

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37

Zhang, Lin, Xiaohui Chen, Abdelhakim Khatab, and Youjun An. "Optimizing imperfect preventive maintenance in multi-component repairable systems under s-dependent competing risks." Reliability Engineering & System Safety 219 (March 2022): 108177. http://dx.doi.org/10.1016/j.ress.2021.108177.

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38

Nguyen, Kim-Anh, Phuc Do, and Antoine Grall. "Joint predictive maintenance and inventory strategy for multi-component systems using Birnbaum’s structural importance." Reliability Engineering & System Safety 168 (December 2017): 249–61. http://dx.doi.org/10.1016/j.ress.2017.05.034.

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Vu, Hai Canh, Phuc Do, Mitra Fouladirad, and Antoine Grall. "Dynamic opportunistic maintenance planning for multi-component redundant systems with various types of opportunities." Reliability Engineering & System Safety 198 (June 2020): 106854. http://dx.doi.org/10.1016/j.ress.2020.106854.

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40

Shi, Yue, Weihang Zhu, Yisha Xiang, and Qianmei Feng. "Condition-based maintenance optimization for multi-component systems subject to a system reliability requirement." Reliability Engineering & System Safety 202 (October 2020): 107042. http://dx.doi.org/10.1016/j.ress.2020.107042.

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Zhou, Xiaojun, Kaimin Huang, Lifeng Xi, and Jay Lee. "Preventive maintenance modeling for multi-component systems with considering stochastic failures and disassembly sequence." Reliability Engineering & System Safety 142 (October 2015): 231–37. http://dx.doi.org/10.1016/j.ress.2015.05.005.

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42

Wang, Ling, Hong Xu, Jinjin Wu, Xiai Chen, and Wenbo Na. "Agent-based modeling of availability for complex multiple units systems." Journal of Quality in Maintenance Engineering 23, no. 1 (2017): 71–81. http://dx.doi.org/10.1108/jqme-06-2013-0033.

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Purpose The purpose of this paper is to propose an availability modeling method of complex multiple units system (CMUS) based on the multi-agent technique. Design/methodology/approach Based on the multi-agent technique, this paper describes the availability model structure for CMUS and develops agent-based models of components, maintenance policies, maintenance tools, maintenance fields, and maintenance staff, as well as the communication method among the different agents. On the basis of the agent-based availability modeling theory, the availability simulation scheme of CMUS is given using MA

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43

Zaretalab, Arash, Mani Sharifi, Pedram Pourkarim Guilani, Sharareh Taghipour, and Seyed Taghi Akhavan Niaki. "A multi-objective model for optimizing the redundancy allocation, component supplier selection, and reliable activities for multi-state systems." Reliability Engineering & System Safety 222 (June 2022): 108394. http://dx.doi.org/10.1016/j.ress.2022.108394.

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Okumura, Susumu, Yuuki Matsumoto, Yuji Hatanaka, and Kazunori Ogohara. "Simultaneous Evaluation of Environmental Impact and Incurred Cost on Selection of End-Of-Life Products Recovery Options." International Journal of Automation Technology 10, no. 5 (2016): 699–707. http://dx.doi.org/10.20965/ijat.2016.p0699.

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Conventional production and consumption systems, in which industrial products are manufactured, consumed, and then finally disposed, have significant environmental impacts. Reusing and recycling product components in the manufacture of industrial products has recently become popular as an effective way of conserving natural resources. In this study, we propose a method to assign each product component a reasonable end-of-life (EOL) option (reuse, recycling, and disposal) in the product design phase. We develop a method, in which a product tree is generated by a multi-agent system, to determine

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45

Kohansal, Akram, Shirin Shoaee, and Mohammad Z. Raqab. "Estimating the stress-strength parameter in multi-component systems based on adaptive hybrid progressive censoring." International Journal of Industrial and Systems Engineering 41, no. 3 (2022): 363. http://dx.doi.org/10.1504/ijise.2022.124069.

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Kohansal, Akram, SHIRIN SHOAEE, and Mohammad Z. Raqab. "Estimating the stress-strength parameter in multi-component systems based on adaptive hybrid progressive censoring." International Journal of Industrial and Systems Engineering 1, no. 1 (2020): 1. http://dx.doi.org/10.1504/ijise.2020.10039570.

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47

Xu, Zhuoran, Qianmu Li, Linfang Qian, and Manyi Wang. "Multi-Sensor Fault Diagnosis Based on Time Series in an Intelligent Mechanical System." Sensors 22, no. 24 (2022): 9973. http://dx.doi.org/10.3390/s22249973.

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Intelligent mechanical systems are a focused area nowadays. One of the requirements of intelligent mechanical systems is to achieve intelligent fault diagnosis through the real-time acquisition and analysis of data from various sensors installed on mechanical components. In this paper, a new fault diagnosis method is proposed to solve the problems of difficulty in integrating the fault diagnosis algorithm and locating fault parts due to the complexity of modern mechanical systems. The complexity of modern industrial intelligent systems is due to the fact that the systems are composed of multip

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48

Falkowski, Michał J., Paweł D. Domański, and Ewa Pawłuszewicz. "Causality in Control Systems Based on Data-Driven Oscillation Identification." Applied Sciences 12, no. 8 (2022): 3784. http://dx.doi.org/10.3390/app12083784.

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This paper addresses the subject of causality analysis using simulation data and data collected from a real control system. Simulated data includes Gaussian and Cauchy noise signals. Real-time series include various, mostly unknown distortions, like trends, oscillations, and noises. Presented research focuses on the oscillatory component in data and its propagation in multi-loop control systems. Oscillation identification is based on a deep decomposition process for control error time series. Identified periodic signals are used for further causality processing. The analysis uses the Transfer

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Wang, Siqi, Xian Zhao, Zhigang Tian, and Ming J. Zuo. "Optimum component reassignment for balanced systems with multi-state components operating in a shock environment." Reliability Engineering & System Safety 210 (June 2021): 107514. http://dx.doi.org/10.1016/j.ress.2021.107514.

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50

Xu, Jun, Zhenglin Liang, Yan-Fu Li, and Kaibo Wang. "Generalized condition-based maintenance optimization for multi-component systems considering stochastic dependency and imperfect maintenance." Reliability Engineering & System Safety 211 (July 2021): 107592. http://dx.doi.org/10.1016/j.ress.2021.107592.

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