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Journal articles on the topic 'Prescriptive maintenance'

Author: Grafiati

Published: 7 July 2024

Last updated: 31 July 2025

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1

Geier, Manuel. "Prescriptive Maintenance mit zentralem Datenportal." BWK ENERGIE. 74, no. 9-10 (2022): 26–27. http://dx.doi.org/10.37544/1618-193x-2022-9-10-26.

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Wollen Unternehmen den optimalen Instandhaltungsmix finden, benötigen sie zunächst saubere Maschinendaten. Diese müssen richtig erfasst, konsolidiert und danach bewertet werden, um aus der Analyse Einsichten zu gewinnen, mit denen unerwartete Stillstände vermieden werden und die Instandhaltung gleichzeitig konstant optimiert werden kann. Unternehmen der Energiebranche gelingt das mit einem zentralen Datenportal.

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2

Errandonea, Itxaro, Unai Alvarado, Sergio Beltrán, and Saioa Arrizabalaga. "A Maturity Model Proposal for Industrial Maintenance and Its Application to the Railway Sector." Applied Sciences 12, no. 16 (2022): 8229. http://dx.doi.org/10.3390/app12168229.

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Maintenance is one of the major concerns of the industrial sector. Acquiring better levels of maintenance maturity is one of the objectives to be achieved. Therefore, prescriptive maintenance is one of the areas of recent research. Current works in literature are focused on specifics of maintenance strategies (from preventive to prescriptive), usually related to a fixed asset. No previous work has been identified regarding the methodology and guidelines to be followed to be able to evolve within the different strategies from a generic perspective. To address the lack of a methodology that show

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3

Yamashita, Akiko, Mitsuyuki Kawakami, Yoshimasa Inagaki, and Takao Ohkubo. "A Prescriptive Exercise Program for Health Maintenance." International Journal of Occupational Safety and Ergonomics 7, no. 2 (2001): 195–209. http://dx.doi.org/10.1080/10803548.2001.11076486.

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4

Souza, Josiely Borges de, and Sandra Mara Santana Rocha. "PRESCRIPTIVE MAINTENANCE SYNCHRONIZED TO THE CHARACTERISTICS OF INDUSTRY 5.0: A THEORETICAL DISCUSSION." Journal of Technology and Operations Management 19, no. 1 (2024): 40–58. http://dx.doi.org/10.32890/jtom2024.19.1.4.

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This article aims to examine and understand the current scope of Prescriptive Maintenance integrated with the human-centric characteristics of Industry 5.0. Therefore, the main research question is the following: “In the view of the managers of the companies visited, located in the Southeast Region of Brazil, what are the main technical and administrative difficulties that companies encounter in successfully implementing proactive combinations on the factory floor, such as Prescriptive Maintenance integrated with the characteristics of Industry 5.0”?. The evolution of industrial processes in r

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Kothona, Despoina, Ioannis P. Panapakidis, and Georgios C. Christoforidis. "Development of prescriptive maintenance methodology for maintenance cost minimization of photovoltaic systems." Solar Energy 271 (March 2024): 112402. http://dx.doi.org/10.1016/j.solener.2024.112402.

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Setyobudi, Bima Bagus. "Strategi Pemeliharaan Preskriptif: Optimalisasi Keandalan Mesin Berbasis Machine Learning Guna Mencegah Terjadinya Downtime Pada Mesin Industri." Prosiding Seminar Nasional KONSTELASI 2, no. 1 (2025): 414–26. https://doi.org/10.24002/prosidingkonstelasi.v2i1.11199.

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Abstrak. Downtime pada mesin industri dapat menyebabkan kerugian yang signifikan dalam produktivitas dan efisiensi operasional. Berbagai metode pemeliharaan seperti Corrective, Descriptive, Diagnostic, dan Predictive Maintenance memiliki keterbatasan dalam mengoptimalkan strategi mitigasi downtime. Oleh karena itu, penelitian ini mengimplementasikan Prescriptive Maintenance berbasis Machine Learning (XGBoost) untuk tidak hanya memprediksi kegagalan mesin tetapi juga memberikan rekomendasi langkah korektif guna mencapai zero downtime. Dataset AI4I 2020 Predictive Maintenance digunakan sebagai s

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Pop-Suărășan, Ana-Diana, Nicolae Stelian Ungureanu, and Adrian Petrovan. "Analytical Research Regarding the Implementation of a Prescriptive Maintenance System Applied to IT&C Equipment." Machines 13, no. 5 (2025): 412. https://doi.org/10.3390/machines13050412.

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In the era of digitalization, prescriptive maintenance and equipment condition monitoring are essential for ensuring the continuity of operations in various industries. The proposed software solution provides an integrated solution for monitoring and maintaining equipment, facilitating the collection, processing and interpretation of data related to their performance. Prioritization of prescriptive maintenance recommendations for alerts within the application is based on a set of well-defined criteria that integrate both the analysis of physical sensor data and computer logs. This is achieved

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Kawakami, M., A. Yamashita, T. Ohkubo, and Y. Sanbayashi. "A Reasonable Prescriptive Exercise Program for Health Care Maintenance." Proceedings of the Human Factors and Ergonomics Society Annual Meeting 44, no. 33 (2000): 6–178. http://dx.doi.org/10.1177/154193120004403327.

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9

Koops, Lily Geraldine. "Optimized Maintenance Decision-Making – A Simulation-supported Prescriptive Analytics Approach based on Probabilistic Cost-Benefit Analysis." PHM Society European Conference 5, no. 1 (2020): 14. http://dx.doi.org/10.36001/phme.2020.v5i1.1269.

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Prescriptive Maintenance strategies are emerging as potential next level of reliability and maintenance best practice. Likely outcomes of maintenance alternatives and their effects on e.g. cost and safety are comparatively evaluated by exploiting various sources of data, knowledge and models. By this means, optimized courses of actions are recommended to quickly resolve problems and to automate Maintenance, Repair and Overhaul (MRO) decisions. In this work, the key question is pursued as to how their dependability and potential business advantage can be assessed and improved in the presence of

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10

Fox, Harriet, Ajit C. Pillai, Daniel Friedrich, Maurizio Collu, Tariq Dawood, and Lars Johanning. "A Review of Predictive and Prescriptive Offshore Wind Farm Operation and Maintenance." Energies 15, no. 2 (2022): 504. http://dx.doi.org/10.3390/en15020504.

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Offshore wind farms are a rapidly developing source of clean, low-carbon energy and as they continue to grow in scale and capacity, so does the requirement for their efficient and optimised operation and maintenance. Historically, approaches to maintenance have been purely reactive. However, there is a movement in offshore wind, and wider industry in general, towards more proactive, condition-based maintenance approaches which rely on operational data-driven decision making. This paper reviews the current efforts in proactive maintenance strategies, both predictive and prescriptive, of which t

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Belov, Sergei, Sergei Nikolaev, and Ighor Uzhinsky. "Hybrid Data-Driven and Physics-Based Modeling for Gas Turbine Prescriptive Analytics." International Journal of Turbomachinery, Propulsion and Power 5, no. 4 (2020): 29. http://dx.doi.org/10.3390/ijtpp5040029.

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This paper presents a methodology for predictive and prescriptive analytics of a gas turbine. The methodology is based on a combination of physics-based and data-driven modeling using machine learning techniques. Combining these approaches results in a set of reliable, fast, and continuously updating models for prescriptive analytics. The methodology is demonstrated with a case study of a jet-engine power plant preventive maintenance and diagnosis of its flame tube. The developed approach allows not just to analyze and predict some problems in the combustion chamber, but also to identify a par

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12

Shohet, Igal M., and Ad Straub. "PERFORMANCE-BASED-MAINTENANCE: A COMPARATIVE STUDY BETWEEN THE NETHERLANDS AND ISRAEL." International Journal of Strategic Property Management 17, no. 2 (2013): 199–209. http://dx.doi.org/10.3846/1648715x.2013.807482.

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Traditional maintenance contracts using the unit price system and prescriptive specifications are simple in their structure and implementation. Implementation of prescriptive-based specification reduces though the flexibility of the procurement and limits the possibilities of the contractor to improve the in-sight operation. Furthermore, the management of the contract faces difficulties such as poor performance of the buildings and ineffective contract management. Performance-Based-Maintenance (PBM) attains an alternative means for outsourcing of maintenance. The objective of the study was to

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Frawley, Jack. "What Should Schools do About Aboriginal Language Maintenance?" Aboriginal Child at School 20, no. 1 (1992): 3–14. http://dx.doi.org/10.1017/s0310582200007690.

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In addressing this question, I will briefly outline the existing types of language maintenance program models, and what schools can do about Aboriginal language maintenance in the Aboriginal community school context. I have suggested a number of guiding principles for Aboriginal schools which are not intended to be prescriptive, but rather to establish a basis for dialogue and discussion from which language maintenance programs could be developed.

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14

Di Pasquale, Valentina, Salvatore Digiesi, Ivan Ferretti, and Antonio Padovano. "Building and sustaining competence in maintenance: a prescriptive training model." IFAC-PapersOnLine 58, no. 8 (2024): 174–79. http://dx.doi.org/10.1016/j.ifacol.2024.08.116.

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15

Ansari, Fazel, Robert Glawar, and Tanja Nemeth. "PriMa: a prescriptive maintenance model for cyber-physical production systems." International Journal of Computer Integrated Manufacturing 32, no. 4-5 (2019): 482–503. http://dx.doi.org/10.1080/0951192x.2019.1571236.

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16

Liu, Bin, Jing Lin, Liangwei Zhang, and Uday Kumar. "A Dynamic Prescriptive Maintenance Model Considering System Aging and Degradation." IEEE Access 7 (2019): 94931–43. http://dx.doi.org/10.1109/access.2019.2928587.

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17

Petroutsatou, K., and I. Ladopoulos. "Integrated Prescriptive Maintenance System (PREMSYS) for Construction Equipment Based on Productivity." IOP Conference Series: Materials Science and Engineering 1218, no. 1 (2022): 012006. http://dx.doi.org/10.1088/1757-899x/1218/1/012006.

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Abstract It is now imperative to create smart systems that prevent mechanical damage through timely preventive maintenance, particularly in construction projects with strict time schedules and budgets. Construction equipment is the largest capital investment for construction companies. Proper maintenance is of major importance for efficiency, productivity, minimization of equipment costs, and environmental management. The aim of this study is to propose an integrated smart system that will monitor the condition based on productivity of the equipment and will provide diagnostic data, helping to

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18

Carvalho, Johnderson Nogueira de, Felipe Rodrigues da Silva, and Erick Giovani Sperandio Nascimento. "Challenges of the Biopharmaceutical Industry in the Application of Prescriptive Maintenance in the Industry 4.0 Context: A Comprehensive Literature Review." Sensors 24, no. 22 (2024): 7163. http://dx.doi.org/10.3390/s24227163.

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The biopharmaceutical industry has specificities related to the optimization of its processes, the effectiveness of the maintenance of the productive park in the face of regulatory requirements. and current concepts of modern industry. Current research on the subject points to investments in the health area using the current tools and concepts of Industry 4.0 (I4.0) with the objective of a more assertive production, reduction of maintenance costs, reduction of operating risks, and minimization of equipment idle time. In this context, this study aims to characterize the current knowledge about

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19

Kolar, Davor, Dragutin Lisjak, Martin Curman, and Michał Pająk. "Condition Monitoring of Rotary Machinery Using Industrial IOT Framework." Tehnički glasnik 16, no. 3 (2022): 343–52. http://dx.doi.org/10.31803/tg-20220517173151.

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Modern maintenance strategies, such as predictive and prescriptive maintenance, which derived from the concept of Industry and Maintenance 4.0, involve the application of the Industrial Internet of Things (IIoT) to connect maintenance objects enabling data collection and analysis that can help make better decisions on maintenance activities. Data collection is the initial step and the foundation of any modern Predictive or Prescriptive maintenance strategy because it collects data that can then be analysed to provide useful information about the state of maintenance objects. Condition monitori

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20

Matyas, Kurt, Tanja Nemeth, Klaudia Kovacs, and Robert Glawar. "A procedural approach for realizing prescriptive maintenance planning in manufacturing industries." CIRP Annals 66, no. 1 (2017): 461–64. http://dx.doi.org/10.1016/j.cirp.2017.04.007.

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21

Grijalvo Martín, Mercedes, Antonia Pacios Álvarez, Joaquín Ordieres-Meré, Javier Villalba-Díez, and Gustavo Morales-Alonso. "New Business Models from Prescriptive Maintenance Strategies Aligned with Sustainable Development Goals." Sustainability 13, no. 1 (2020): 216. http://dx.doi.org/10.3390/su13010216.

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The industry has entered on the Fourth Industrial Revolution, the so-called Industry 4.0, with global markets and strong competition, some traditional manufacturing firms are implementing new maintenance innovations and policies, based on digitalisation and data driven approach, but also based on servitisation. The implementation of these new equipment maintenance business models, could require new organisational approach at different levels. Different sorts of integration are arranged, in vertical with a flat structure of intelligent, flexible and autonomous units working integrated, in horiz

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22

Gordon, Christopher Ampofo Kwadwo, Baris Burnak, Melis Onel, and Efstratios N. Pistikopoulos. "Data-Driven Prescriptive Maintenance: Failure Prediction Using Ensemble Support Vector Classification for Optimal Process and Maintenance Scheduling." Industrial & Engineering Chemistry Research 59, no. 44 (2020): 19607–22. http://dx.doi.org/10.1021/acs.iecr.0c03241.

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23

Tolstow, K. T., A. Beiky, and I. El-Thalji. "Maintenance philosophy for an unmanned platform: A case study for an Offshore wind substation." IOP Conference Series: Materials Science and Engineering 1201, no. 1 (2021): 012085. http://dx.doi.org/10.1088/1757-899x/1201/1/012085.

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Abstract Unmanned installations introduce new challenges for the operations and maintenance. In many offshore windfarms there is a need for offshore substations and these substations can be designed as unmanned installations. Thus, the purpose of this paper is to review and discuss the available maintenance philosophies for unmanned substation platforms and as a result, propose a suitable maintenance philosophy for this type of installations with regards to key performance indicators such as high availability, low maintenance man-hours and minimal fixed maintenance campaigns. It is concluded t

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24

Nordal, Helge, and Idriss El-Thalji. "Lifetime Benefit Analysis of Intelligent Maintenance: Simulation Modeling Approach and Industrial Case Study." Applied Sciences 11, no. 8 (2021): 3487. http://dx.doi.org/10.3390/app11083487.

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The introduction of Industry 4.0 is expected to revolutionize current maintenance practices by reaching new levels of predictive (detection, diagnosis, and prognosis processes) and prescriptive maintenance analytics. In general, the new maintenance paradigms (predictive and prescriptive) are often difficult to justify because of their multiple inherent trade-offs and hidden systems causalities. The prediction models, in the literature, can be considered as a “black box” that is missing the links between input data, analysis, and final predictions, which makes the industrial adaptability to suc

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25

Moros, D., N. Berrabah, K. D. Searle, and I. G. Ashton. "Maintenance & failure data analysis of an offshore wind farm." Journal of Physics: Conference Series 2767, no. 6 (2024): 062006. http://dx.doi.org/10.1088/1742-6596/2767/6/062006.

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Abstract Offshore Wind (OW) continues to grow globally at a rapid pace, with growth estimates of 630GW by 2050. To facilitate this rapid growth, costs must continue to be reduced. Reducing operations and maintenance (O&M) costs, which are estimated at 30% of the lifetime costs of wind farms, offers opportunity. This could be achieved by moving current maintenance strategies to a prescriptive strategy. Prescriptive strategies use the turbine monitoring data to determine component remaining useful lifetimes or predict failure windows and then provide an optimised maintenance plan. The first

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26

Gonzaga, Luiz Gonzaga da Costa Neto. "analysis of the possibility of reducing spare parts in the maintenance context 4.0." Independent Journal of Management & Production 13, no. 1 (2022): 350–63. http://dx.doi.org/10.14807/ijmp.v13i1.1550.

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Equipment inspection arose from the need to maintain industrial facilities in satisfactory physical condition, providing the minimum level of safety and reliability in operation and maintenance. Machines and equipment cannot stop operating without planning and managing the supply chain, maintaining large quantities of spare parts stocks. The objective of this work is to analyze the possibility of predictive and / or prescriptive monitoring to contribute to the preventive maintenance of the real condition of the equipment, that is, only in real need, avoiding preventive maintenance for pre-esta

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Costa, J., José Torres Farinha, Mateus Mendes, and J. O. Estima. "AI-Driven Belt Failure Prediction and Prescriptive Maintenance with Motor Current Signature Analysis." Applied Sciences 15, no. 12 (2025): 6947. https://doi.org/10.3390/app15126947.

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Industrial belt failures pose significant challenges to manufacturing operations, often resulting in costly downtime and maintenance interventions. This study presents a comprehensive approach to belt failure analysis, leveraging advanced monitoring and diagnostic techniques. Through the integration of motor current signature analysis (MCSA) and machine learning algorithms, particularly long short-term memory (LSTM) networks, this study aims to predict and detect belt degradation in real time. The methodology involves the collection and pre-processing of raw spectral data from industrial asset

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Holovan, Andrii, Igor Gritsuk, Valerii Verbovskyi, et al. "Algorithmic support and efficiency analysis of comprehensive prescriptive maintenance for cargo ships using predictive monitoring." Eastern-European Journal of Enterprise Technologies 3, no. 3 (135) (2025): 13–26. https://doi.org/10.15587/1729-4061.2025.331875.

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The object of this study is the processes of prescriptive technical maintenance (TM) of vessel machinery and structures of cargo ships. The task addressed relates to the insufficient efficiency of conventional methods for vessel machinery TM, which leads to increased risks of failures and enhanced operating costs. In this work, algorithmic support to a system of comprehensive prescriptive maintenance of cargo ships based on predictive monitoring methods has been developed. Data on the parameters of machinery technical condition were experimentally acquired and systemized; a comprehensive analy

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29

Wesendrup, Kevin, Bernd Hellingrath, and Zoi Nikolarakis. "A framework for conceptualizing integrated prescriptive maintenance and production planning and control models." Brazilian Journal of Operations & Production Management 21, no. 3 (2024): 2172. http://dx.doi.org/10.14488/bjopm.2172.2024.

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Goal: This study aims to support researchers and managers in conceptualising new integrated prescriptive maintenance (PxM) and production planning and control (PPC) models. Design / Methodology / Approach: We perform a systematic literature review based on Thomé et al. (2016) and analyse literary findings using qualitative content analysis and quantitative correlation analyses. Results: This work identifies 94 integrated PxM and PPC planning models and 47 outcomes, 16 decision variables and 34 environment entities. Based on the quantitative analyses of these components, we derive a normative f

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30

Biebl, Fabian, Robert Glawar, Anahid Jalali, et al. "A conceptual model to enable prescriptive maintenance for etching equipment in semiconductor manufacturing." Procedia CIRP 88 (2020): 64–69. http://dx.doi.org/10.1016/j.procir.2020.05.012.

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31

Jeon, Chi-Ho, Chang-Su Shim, Yang-Hee Lee, and Jennifer Schooling. "Prescriptive maintenance of prestressed concrete bridges considering digital twin and key performance indicator." Engineering Structures 302 (March 2024): 117383. http://dx.doi.org/10.1016/j.engstruct.2023.117383.

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32

Chesalov, Alexander Yu. "Application of Artificial Intelligence for the Implementation of Mismatch Negativity Potential Algorithms in Industrial Automated Predictive Maintenance Systems." Open Education 29, no. 3 (2025): 11–21. https://doi.org/10.21686/1818-4243-2025-3-11-21.

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Problem statement. One of the urgent problems of industrial automation is that the operation of the few predictive maintenance systems available on the Russian market is usually based on the collection and analysis of equipment data without considering the joint impact of internal and external factors. In the current economic conditions, it is necessary to make a reasonable choice and apply new technologies of artificial intelligence for research and realization of basic principles of mismatch negativity potential, which will open new horizons for increasing efficiency and reliability of indus

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33

Wesendrup, Kevin, Mergim Mustafa, and Bernd Hellingrath. "Degradation-agnostic integrated prescriptive maintenance and production scheduling simulation for electrophoretic dip coating system." Procedia CIRP 130 (2024): 1210–15. http://dx.doi.org/10.1016/j.procir.2024.10.229.

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34

Ordieres-Meré, Joaquín, Antonio Sánchez-Herguedas, and Ángel Mena-Nieto. "A Data-Driven Monitoring System for a Prescriptive Maintenance Approach: Supporting Reinforcement Learning Strategies." Applied Sciences 15, no. 12 (2025): 6917. https://doi.org/10.3390/app15126917.

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The aim of this study was to evaluate machine learning algorithms’ capacity to improve prescriptive maintenance. A pumping system consisting of two hydraulic pumps with an electric motor from a Spanish petrochemical company was used as a case study. Sensors were used to record data on the variables, with the target variable being the bearing temperature of the electric motor. Several regression models and a neural network time series model were tested to model the system variables. A bearing temperature sensitivity analysis was conducted based on the coefficients obtained from the optimization

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Rahman, Azwanizam b. Che Abdul, Mohd Rahmat Tahir, M. Hamdan Kamarul Bahraini, Mohd Helmi Halim, and Muzamir Isa. "Digital Tools Approach Based On ‘Gerun’ And Online Partial Discharge Monitoring Project To Resolve Alternator’s Failure." Journal of Physics: Conference Series 2312, no. 1 (2022): 012041. http://dx.doi.org/10.1088/1742-6596/2312/1/012041.

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Abstract There is no online monitoring system and digital tools to monitor generator gas turbine healthiness led to generator failure caused un-planned outages resulted power import and penalty chargers. Maintenance program for generator is based on time-based method. Since 2016 to 2020, Asset Team spent millions of ringgit Malaysia for generator rectification and incurred power import cost due to the failure. To overcome the tripping issues, Generator Health Monitoring System was initiated as a research/pilot project as tools to monitor healthiness of Gas Turbine Generator. This project was c

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Shriprakashan. L. Parapalli and Jithen Shetty. "Leveraging Hybrid Edge-Cloud Predictive Maintenance in Pharmaceutical MES: An Industry 4.0 Approach Using Big Data." Journal of Computer Science and Technology Studies 7, no. 2 (2025): 86–94. https://doi.org/10.32996/jcsts.2025.7.2.7.

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The pharmaceutical sector relies on stringent manufacturing environments to safeguard product integrity and uphold regulatory standards. Unexpected equipment failures can lead to costly downtime, regulatory exposure, and compromised quality. To address these challenges, this paper presents an integrated Hybrid Edge-Cloud Predictive Maintenance (HEC-PdM) framework embedded within a Manufacturing Execution System (MES). By combining edge computing for real-time anomaly detection with cloud-based machine learning (ML) analytics, manufacturers can transition from reactive to predictive and prescri

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Swarun Kumar Joginpelly. "Predictive Analytics for Equipment Failure: Implementation and Outcomes of the Equipment Predisposed Tool." Journal of Computer Science and Technology Studies 7, no. 4 (2025): 240–47. https://doi.org/10.32996/jcsts.2025.7.4.29.

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This article presents a comprehensive investigation of the Equipment Predisposed Tool (EPT), a predictive analytics system designed to forecast equipment failures in industrial environments. It examines how advanced data analytics and machine learning techniques can transform maintenance operations from reactive to proactive paradigms. It details the data infrastructure, analytical methods, system architecture, and implementation strategies that underpin successful predictive maintenance initiatives. The article analyzes how the integration of sensor data, operational metrics, maintenance reco

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Papaioannou, Alexios, Asimina Dimara, Charalampos S. Kouzinopoulos, et al. "LP-OPTIMA: A Framework for Prescriptive Maintenance and Optimization of IoT Resources for Low-Power Embedded Systems." Sensors 24, no. 7 (2024): 2125. http://dx.doi.org/10.3390/s24072125.

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Low-power embedded systems have been widely used in a variety of applications, allowing devices to efficiently collect and exchange data while minimizing energy consumption. However, the lack of extensive maintenance procedures designed specifically for low-power systems, coupled with constraints on anticipating faults and monitoring capacities, presents notable difficulties and intricacies in identifying failures and customized reaction mechanisms. The proposed approach seeks to address the gaps in current resource management frameworks and maintenance protocols for low-power embedded systems

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39

Papaioannou, Alexios, Asimina Dimara, Charalampos Kouzinopoulos, et al. "LP-OPTIMA: A Framework for Prescriptive Maintenance and Optimization of IoT Resources for Low-Power Embedded Systems." Sensors 24 (March 26, 2024): 2125. https://doi.org/10.3390/s24072125.

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Low-power embedded systems have been widely used in a variety of applications, allowing devices to efficiently collect and exchange data while minimizing energy consumption. However, the lack of extensive maintenance procedures designed specifically for low-power systems, coupled with constraints on anticipating faults and monitoring capacities, presents notable difficulties and intricacies in identifying failures and customized reaction mechanisms. The proposed approach seeks to address the gaps in current resource management frameworks and maintenance protocols for low-power embedded systems

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40

Molęda, Marek, Bożena Małysiak-Mrozek, Weiping Ding, Vaidy Sunderam, and Dariusz Mrozek. "From Corrective to Predictive Maintenance—A Review of Maintenance Approaches for the Power Industry." Sensors 23, no. 13 (2023): 5970. http://dx.doi.org/10.3390/s23135970.

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Appropriate maintenance of industrial equipment keeps production systems in good health and ensures the stability of production processes. In specific production sectors, such as the electrical power industry, equipment failures are rare but may lead to high costs and substantial economic losses not only for the power plant but for consumers and the larger society. Therefore, the power production industry relies on a variety of approaches to maintenance tasks, ranging from traditional solutions and engineering know-how to smart, AI-based analytics to avoid potential downtimes. This review show

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41

Molęda, Marek, Bozena Małysiak-Mrozek, Weiping Ding, Vaidy Sunderam, and Dariusz Mrozek. "From Corrective to Predictive Maintenance—A Review of Maintenance Approaches for the Power Industry." Sensors 23, no. 13 (2023): 1–47. https://doi.org/10.3390/s23135970.

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Appropriate maintenance of industrial equipment keeps production systems in good health and ensures the stability of production processes. In specific production sectors, such as the electrical power industry, equipment failures are rare but may lead to high costs and substantial economic losses not only for the power plant but for consumers and the larger society. Therefore, the power production industry relies on a variety of approaches to maintenance tasks, ranging from traditional solutions and engineering know-how to smart, AI-based analytics to avoid potential downtimes. This review show

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42

Gonçalves Rosado, Carlos Antônio, and Gilson Ricardo De Melo. "ANÁLISE DE ESTRATÉGIAS PARA DISPONIBILIDADE DE MATERIAIS EM MANUTENÇÃO DE MÁQUINAS DE VIA: UMA REVISÃO SISTEMÁTICA." RECIMA21 - Revista Científica Multidisciplinar - ISSN 2675-6218 5, no. 12 (2024): e5125978. https://doi.org/10.47820/recima21.v5i12.5978.

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This systematic research addresses the critical importance of material availability for the effective maintenance of track machines, a fundamental element to ensure safety and efficiency in railway operations. The central problem investigated focuses on the challenges faced in provisioning these materials, including logistical issues, stock errors, and delivery delays, which can compromise timely and efficient maintenance. The aim of this study is to analyze innovative and effective strategies that can optimize the provisioning of materials necessary for track machine maintenance. To achieve t

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Finch, Byron J., and James P. Gilbert. "Developing maintenance craft labor efficiency through an integrated planning and control system: A prescriptive model." Journal of Operations Management 6, no. 3-4 (1986): 449–59. http://dx.doi.org/10.1016/0272-6963(86)90016-1.

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Gibey, Gaultier, Elodie Pahon, Noureddine Zerhouni, and Daniel Hissel. "Diagnostic and prognostic for prescriptive maintenance and control of PEMFC systems in an industrial framework." Journal of Power Sources 613 (September 2024): 234864. http://dx.doi.org/10.1016/j.jpowsour.2024.234864.

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Patil, Nikhil, Suhas Sarje, Pramod Bagade, Amol Patil, and Wasim Shaikh. "Maintenance 5.0, Sustainability and Sustainable Development Goals: A Review." International Journal of Basic and Applied Sciences 14, SI-2 (2025): 100–110. https://doi.org/10.14419/tc9tkg66.

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The advent of Industry 4.0 has brought about a surge in productivity using technologies such as digital twins, cloud computing, additive manufacturing, big data, sensor technologies, Internet of Things [IoT], Industrial Internet of Things [IIoT], etc,. However, it is essential that all nations need to adopt sustainable technologies due to the resolutions in the Paris Agreement [Paris Climate Accords] and global outrage. As a part of this endeavor, the industry 4.0 paradigm is transitioning to Industry. 5.0, emphasizing sustainable technologies. The activities related to maintenance in Industry

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DENG, HAOXUAN, Bernadin Namoano, BOHAO ZHENG, Samir Khan, and John Ahmet Erkoyuncu. "From Prediction to Prescription: Large Language Model Agent for Context-Aware Maintenance Decision Support." PHM Society European Conference 8, no. 1 (2024): 10. http://dx.doi.org/10.36001/phme.2024.v8i1.4114.

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Predictive analytics with machine learning approaches has widely penetrated and shown great success in system health management over the decade. However, how to convert the prediction to an actionable plan for maintenance is still far from mature. This study investigates how to narrow the gapbetween predictive outcomes and prescriptive descriptions for system maintenance using an agentic approach based on the large language model (LLM). Additionally, with the retrieval-augmented generation (RAG) technique and tool usage capability, the LLM can be context-aware when making decisions in maintena

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Ighravwe, Desmond Eseoghene. "Assessment of Sustainable Maintenance Strategy for Manufacturing Industry." Sustainability 14, no. 21 (2022): 13850. http://dx.doi.org/10.3390/su142113850.

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This study creates a framework to aid in the sustainability of maintenance strategies. The framework was created using expertise from the industry and academia. Using this knowledge, three multi-criteria tools were chosen for the maintenance strategies evaluation. The tools include grey relational analysis (GRA) techniques, additive ratio assessment (ARAS), and step-wise weight assessment ratio analysis (SWARA). In a production system, they were used to assess four planned maintenance strategies. The strategies are periodic maintenance (S1), meter-based maintenance (S2), predictive maintenance

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Sathyapalan, Dipu T., Jini James, Sangita Sudhir, et al. "Antimicrobial Stewardship and Its Impact on the Changing Epidemiology of Polymyxin Use in a South Indian Healthcare Setting." Antibiotics 10, no. 5 (2021): 470. http://dx.doi.org/10.3390/antibiotics10050470.

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Polymyxins being last resort drugs to treat infections triggered by multidrug-resistant pathogens necessitates the implementation of antimicrobial stewardship program (ASP) initiatives to support its rational prescription across healthcare settings. Our study aims to describe the change in the epidemiology of polymyxins and patient outcomes following the implementation of ASP at our institution. The antimicrobial stewardship program initiated in February 2016 at our 1300 bed tertiary care center involved post-prescriptive audits tracking polymyxin consumption and evaluating prescription approp

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Santiago, Rogerio Adriano da Fonseca, Natasha Benjamim Barbosa, Henrique Gomes Mergulhão, et al. "Data-Driven Models Applied to Predictive and Prescriptive Maintenance of Wind Turbine: A Systematic Review of Approaches Based on Failure Detection, Diagnosis, and Prognosis." Energies 17, no. 5 (2024): 1010. http://dx.doi.org/10.3390/en17051010.

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Wind energy has achieved a leading position among renewable energies. The global installed capacity in 2022 was 906 GW of power, with a growth of 8.4% compared to the same period in the previous year. The forecast is that the barrier of 1,000,000 MW of installed wind capacity in the world will be exceeded in July 2023, according to data from the World Association of Wind Energy. In order to support the expected growth in the wind sector, maintenance strategies for wind turbines must provide the reliability and availability necessary to achieve these goals. The usual maintenance procedures may

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Tektaş, Berna, Hasan Hüseyin Turan, Nihat Kasap, Ferhan Çebi, and Dursun Delen. "A Fuzzy Prescriptive Analytics Approach to Power Generation Capacity Planning." Energies 15, no. 9 (2022): 3176. http://dx.doi.org/10.3390/en15093176.

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This study examines the long-term energy capacity investment problem of a power generation company (GenCo), considering the drought threat posed by climate change in hydropower resources in Turkey. The mid-term planning decisions such as maintenance and refurbishment scheduling of power plants are also considered in the studied investment planning problem. In the modeled electricity market, it is assumed that GenCos conduct business in uncertain market conditions with both bilateral contracts (BIC) and day-ahead market (DAM) transactions. The problem is modeled as a fuzzy mixed-integer linear

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