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A Review of Data-Driven Decision-Making Methods for Industry 4.0 Maintenance Applications
2021
Electronics
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The current paper reviews the literature on data-driven decision-making in maintenance and outlines directions for future research towards data-driven decision-making for Industry 4.0 maintenance applications ...
of the cloud continuum for optimal deployment of decision-making services; capability of decision-making methods to cope with big data; incorporation of advanced security mechanisms; and coupling decision-making ...
[21] proposed a method for an optimal maintenance policy on the basis of residual life estimation for a slowly degrading system subject to soft failure and condition monitoring. ...
doi:10.3390/electronics10070828
doaj:8accfa8ec357433dbb02cde449e3af6a
fatcat:7q55ex2mezfstdllzfufryeo3a
Integration of disparate data sources to perform maintenance prognosis and optimal decision making
2012
Insight (Northampton)
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The objective is to give an overview of how the integration of disparate data sources, commonly available in industry, can be achieved for maintenance prognosis and optimal decision making. ...
The three main branches of condition based maintenance are diagnosis, prognosis, and treatmentprognosis, however prognosis is admittedly the most difficult. ...
The data-driven approaches are based on statistical and learning techniques from the theory of pattern recognition. ...
doi:10.1784/insi.2012.54.8.440
fatcat:loiogst5ozhh7acdqn7ltnhjpq
Analysis of Smart Manufacturing Technologies for Industry Using AI Methods
2018
Turkish Journal of Computer and Mathematics Education
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The study explores various AI-based approaches used in different stages of smart manufacturing, including data acquisition, data analysis, process optimization, and predictive maintenance. ...
Artificial intelligence (AI) methods, such as machine learning and data analytics, play a crucial role in enabling smart manufacturing systems to optimize processes and make informed decisions. ...
implementation of an AI-driven predictive maintenance system in a manufacturing plant. ...
doi:10.17762/turcomat.v9i2.13857
fatcat:bf7kte7m3ne3fob7ew6ucffrqm
Investigation of Fault Diagnosis and Prognostics Techniques for Predictive Maintenance in Industrial Machinery
2023
Engineering International
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The policy ramifications encompass the requirement for staff training, data standardization, investment in R&D, and regulatory frameworks to surmount constraints and stimulate innovation in industrial ...
Major conclusions demonstrating the value of integrated fault diagnosis and prognostics in early fault identification, proactive decision-making, and optimal maintenance scheduling have been drawn from ...
, data-driven, and hybrid approaches. ...
doi:10.18034/ei.v11i1.693
fatcat:d2xr3wocuvg35i44dcwftwfake
Towards Predictive Maintenance for Flexible Manufacturing Using FIWARE
[chapter]
2020
Lecture Notes in Business Information Processing
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Specifically, it looks at applying a data driven approach to the Long Short-Term Memory Network (LSTM) model for machine condition and remaining useful life to support predictive maintenance using FIWARE ...
For example, product design processes, manufacturing processes, and maintenance processes across different factories and enterprises. ...
The contributions of this work are a) design a predictive maintenance analytics platform based on FIWARE b) propose data-driven approach with Long Short-Term Memory (LSTM) network for RUL estimation, which ...
doi:10.1007/978-3-030-49165-9_2
fatcat:hvplqeh7j5fibjdfumg6welmvy
A clustering approach for mining reliability big data for asset management
2018
Proceedings of the Institution of Mechanical Engineers. Part O, Journal of risk and reliability
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For this, we propose a cost model to support asset managers in trading-off the simplification brought by the cluster-based approach against the related extra-costs. ...
Big data from very large fleets of assets challenge the asset management, as the number of maintenance strategies to optimize and administrate may become very large. ...
In [10] , an optimized OnLine Support Vector Regression (OL-SVR) for condition-based maintenance is proposed for streaming analysis of big data in the context of rail transportation systems. ...
doi:10.1177/1748006x17716344
fatcat:o2q3tvu5ofh2nm6rm24kseqtyu
Systematic Literature Review on Data-Driven Models for Predictive Maintenance of Railway Track: Implications in Geotechnical Engineering
2020
Geosciences
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Conventional planning of maintenance and renewal work for railway track is based on heuristics and simple scheduling. ...
This study presents a systematic literature review of data-driven models applied in the predictive maintenance of railway track. ...
Unnecessary maintenance actions may be taken, leading to additional cost. • Condition-based maintenance aims to optimize maintenance strategies based on the estimation of the track status. ...
doi:10.3390/geosciences10110425
fatcat:r73zrv554vcsnjbi2aaeswvbsq
A Predictive Maintenance Model for Flexible Manufacturing in the Context of Industry 4.0
2021
Frontiers in Big Data
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machine components driven by a data-driven LSTM model for RUL (remaining useful life) estimation. ...
To address this, we propose PMMI 4.0, a Predictive Maintenance Model for Industry 4.0, which utilizes a newly proposed solution PMS4MMC for supporting an optimized maintenance schedule plan for multiple ...
In the context of flexible job shop scheduling, Zheng et al. (2013) focused on a scheduling problem incorporating a condition-based maintenance approach for providing the optimal solution. ...
doi:10.3389/fdata.2021.663466
pmid:34514378
pmcid:PMC8427870
fatcat:ycdvo5m32va6bh4tavj6xevwoa
A Comprehensive Review of Emerging Trends in Aircraft Structural Prognostics and Health Management
2023
Mathematics
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With a comprehensive assessment of various SPHM techniques, the paper contributes by comparing traditional and modern approaches, evaluating their limitations, and showcasing advancements in data-driven ...
This review paper addresses the critical need for structural prognostics and health management (SPHM) in aircraft maintenance, highlighting its role in identifying potential structural issues and proactively ...
Gerdes et al. explored DT based data-driven condition monitoring and prognosis for reducing the unscheduled maintenance of A320 aircraft from Etihad Airways [89] . ...
doi:10.3390/math11183837
fatcat:kr2d7lu2x5ds7kbpdfu2yubaj4
PrimaVera: Synergising Predictive Maintenance
2020
Applied Sciences
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, inaccurate or incomplete data and the role of human and organisational factors in data-driven decision support tools. ...
The overarching challenge of predictive maintenance is to leverage these individual building blocks to obtain a framework that supports optimal maintenance and asset management. ...
The funders had no role in the design of the study; in the collection, analyses, or interpretation of data; in the writing of the manuscript, or in the decision to publish the results. ...
doi:10.3390/app10238348
fatcat:jdwhvgnynbhrtpvfijcejfe3ge
Condition-based maintenance optimization considering improving prediction accuracy
2014
Journal of the Operational Research Society
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In this research, we develop a method to quantify the remaining life prediction uncertainty considering the prediction accuracy improvement, and an effective CBM optimization approach to optimize the maintenance ...
Condition based maintenance (CBM) aims to reduce maintenance cost and improve equipment reliability by effectively utilizing condition monitoring and prediction information. ...
We appreciate very much the help from OMDEC Inc. and the Centre for Maintenance Optimization and Reliability Engineering (C-MORE) at the University of Toronto for providing the condition monitoring data ...
doi:10.1057/jors.2013.65
fatcat:lrrlxjlwrzg2pnjsmonaxjudky
Deployment of Prognostics to Optimize Aircraft Maintenance - A Literature Review
2019
Proceedings of the Annual Conference of the Prognostics and Health Management Society, PHM
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Therefore, optimization of maintenance operations is extremely important for airlines in order to stay competitive. ...
Finally, some recommendations for further research are discussed in perspective of deployment of prognostics to optimize aircraft maintenance. ...
We thank the development team of Prognos for Aircraft for their insights about using prognostics in MRO operations. ...
doi:10.36001/phmconf.2019.v11i1.776
fatcat:jequ75f72fe6lhl6ngjsgn6taq
Data Analytics and Optimization for Decision Support
2019
Business & Information Systems Engineering
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for their help in finalizing this special issue. ...
We would like to express our gratitude to the authors for their contributions, the referees for ensuring the quality of the accepted papers, and the staff of the Editorial Office and Production Department ...
Traditional decision methods, by comparison, use much less data. In this new setting, ''data-driven optimization'' as a fresh approach for industrial optimization has been proposed. ...
doi:10.1007/s12599-019-00591-6
fatcat:sziqj7iqb5g7tpy5jttkh56sxi
Evolution of Decision Support Systems for Railway Infrastructure Managers
2018
Zenodo
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We illustrate the decision-driven approach for DSS development using a case study of maintenance decisions for bridge selection. ...
To tackle these challenges of maintenance decision-making and data management, a decision-driven approach is suggested for the development of DSS. ...
Similarly, a data fusion framework for a number of isolated datasets is proposed for maintenance prognosis and optimal decision-making (Galar et. al., 2012b; Galar et. al., 2012) . ...
doi:10.5281/zenodo.1451327
fatcat:ipex45dqvvd4zeqa5itxarbg3i
An Optimized and Safety-aware Maintenance Framework: A Case Study on Aircraft Engine
[article]
2022
arXiv
pre-print
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This paper proposes an AI-assisted predictive maintenance scheme that synthesizes prognostics modeling and simulation-based optimization to help airlines decide their optimal engine maintenance approach ...
The proposed method enables airlines to utilize their diagnostics measurements and operational settings to design a more customized maintenance strategy that takes engine operations conditions into account ...
ACKNOWLEDGMENT The authors would like to thank the GMF AeroAsia team for providing valuable discussions and insights about maintenance approaches in airline industries. ...
arXiv:2209.02678v1
fatcat:nicuwwzimjdpnajzlslnznf6ka
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