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Log-based predictive maintenance

Ruben Sipos, Dmitriy Fradkin, Fabian Moerchen, Zhuang Wang
2014 Proceedings of the 20th ACM SIGKDD international conference on Knowledge discovery and data mining - KDD '14  
We present a data-driven approach based on multiple-instance learning for predicting equipment failures by mining equipment event logs which, while usually not designed for predicting failures, contain  ...  Our predictive maintenance approach, deployed by a major medical device provider over the past several months, learns and evaluates predictive models from terabytes of log data, and actively monitors thousands  ...  .: One graph is worth a thousand logs: Uncovering hidden structures in massive system event logs. In: ECML PKDD (2009)  ... 
doi:10.1145/2623330.2623340 dblp:conf/kdd/SiposFMW14 fatcat:rzhqrlxasbbnzdd2w3tnkft2ze

Real-Time Anomaly Detection in Data Centers for Log-based Predictive Maintenance using an Evolving Fuzzy-Rule-Based Approach [article]

Leticia Decker, Daniel Leite, Luca Giommi, Daniele Bonacorsi
2020 arXiv   pre-print
Detection of anomalous behaviors in data centers is crucial to predictive maintenance and data safety.  ...  We propose a real-time approach to monitor and classify log records based on sliding time windows, and a time-varying evolving fuzzy-rule-based classification model.  ...  Usually, CC maintenance is based on offline statistical analysis of log records -in the preventive case, this is based on fixed time intervals.  ... 
arXiv:2004.13527v1 fatcat:limrvrdmjnds7nekwagonamluq

Predictive Maintenance from Event Logs Using Wavelet-Based Features: An Industrial Application [chapter]

Stéphane Bonnevay, Jairo Cugliari, Victoria Granger
2019 Springer Reference Sozialwissenschaften  
Unsupervised pattern detection approaches take an event log as input and generate 29 patterns based on statistical properties 2,3,5 .  ...  We propose a supervised approach to predict faults from an event log data using wavelets features as input of a random forest which is an ensemble learning method.  ...  Moreover, some specic works dealing with predictive maintenance based on event logs have 37 also been tackled.  ... 
doi:10.1007/978-3-030-20055-8_13 dblp:conf/softcomp/BonnevayCG19 fatcat:gqjyi5zfanerjklrmckhslmtpi

Predictive maintenance using FMECA method and NHPP models

Nishit Kumar Srivastava, Sandeep Mondal
2014 International Journal of Services and Operations Management  
Most of predictive maintenance technologies are inaccessible to small scale and medium scale industries due to their demanding cost.  ...  Firstly, the component to be used as an indicator for predictive maintenance is chosen using FMECA method, in which the most critical component is chosen.  ...  Table 1 Classification of predictive maintenance models (continued) Predictive maintenance models 2 Age-based models • Yang and Liu (1999) simulated ageing failure mode of a DC motor using rotating speed  ... 
doi:10.1504/ijsom.2014.065367 fatcat:mp2xi6obbjbg7dututr3a2qhry

SOPHIA: An Event-Based IoT and Machine Learning Architecture for Predictive Maintenance in Industry 4.0

Matteo Calabrese, Martin Cimmino, Francesca Fiume, Martina Manfrin, Luca Romeo, Silvia Ceccacci, Marina Paolanti, Giuseppe Toscano, Giovanni Ciandrini, Alberto Carrotta, Maura Mengoni, Emanuele Frontoni (+1 others)
2020 Information  
Our predictive maintenance approach deployed on a Big Data framework allows screening simultaneously multiple connected machines by learning from terabytes of log data.  ...  The target prediction provides salient information which can be adopted within the maintenance management practice.  ...  (iii) predictive maintenance.  ... 
doi:10.3390/info11040202 fatcat:6ko3ze2msbfhnfwbd42jpo3bo4

Integrated Maintenance System Trend and a Maintenance Scheduling System Application [chapter]

Toshiharu Miwa, Toshiya Kaihara, Youichi Nonaka
2014 Through-life Engineering Services  
Preventive Maintenance a. Time-Based Maintenance b. Condition-Based Maintenance 2.  ...  Maintenance Propagation Prediction Logs Visualization Time Result of Manufacturing Condition Prediction Demonstration Process A Process B Process C Group A Group B Group C In maintenance  ...  been constructing that controls productivity detractor propagation caused by machine maintenance.  ... 
doi:10.1007/978-3-319-12111-6_15 fatcat:lt3xzquwjjgshcvzhejje6m4by

Time-series Anomaly Detection Applied to Log-based Diagnostic System Using Unsupervised Machine Learning Approach

Francesco Minarini, Leticia Decker
2020 Zenodo  
All WLCG computing centers are focused on the development of hardware and software solutions as machine learning log-based predictive maintenance systems.  ...  Its final goal is to build up an automatised log-based event-oriented predictive maintenance system [4] .  ...  Predictive maintenance (3) involves methods that make a prediction of failure occurrences according to system outputs.  ... 
doi:10.5281/zenodo.4026499 fatcat:pyefozycofestgiqkpx2trqd2y

Analysis of Predictive Maintenance for Tunnel Systems

Tomáš Tichý, Jiří Brož, Zuzana Bělinová, Rastislav Pirník
2021 Sustainability  
of predictive maintenance.  ...  The main goal of the article is to summarize the possibilities of optimizing system maintenance that are based on data analysis as well as expert analysis based on the experience with the equipment in  ...  Important approaches in failure maintenance are predictive maintenance (PdM), which is based on continuous diagnostics and evaluation of the current state and of the prediction of the trends that forecast  ... 
doi:10.3390/su13073977 fatcat:2qoo7uoml5ds3czhvywhkeiomu

AutoML for Log File Analysis (ALFA) in a Production Line System of Systems pointed towards Predictive Maintenance

Matthias Maurer, Andreas Festl, Bor Bricelj, Germar Schneider, Michael Schmeja
2021 Infocommunications journal  
In this paper, we investigate the possibility to create a predictive maintenance framework using only easily available log data based on a neural network framework for predictive maintenance tasks.  ...  Combining these two fields of research by conducting log analysis using automated machine learning techniques to fuel predictive maintenance algorithms holds multiple advantages, especially when applied  ...  In a predictive maintenance manner, a NN can be trained to predict upcoming log entries of interest-based on the observed log entries to allow for appropriate intervention.  ... 
doi:10.36244/icj.2021.3.8 fatcat:6lb64pkskbhgxcrorfzzjhescm

Design and Implementation of Marine Elevator Safety Monitoring System based on Machine Learning

Young Wook Cho, Jae Myoung Kim, Yoon Yong Park
2016 Indian Journal of Science and Technology  
The accuracy of load and platform tilt based slope prediction model is 0.99 or above, but the accuracy of roll and pitch based slope prediction model is below 0.94.  ...  Therefore, it cannot be adapted to the logging gateway prediction model.  ...  The logging gateway provides diagnosis prediction model trained by big data on the server for the marine elevator maintenance.  ... 
doi:10.17485/ijst/2016/v9is1/109889 fatcat:eeoyqzozbfbdpkpl7dgus3o7ny

Life Cycle Costing: Maintenance and Repair Costs of Hospital Facilities Using Monte Carlo Simulation

Tae-Hui Kim, Jong-Soo Choi, Young Jun Park, Kiyoung Son
2013 Journal of the Korea Institute of Building Construction  
From the design phase to the maintenance phase, these participants may confront many risks. To avoid these risks, participants should utilize an insurance company or a bond company.  ...  Based on the same data, the log-normal distribution method and the Monte Carlo simulation are performed to predict the M&R cost for 50 years of the same building.  ...  Log-normal distribution for total components In this study, the log-normal distribution was used to predict the M&R costs of a research hospital facility.  ... 
doi:10.5345/jkibc.2013.13.6.541 fatcat:icvuyfncz5gaddsbynt4nojlzu

Monitoring and Analytics at INFN Tier-1: the next step

Fabio Viola, Barbara Martelli, Diego Michelotto, Enrico Fattibene, Antonio Falabella, Stefano Dal Pra, Lucia Morganti, Luca Dell'Agnello, Daniele Bonacorsi, Simone Rossi Tisbeni, C. Doglioni, D. Kim (+4 others)
2020 EPJ Web of Conferences  
us with a suitable framework to implement a solution for the predictive analysis of the status of the whole environment.  ...  Since its birth, INFN Tier-1 data centre, hosted at CNAF, has used various monitoring tools all replaced, a few years ago, by a system common to all CNAF departments (based on Sensu, Influxdb, Grafana)  ...  In fact, we hereby present a layered scalable big data infrastructure that, upon completion, will be aimed at predictive maintenance for large data centres, going beyond the pure log-based predictive maintenance  ... 
doi:10.1051/epjconf/202024507008 fatcat:p4dlssz2gveu3mqqshrxn4524m

Using Temporal and Semantic Developer-Level Information to Predict Maintenance Activity Profiles [article]

Stanislav Levin, Amiram Yehudai
2016 arXiv   pre-print
The computed metrics were then employed to predict the corrective, perfective, and adaptive maintenance activity profiles identified in previous works.  ...  Predictive models for software projects' characteristics have been traditionally based on project-level metrics, employing only little developer-level information, or none at all.  ...  ACTIVITY Predicted profile: Predictor Corrective (1) Perfective (2) Adaptive (3) (P 1 ) log(Commitsrepo) 0.797 0.572 0.503 (0.010) (0.020) (0.015) (P 2 ) log(Muserepo) 0.171 −0.288  ... 
arXiv:1611.10053v1 fatcat:cfubwnijqvb7bpkxzarev52gcy

Intelligent Choice of Machine Learning Methods for Predictive Maintenance of Intelligent Machines

Marius Becherer, Michael Zipperle, Achim Karduck
2020 Computer systems science and engineering  
Based on the relationships found, a process model is presented that shows a fast implementation of the predictive maintenance for machines.  ...  In this paper, results are compiled to give a state of the art of predictive maintenance. First, the different types of maintenance and economic relationships are explained.  ...  With regard to predicted maintenance, data sources such as historical maintenance logs and error logs are particularly important for this.  ... 
doi:10.32604/csse.2020.35.081 fatcat:ehu2h24qlzeetljzcenlkwkaly

Health Monitoring for Lighting Applications [chapter]

W. D. van Driel, L. M. Middelburg, B. El Mansouri, B. J. C. Jacobs
2019 Sensor Systems Simulations  
Lumen Maintenance The debate on producing commercial claims for LED-based products in terms of lumen maintenance is still not settled.  ...  So, per today, commercial claims for LED-based products in terms of lumen maintenance are fully based on these LM-80 data and TM-21 extrapolations.  ... 
doi:10.1007/978-3-030-16577-2_13 fatcat:brpkbdgukvbabdnbw7jebnjoo4
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