Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

  • We're Hiring!
  • Help Center

paper cover thumbnail

A literature review of maintenance performance measurement: a conceptual framework and directions for future research

Profile image of Carlos  F. Gomes

2011, Journal of Quality in Maintenance Engineering

Related Papers

Ankur Joshi

research a literature review related in system administration and maintenance

Shiva Shangar

Alessandro Silveira

Overview of opportunities to deliver productivity projects in maintenance department

Handbook of Maintenance Management and Engineering

Aditya Parida

Journal of Quality in Maintenance Engineering

Indian Journal of Science and Technology

Aurora Irma Máynez Guaderrama

Objective: to explain the development of a questionnaire for the identification of the Critical Success Factors -CSF- of Total Productive Maintenance from the ample list of factors cited in the literature. Methods/Statistical Analysis: The questionnaire is constructed with the factors determined in the literature. The common method bias was discarded and several confirmatory analyses procedures tested the model fit. Other tests were applied for an adequate evaluation of psychometric properties and internal reliability. The main underlying proposal is the construct developed establishing a relationship between the TPM deployment and the improvement of operational performance. Findings: The questionnaire developed was validated psychometrically, was applied in 65 plants, receiving 306 questionnaires back. A ten-factor measuring model of the CSF related to TPM deployment was confirmed with different goodness of fit indexes (χ2=965.69, df=657, p 0.572 and the Common Method Bias evaluation indicates results are not biased. Validity of the construct for the operational performance subscale is acceptable, accordingly to Cua et al., 2001; Ma Kone et al., 2001; Konecny and Thun, 2011. Though Ciudad Juarez has a thirty plus years presence of multinational companies with twin plant (maquiladora) world-class operations, some techniques, such as TPM are deployed with noticeable differences among companies. The questionnaire allowed the identification of 34 influencing factors, specifically, the CSF and best practices for the TPM effective application and measures their impact in operational performance. Application/Improvements: This enhancement of the TPM explanatory capabilities allows the companies deploying it to have a better chance of success managing TPM projects under a CSF approach and better practices focus.

Carlos F. Gomes

The purpose of this study is to examine the nature of performance measures utilized by the maintenance function in today’s business organizations. In the process, the increasing variety and significance of these measures are addressed from operational and strategic perspectives. A survey-based research method was utilized to gather the research data. Several statistical procedures were utilized to analyse the data. The findings of this study point to the multifaceted nature of the maintenance measures and measurement. Multiple categories of maintenance measures were identified. These categories varied from the machine-specific, to measures impacting organizational performance. The relative lack of emphasis placed on the environment and strategic facets of maintenance is noted. The findings of this study have direct implications to organizations, which are attempting to measure the effectiveness of their maintenance efforts. The need to align the maintenance performance efforts with the organizational strategic direction is emphasized. In this context, the integration of the maintenance performance information systems with the overall organizational performance management information system might facilitate the needed alignment. This study utilizes 120 maintenance measures. As such, it represents a comprehensive view of the maintenance effort.

Jatinder Gupta

RELATED PAPERS

Modern Applied Science

arash shahin

Iskandar Nur Hidayat

Editor IJRET

Sandra Appiah

Yousif M Ibrahim

S.G. Deshmukh , Amik Garg

Benchmarking: An International Journal

S.G. Deshmukh

Journal of operations management

Patrik Jonsson

Sulo Lahdelma , Esko Juuso

Pat Banjongkit

Norlena Hasnan

Abhishek Jain

Robotics and Computer-integrated Manufacturing

Jalal Ashayeri

IYAD Alawaysheh

International Journal of Production Economics

Liliane Pintelon

stefano pippo

Matias Taye

IJMER Journal

IAEME Publication

Volume 2: Materials; Biomanufacturing; Properties, Applications and Systems; Sustainable Manufacturing

Keshav Nandurkar

Parani Tharan

Rahul Dhiman

Suhaiza Zailani

Linh Nguyen Bao

IASET US , Oti Robinson Chibu

Int. J Sup. Chain. Mgt

Taofeeq Durojaye Moshood

Nazim Baluch

divine intervention

Jerick Olpindo

Francis Amaeshi

International Journal of Business and Management

Ayman B Abdallah

Measuring OEE in Malaysian Palm Oil Mills

Applied Energy

Sơn Hải Đặng

IJERA Journal

Arsalan Allahyar

ismail droup

TJPRC Publication

RELATED TOPICS

  •   We're Hiring!
  •   Help Center
  • Find new research papers in:
  • Health Sciences
  • Earth Sciences
  • Cognitive Science
  • Mathematics
  • Computer Science
  • Academia ©2024

Smart predictive maintenance for high-performance computing systems: a literature review

  • Published: 27 April 2021
  • Volume 77 , pages 13494–13513, ( 2021 )

Cite this article

  • André Luis da Cunha Dantas Lima 1 ,
  • Vitor Moraes Aranha 1 ,
  • Caio Jordão de Lima Carvalho 1 &
  • Erick Giovani Sperandio Nascimento   ORCID: orcid.org/0000-0003-2219-0290 1  

998 Accesses

9 Citations

Explore all metrics

Predictive maintenance is an invaluable tool to preserve the health of mission critical assets while minimizing the operational costs of scheduled intervention. Artificial intelligence techniques have been shown to be effective at treating large volumes of data, such as the ones collected by the sensors typically present in equipment. In this work, we aim to identify and summarize existing publications in the field of predictive maintenance that explore machine learning and deep learning algorithms to improve the performance of failure classification and detection. We show a significant upward trend in the use of deep learning methods of sensor data collected by mission critical assets for early failure detection to assist predictive maintenance schedules. We also identify aspects that require further investigation in future works, regarding exploration of life support systems for supercomputing assets and standardization of performance metrics.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price includes VAT (Russian Federation)

Instant access to the full article PDF.

Rent this article via DeepDyve

Institutional subscriptions

research a literature review related in system administration and maintenance

Aydin O, Guldamlasioglu S (2017) Using LSTM networks to predict engine condition on large scale data processing framework. In: 2017 4th International Conference on Electrical and Electronic Engineering (ICEEE). IEEE, pp 281–285. https://doi.org/10.1109/iceee2.2017.7935834

Borghesi A, Bartolini A, Lombardi M, Milano M, Benini L (2019) Anomaly detection using autoencoders in high performance computing systems. Proc AAAI Conf Artif Intell 33:9428–9433.  https://doi.org/10.1609/aaai.v33i01.33019428

Article   Google Scholar  

Borghesi A, Libri A, Benini L, Bartolini A (2019) Online anomaly detection in hpc systems. In: 2019 IEEE International Conference on Artificial Intelligence Circuits and Systems (AICAS). IEEE, pp 229–233.  https://doi.org/10.1109/AICAS.2019.8771527

Caponetto R, Rizzo F, Russotti L, Xibilia M (2019) Deep learning algorithm for predictive maintenance of rotating machines through the analysis of the orbits shape of the rotor shaft. Ergonomics and applied human factors. International conference on smart innovation. Springer, pp 245–250.  https://doi.org/10.1007/978-3-030-22964-1_25

Chapter   Google Scholar  

Carvalho T P, Soares F A, Vita R, Francisco R d P, Basto J P, Alcalá S G (2019) A systematic literature review of machine learning methods applied to predictive maintenance. Comput Ind Eng 137:106024.  https://doi.org/10.1016/j.cie.2019.106024

Chen X, Lu CD, Pattabiraman K (2014) Failure prediction of jobs in compute clouds: a google cluster case study. In: 2014 IEEE international symposium on software reliability engineering workshops. IEEE, pp 341–346.  https://doi.org/10.1109/ISSREW.2014.105

Das A, Mueller F, Siegel C, Vishnu A (2018) Desh: deep learning for system health prediction of lead times to failure in hpc. In: Proceedings of the 27th international symposium on high-performance parallel and distributed computing. pp 40–51.  https://doi.org/10.1145/3208040.3208051

Du M, Li F, Zheng G, Srikumar V (2017) Deeplog: Anomaly detection and diagnosis from system logs through deep learning. In: Proceedings of the 2017 ACM SIGSAC Conference on Computer and Communications Security. pp 1285–1298.  https://doi.org/10.1145/3133956.3134015

Essien A, Giannetti C (2020) A deep learning model for smart manufacturing using convolutional LSTM neural network autoencoders. IEEE Trans Ind Inform 16(9):6069–6078. https://doi.org/10.1109/TII.2020.2967556

Fink O, Wang Q, Svensén M, Dersin P, Lee WJ, Ducoffe M (2020) Potential, challenges and future directions for deep learning in prognostics and health management applications. Eng Appl Artif Intell 92:103678.  https://doi.org/10.1016/j.engappai.2020.103678

Francois C (2017) Deep learning with python. Apress, Berkeley

Google Scholar  

Ghiasvand S, Ciorba F.M (2019) Anomaly detection in high performance computers: a vicinity perspective. In: 2019 18th international symposium on parallel and distributed computing (ISPDC). IEEE, pp 112–120. https://doi.org/10.1109/ISPDC.2019.00024

Giommi L, Bonacorsi D, Diotalevi T, Tisbeni S.R, Rinaldi L, Morganti L, Falabella A, Ronchieri E, Ceccanti A, Martelli B (2019) Towards predictive maintenance with machine learning at the INFN-CNAF computing centre. In: international symposium on grids & clouds (ISGC). Taipei, Taiwan: Proceedings of Science, p 17.  https://doi.org/10.22323/1.351.0003

Goodfellow I, Bengio Y, Courville A, Bengio Y (2016) Deep learning, vol 1. MIT press Cambridge, Cambridge

MATH   Google Scholar  

Guan Q, Zhang Z, Fu S (2012) Ensemble of bayesian predictors and decision trees for proactive failure management in cloud computing systems. J Commun 7(1):52–61. https://doi.org/10.4304/jcm.7.1.52-61

Haykin S (2007) Neural networks: a comprehensive foundation. Prentice-Hall Inc, New Jersey

Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural Comput 9(8):1735–1780.  https://doi.org/10.1162/neco.1997.9.8.1735

Hu B, Pang CK, Luo M, Li X, Chan HL (2012) A two-stage equipment predictive maintenance framework for high-performance manufacturing systems. In: 2012 7th IEEE Conference on Industrial Electronics and Applications (ICIEA). IEEE, pp 1343–1348. https://doi.org/10.1109/ICIEA.2012.6360931

Kitchenham B, Brereton OP, Budgen D, Turner M, Bailey J, Linkman S (2009) Systematic literature reviews in software engineering-a systematic literature review. Inf Softw Technol 51(1):7–15.  https://doi.org/10.1016/j.infsof.2008.09.009

Klinkenberg J, Terboven C, Lankes S, Müller MS (2017) Data mining-based analysis of hpc center operations. In: 2017 IEEE International Conference on Cluster Computing (CLUSTER). IEEE, pp 766–773.  https://doi.org/10.1109/CLUSTER.2017.23

Kraus M, Feuerriegel S (2019) Forecasting remaining useful life: interpretable deep learning approach via variational bayesian inferences. Decis Support Syst 125:113100.  https://doi.org/10.1016/j.dss.2019.113100

Li X, Ding Q, Sun JQ (2018) Remaining useful life estimation in prognostics using deep convolution neural networks. Reliab Eng Syst Saf 172:1–11.  https://doi.org/10.1016/j.ress.2017.11.021

Lima ALDCD, Aranha VM, Sperandio EG (2019) Manutenção preditiva aplicada a ambientes de missão crítica de supercomputação utilizando inteligência artificial: Uma revisão sistemática de literatura. In: Anais do V Simpósio Internacional de Inovação e Tecnologia. Blucher Engineering Proceedings, pp 657–664. https://doi.org/10.5151/siintec2019-82

Luo B, Wang H, Liu H, Li B, Peng F (2018) Early fault detection of machine tools based on deep learning and dynamic identification. IEEE Trans Ind Electron 66(1):509–518. https://doi.org/10.1109/TIE.2018.2807414

Martínez D, Brewer W, Strelzoff A, Wilson A, Wade D (2020) Rotorcraft virtual sensors via deep regression. J Parallel Distrib Comput 135:114–126.  https://doi.org/10.1016/j.jpdc.2019.08.008

Mathew V, Toby T, Singh V, Rao B.M, Kumar M.G (2017) Prediction of Remaining Useful Lifetime (RUL) of turbofan engine using machine learning. In: 2017 IEEE International Conference on Circuits and Systems (ICCS). IEEE, pp 306–311.  https://doi.org/10.1109/ICCS1.2017.8326010

Mohammed B, Awan I, Ugail H, Younas M (2019) Failure prediction using machine learning in a virtualised HPC system and application. Cluster Computing 22(2):471–485.  https://doi.org/10.1007/s10586-019-02917-1

Nakka N, Agrawal A, Choudhary A (2011) Predicting node failure in high performance computing systems from failure and usage logs. In: 2011 IEEE international symposium on parallel and distributed processing workshops and Phd Forum. IEEE, pp 1557–1566.  https://doi.org/10.1109/IPDPS.2011.310

Nguyen KT, Medjaher K (2019) A new dynamic predictive maintenance framework using deep learning for failure prognostics. Reliab Eng Syst Saf 188:251–262. https://doi.org/10.1016/j.ress.2019.03.018

Nie B, Xue, J, Gupta S, Patel T, Engelmann C, Smirni E, Tiwari D (2018) Machine learning models for GPU error prediction in a large scale HPC system. In: 2018 48th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE, pp 95–106. https://doi.org/10.1109/DSN.2018.00022

Souza RM, Nascimento EGS, Miranda UA, Silva WJD, Lepikson HA (2021) Deep learning for diagnosis and classification of faults in industrial rotating machinery. Comput Ind Eng 153:107060. https://doi.org/10.1016/j.cie.2020.107060

Susto G.A, McLoone S, Pagano D, Schirru A, Pampuri S, Beghi A (2013) Prediction of integral type failures in semiconductor manufacturing through classification methods. In: 2013 IEEE 18th Conference on Emerging Technologies & Factory Automation (ETFA). IEEE, pp 1–4. https://doi.org/10.1109/ETFA.2013.6648127

Susto G.A, Schirru A, Pampuri S, McLoone S, Beghi A (2014) Machine learning for predictive maintenance: a multiple classifier approach. IEEE Trans Ind Inform 11(3):812–820. https://doi.org/10.1109/TII.2014.2349359

Tuncer O, Ates E, Zhang Y, Turk A, Brandt J, Leung VJ, Egele M, Coskun AK (2017) Diagnosing performance variations in HPC applications using machine learning. International supercomputing conference. Springer, pp 355–373.  https://doi.org/10.1007/978-3-319-58667-0_19

Wu Y, Yuan M, Dong S, Lin L, Liu Y (2018) Remaining useful life estimation of engineered systems using vanilla LSTM neural networks. Neurocomputing 275:167–179.  https://doi.org/10.1016/j.neucom.2017.05.063

Yurek O.E, Birant D (2019) Remaining useful life estimation for predictive maintenance using feature engineering. In: Innovations in Intelligent Systems and Applications Conference (ASYU). IEEE, pp 1–5. https://doi.org/10.1109/ASYU48272.2019.8946397

Zhang J, Wang P, Yan R, Gao R.X (2018) Long short-term memory for machine remaining life prediction. J Manuf Syst 48:78–86.  https://doi.org/10.1016/j.jmsy.2018.05.011

Zhang K, Xu J, Min M.R, Jiang G, Pelechrinis K, Zhang H (2016) Automated IT system failure prediction: a deep learning approach. In: 2016 IEEE International Conference on Big Data (Big Data). IEEE, pp 1291–1300. https://doi.org/10.1109/BigData.2016.7840733

Zhang S, Li X, Wang J, Su S (2017) Curve-registration-based feature extraction for predictive maintenance of industrial equipment. International Conference on Collaborative Computing: Networking, Applications and Worksharing. Springer, pp 253–263.  https://doi.org/10.1007/978-3-030-00916-8_24

Zhao H, Wang J, Gao P (2017) A Deep Learning Approach for Condition-Based Monitoring and Fault Diagnosis of Rod Pump System. STIoT Editorial Board 32. https://doi.org/10.29268/stsc.2017.0003

Zheng S, Farahat A, Gupta C (2019) Generative adversarial networks for failure prediction. Joint European Conference on Machine Learning and Knowledge Discovery in Databases. Springer, pp 621–637.  https://doi.org/10.1007/978-3-030-46133-1_37

Zhu B, Wang G, Liu X, Hu D, Lin S, Ma J (2013) Proactive drive failure prediction for large scale storage systems. In: IEEE 29th symposium on mass storage systems and technologies (MSST). IEEE, pp 1–5. https://doi.org/10.1109/MSST.2013.6558427

Download references

Acknowledgements

We would like to thank ATOS BULL, as well as the Supercomputing Center for Industrial Innovation (CS2I) and the Reference Center on Artificial Intelligence (CRIA), both from SENAI CIMATEC, for providing the infrastructure and environment for the execution of this research.

Author information

Authors and affiliations.

Faculdade de Tecnologia SENAI CIMATEC Salvador, SENAI CIMATEC Manufacturing and Technology Integrated Campus, Salvador, BA, Brazil

André Luis da Cunha Dantas Lima, Vitor Moraes Aranha, Caio Jordão de Lima Carvalho & Erick Giovani Sperandio Nascimento

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Erick Giovani Sperandio Nascimento .

Ethics declarations

Conflict of interest.

The authors declare that they have no conflict of interest.

Additional information

Publisher's note.

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Lima, A.L.d.C.D., Aranha, V.M., Carvalho, C.J.d.L. et al. Smart predictive maintenance for high-performance computing systems: a literature review. J Supercomput 77 , 13494–13513 (2021). https://doi.org/10.1007/s11227-021-03811-7

Download citation

Accepted : 12 April 2021

Published : 27 April 2021

Issue Date : November 2021

DOI : https://doi.org/10.1007/s11227-021-03811-7

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

  • Predictive maintenance
  • High-performance computing
  • Artificial intelligence
  • Deep learning
  • Find a journal
  • Publish with us
  • Track your research

To read this content please select one of the options below:

Please note you do not have access to teaching notes, a literature review of maintenance performance measurement: a conceptual framework and directions for future research.

Journal of Quality in Maintenance Engineering

ISSN : 1355-2511

Article publication date: 31 May 2011

This research aims to examine the relevant literature related to maintenance performance measurement in the manufacturing sector. In the process, innovative approaches and models utilized to measure and manage maintenance performance in manufacturing operational settings are classified and examined. Based on this investigation, future research directions and themes are identified.

Design/methodology/approach

A database of 251 peer‐reviewed publications, published during the last 30 years, was utilized for the purpose of this research. The published works included contributions from both practitioners and scholars.

This literature review‐based research revealed important themes related to evolution of maintenance performance management. These themes focus on the effective utilization of maintenance resources, information systems support, and human factor management. Based on this literature review, a conceptual framework, which traces the different operational and organizational facets of the evolution of maintenance performance management, is offered.

Research limitations/implications

Based on the findings of this study, it is concluded that the area of maintenance performance and management is in need of more future systematic research efforts aimed at solidifying theoretical constructs and promoting the utilization of more practical applications.

Practical implications

Findings derived from this investigation have relevant manufacturing implications. In this context, understanding the different approaches to maintenance performance measurement and management, as utilized in manufacturing organizations, is critical to these organizations' performance improvement efforts.

Originality/value

Understanding the types and scopes of the different approaches and models utilized to manage and measure maintenance performance in manufacturing operational settings is important in light of the growing competitiveness of the manufacturing sector.

  • Maintenance
  • Performance measures
  • Manufacturing industries

Simões, J.M. , Gomes, C.F. and Yasin, M.M. (2011), "A literature review of maintenance performance measurement: A conceptual framework and directions for future research", Journal of Quality in Maintenance Engineering , Vol. 17 No. 2, pp. 116-137. https://doi.org/10.1108/13552511111134565

Emerald Group Publishing Limited

Copyright © 2011, Emerald Group Publishing Limited

Related articles

We’re listening — tell us what you think, something didn’t work….

Report bugs here

All feedback is valuable

Please share your general feedback

Join us on our journey

Platform update page.

Visit emeraldpublishing.com/platformupdate to discover the latest news and updates

Questions & More Information

Answers to the most commonly asked questions here

U.S. flag

An official website of the United States government.

Here’s how you know

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

  • American Job Centers
  • Apprenticeship
  • Demonstration Grants
  • Farmworkers
  • Federal Bonding Program
  • Foreign Labor Certification
  • Indians and Native Americans
  • Job Seekers
  • Layoffs and Rapid Response
  • National Dislocated Worker Grants
  • Older Workers
  • Skills Training Grants
  • Trade Adjustment Assistance
  • Unemployment Insurance
  • Workforce Innovation and Opportunity Act (WIOA)
  • WIOA Adult Program
  • Advisories and Directives
  • Regulations
  • Labor Surplus Area
  • Performance
  • Recovery-Ready Workplace Resource Hub
  • Research and Evaluation
  • ETA News Releases
  • Updates for Workforce Professionals
  • Regional Offices
  • Freedom of Information Act

The Role of the Workforce System in Addressing the Opioid Crisis: A Resource Guide

Publication info, research methodology, description, other products.

This guide provides information on resources that could be used to plan and implement new strategies to address the impacts of opioid (and other substance) use disorders on workers and workplaces. The guide was developed as part of an evaluation of six U.S. Department of Labor (DOL) Dislocated Worker Demonstration grants to address the National Health Emergency (NHE) of the opioid crisis. The guide complements other products developed as part of the study, i.e., a literature review, a final report on the evaluation of the DOL demonstration grants, and four strategy "spotlights" on promising programs and practices implemented under the grants.

Resources identified in the guide are related to three broad areas: 1) employment supports for people in recovery, 2) approaches that employers can use to address opioid use disorder in the workplace and support affected individuals, and 3) strategies to develop the health care workforce to help address the opioid crisis. Information included in the guide covers relevant publications, websites, and interactive tools, as well as descriptions of programs being implemented across the country (and websites to access information on them).

The guide identifies resources available from DOL (including those developed by the Employment and Training Administration and found on its WorkforceGPS technical assistance website) and materials related to particular programs and practices implemented under the NHE grants. It also includes resources from other federal agencies (such as the Substance Abuse and Mental Health Services Administration, the Administration for Children and Families, the National Institute for Occupational Safety and Health, and the Centers for Disease Control and Prevention) and from various states, universities, and business organizations.

IMAGES

  1. How to write a literature review in research paper

    research a literature review related in system administration and maintenance

  2. (PDF) Healthcare facilities maintenance management: a literature review

    research a literature review related in system administration and maintenance

  3. √ Free APA Literature Review Format Template

    research a literature review related in system administration and maintenance

  4. Writing a Research Paper Literature Review in APA or MLA

    research a literature review related in system administration and maintenance

  5. IT SA01 Systems Administration AND Maintenance 2

    research a literature review related in system administration and maintenance

  6. 5 Ongoing System Maintenance, Administration, and

    research a literature review related in system administration and maintenance

VIDEO

  1. Systematic literature review

  2. SYSTEMATIC AND LITERATURE REVIEWS

  3. Academic Writing Workshop

  4. Research (Literature Review) Groups 9 & 10

  5. Literature review and its process

  6. How to find research papers for ur literature review using IA #academicwriting #researchtips #thesis

COMMENTS

  1. Maintenance management: Literature review and directions

    Purpose The purpose of this paper is to review the literature on maintenance management and suggest possible gaps from the point of view of researchers and practitioners. Design/methodology ...

  2. Maintenance management: literature review and directions

    Subsequently, various emerging trends in the field of maintenance management are identified to help researchers specifying gaps in the literature and direct research efforts suitably., - The paper contains a comprehensive listing of publications on the field in question and their classification according to various attributes.

  3. The advancement of maintenance information technology: A literature review

    Purpose. Maintenance management information technology (MMIT) systems have existed for some 40 years. The purpose of this paper is to investigate the advancement of these systems and compares the development of MMIT with other corporate information technology (IT) systems.

  4. System Maintenance: Trends in Management and Technology

    Abstract. Modern day systems are large, complex and automated. The high demands on the performance of such systems has created a need for new management and engineering solutions in the area of the maintenance of the complex systems. This need is mainly motivated by the steeply increasing cost of downtime. This chapter presents an overview of ...

  5. Healthcare facilities maintenance management: a literature review

    Literature on maintenance management in healthcare facilities and hospital buildings has so far been very limited. Recently published literature focusing on healthcare facilities management and its maintenance management functions is classified into various areas and sub-areas. The paper highlights gaps in the literature and suggests avenues ...

  6. Condition-based maintenance implementation: a literature review

    Condition-Based Maintenance (CBM) is a strategy that considers information about the equipment condition to recommend appropriate maintenance actions. The main purpose of CBM is to prevent functional failures or a significant performance decrease of the monitored equipment. CBM relies on a wide range of resources and techniques required to ...

  7. A literature review on selective maintenance for multi‐unit systems

    Based on these features, a set of criteria that have been considered in selective maintenance optimization are summarized into 3 categories: system characteristics, maintenance characteristics, and mission profile characteristics. Based on these criteria, a comprehensive literature review on selective maintenance is undertaken.

  8. Maintenance and Operation of Infrastructure Systems: Review

    This paper presents a review of key aspects involved in the maintenance and operation of infrastructure under uncertainty. It discusses the main conceptual and theoretical principles and guides the reader through different aspects of the problem by offering a large set of state-of-the-art references.

  9. How to conduct systematic literature reviews in management research: a

    The application of systematic or structured literature reviews (SLRs) has developed into an established approach in the management domain (Kraus et al. 2020), with 90% of management-related SLRs published within the last 10 years (Clark et al. 2021).Such reviews help to condense knowledge in the field and point to future research directions, thereby enabling theory development (Fink 2010 ...

  10. A literature review of maintenance performance measurement: a

    For this purpose, the relevant literature is examined, classified and analyzed. 3. Method For the purpose of this research, an exhaustive and systematic search of the literature related to maintenance management and maintenance performance measurement was conducted. The time frame for this literature review was from 1979 to 2009.

  11. PDF Researching system administration

    research by both identifying principles for evaluating system administration research, and by identifying directions of future research. We start by describing principles for evaluating system administration research in sec-tion 1.2. We identify and explain the principles to help researchers avoid some work of deploying their systems.

  12. Smart predictive maintenance for high-performance computing ...

    This study was conducted as a systematic review of the literature based on original directives as mentioned by [19, 23].In this case, the objectives of this review are: to identify works that offer solutions developed with artificial intelligence algorithms to predict failures in mission critical environments for supercomputing and that use deep learning techniques; to identify research ...

  13. Integration of Maintenance Management System Functions with ...

    Industry 4.0 is the latest technological age, in which recent technological developments are being integrated within industrial systems. Consequently, maintenance management of current industrial manufacturing systems is affected by the emergence of the technologies and features of Industry 4.0. This study aimed to conduct a comprehensive literature review to understand how Industry 4.0 ...

  14. Systematic Literature Review Predictive Maintenance Solutions for SMEs

    A systematic review of the literature (SLR) is a means of identifying, evaluating, and interpreting all available research related to a particular research question or a topic or phenomenon of interest. Individual studies that contribute to a systematic review are called preliminary studies. A systematic review is a kind of secondary study .

  15. On the concept of e-maintenance: Review and current research

    Abstract. The importance of the maintenance 1 function has increased because of its role in keeping and improving system availability and safety, as well as product quality. To support this role, the development of the communication and information technologies has allowed the emergence of the concept of e-maintenance.

  16. Writing a literature review

    Writing a literature review requires a range of skills to gather, sort, evaluate and summarise peer-reviewed published data into a relevant and informative unbiased narrative. Digital access to research papers, academic texts, review articles, reference databases and public data sets are all sources of information that are available to enrich ...

  17. A literature review of maintenance performance measurement: A

    The published works included contributions from both practitioners and scholars., - This literature review‐based research revealed important themes related to evolution of maintenance performance management. These themes focus on the effective utilization of maintenance resources, information systems support, and human factor management.

  18. Re-examining systematic literature review in management research

    1. Introduction. As management research grows in volume and scope, topic fragmentation and interconnection increase with other fields (Tranfield, Denyer, & Smart, 2003).To help make sense of this fragmentation of research, Transfield and colleagues introduced the management field to a tool used primarily in medicine/health called a systematic literature review ("SLR" going forward).

  19. LITERATURE REVIEW AND DIRECTIONS

    Manufacturing system has been rapidly developing during these decades. Within this advancement, maintenance becomes an important supporting factor. Maintenance aims to develop better production processes in order to perform as expected. Preventive maintenance (PM) is one of maintenance strategies to prevent incipient failures. Many scholars have been studying PM in numerous occasions as well ...

  20. Land

    A contemporary review of land administration, from the perspective of systems maintenance, is provided. A special emphasis is placed on emerging fit-for-purpose land administration solutions. The research synthesis uses reputable sources from the contemporary era. Results show the challenges of maintaining land administration systems and the data held are long recognized. The 1970s-1980s ...

  21. Understanding software maintenance and evolution by analyzing

    Journal of Software Maintenance and Evolution: Research and Practice is a computer science and software engineering journal publishing new ideas for developing and improving software. Abstract Understanding, managing and reducing costs and risks inherent in change are key challenges of software maintenance and evolution, addressed in empirical ...

  22. The Role of the Workforce System in Addressing the Opioid Crisis: A

    Resources identified in the guide are related to three broad areas: 1) employment supports for people in recovery, 2) approaches that employers can use to address opioid use disorder in the workplace and support affected individuals, and 3) strategies to develop the health care workforce to help address the opioid crisis.

  23. Review on maintenance issues toward building ...

    A systematic literature review (SLR) was conducted to examine the issues or factors that affect building maintenance practice. The review included articles on issues affecting building maintenance practice and recommendations to minimize the issues. The maintenance practice issues were categorized into planning, management, staff, competency ...