IDEAS home Printed from https://ideas.repec.org/a/hin/complx/3759514.html
   My bibliography  Save this article

An Approach to Integrating Tactical Decision-Making in Industrial Maintenance Balance Scorecards Using Principal Components Analysis and Machine Learning

Author

Listed:
  • Néstor Rodríguez-Padial
  • Marta Marín
  • Rosario Domingo

Abstract

The uncertainty of demand has led production systems to become increasingly complex; this can affect the availability of the machines and thus their maintenance. Therefore, it is necessary to adequately manage the information that facilitates decision-making. This paper presents a system for making decisions related to the design of customized maintenance plans in a production plant. This paper addresses this tactical goal and aims to provide greater knowledge and better predictions by projecting reliable behavior in the medium-term, integrating this new functionality into classic Balance Scorecards, and making it possible to extend their current measuring function to a new aptitude: predicting evolution based on historical data. In the proposed Custom Balance Scorecard design, an exploratory data phase is integrated with another analysis and prediction phase using Principal Component Analysis algorithms and Machine Learning that uses Artificial Neural Network algorithms. This new extension allows better control over the maintenance function of an industrial plant in the medium-term with a yearly horizon taken over monthly intervals which allows the measurement of the indicators of strategic productive areas and the discovery of hidden behavior patterns in work orders. In addition, this extension enables the prediction of indicator outcomes such as overall equipment efficiency and mean time to failure.

Suggested Citation

  • Néstor Rodríguez-Padial & Marta Marín & Rosario Domingo, 2017. "An Approach to Integrating Tactical Decision-Making in Industrial Maintenance Balance Scorecards Using Principal Components Analysis and Machine Learning," Complexity, Hindawi, vol. 2017, pages 1-15, October.
  • Handle: RePEc:hin:complx:3759514
    DOI: 10.1155/2017/3759514
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/8503/2017/3759514.pdf
    Download Restriction: no

    File URL: http://downloads.hindawi.com/journals/8503/2017/3759514.xml
    Download Restriction: no

    File URL: https://libkey.io/10.1155/2017/3759514?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Luis Miguel Calvo & Rosario Domingo, 2017. "CO 2 Emissions Reduction and Energy Efficiency Improvements in Paper Making Drying Process Control by Sensors," Sustainability, MDPI, vol. 9(4), pages 1-17, March.
    2. Olivencia Polo, Fernando A. & Ferrero Bermejo, Jesús & Gómez Fernández, Juan F. & Crespo Márquez, Adolfo, 2015. "Failure mode prediction and energy forecasting of PV plants to assist dynamic maintenance tasks by ANN based models," Renewable Energy, Elsevier, vol. 81(C), pages 227-238.
    3. Palocsay, Susan W. & Markham, Ina S. & Markham, Steven E., 2010. "Utilizing and teaching data tools in Excel for exploratory analysis," Journal of Business Research, Elsevier, vol. 63(2), pages 191-206, February.
    4. Rosario Domingo & Sergio Aguado, 2015. "Overall Environmental Equipment Effectiveness as a Metric of a Lean and Green Manufacturing System," Sustainability, MDPI, vol. 7(7), pages 1-17, July.
    5. Waeyenbergh, Geert & Pintelon, Liliane, 2002. "A framework for maintenance concept development," International Journal of Production Economics, Elsevier, vol. 77(3), pages 299-313, June.
    6. Wang, Ling & Chu, Jian & Wu, Jun, 2007. "Selection of optimum maintenance strategies based on a fuzzy analytic hierarchy process," International Journal of Production Economics, Elsevier, vol. 107(1), pages 151-163, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Thanh-Lam Nguyen, 2019. "STEAM-ME: A Novel Model for Successful Kaizen Implementation and Sustainable Performance of SMEs in Vietnam," Complexity, Hindawi, vol. 2019, pages 1-23, February.
    2. Rosario Domingo & Julio Blanco-Fernández & Jorge Luis García-Alcaraz & Leonardo Rivera, 2018. "Complexity in Manufacturing Processes and Systems," Complexity, Hindawi, vol. 2018, pages 1-3, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Faccio, M. & Persona, A. & Sgarbossa, F. & Zanin, G., 2014. "Industrial maintenance policy development: A quantitative framework," International Journal of Production Economics, Elsevier, vol. 147(PA), pages 85-93.
    2. Alsyouf, Imad, 2009. "Maintenance practices in Swedish industries: Survey results," International Journal of Production Economics, Elsevier, vol. 121(1), pages 212-223, September.
    3. B. Kirubakaran & M. Ilangkumaran, 2016. "Selection of optimum maintenance strategy based on FAHP integrated with GRA–TOPSIS," Annals of Operations Research, Springer, vol. 245(1), pages 285-313, October.
    4. Özcan, Evren Can & Ünlüsoy, Sultan & Eren, Tamer, 2017. "A combined goal programming – AHP approach supported with TOPSIS for maintenance strategy selection in hydroelectric power plants," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 1410-1423.
    5. Pinciroli, Luca & Baraldi, Piero & Zio, Enrico, 2023. "Maintenance optimization in industry 4.0," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    6. Priyank Srivastava & Dinesh Khanduja & V. P. Agrawal, 2020. "Agile maintenance attribute coding and evaluation based decision making in sugar manufacturing plant," OPSEARCH, Springer;Operational Research Society of India, vol. 57(2), pages 553-583, June.
    7. Ishizaka, Alessio & Nemery, Philippe, 2014. "Assigning machines to incomparable maintenance strategies with ELECTRE-SORT," Omega, Elsevier, vol. 47(C), pages 45-59.
    8. Li, Lin & Ni, Jun, 2009. "Short-term decision support system for maintenance task prioritization," International Journal of Production Economics, Elsevier, vol. 121(1), pages 195-202, September.
    9. Benyou Jia & Slobodan P. Simonovic & Pingan Zhong & Zhongbo Yu, 2016. "A Multi-Objective Best Compromise Decision Model for Real-Time Flood Mitigation Operations of Multi-Reservoir System," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 30(10), pages 3363-3387, August.
    10. Peters, Lennart & Madlener, Reinhard, 2017. "Economic evaluation of maintenance strategies for ground-mounted solar photovoltaic plants," Applied Energy, Elsevier, vol. 199(C), pages 264-280.
    11. Miguel A. Rodríguez-López & Luis M. López-González & Luis M. López-Ochoa & Jesús Las-Heras-Casas, 2018. "Methodology for Detecting Malfunctions and Evaluating the Maintenance Effectiveness in Wind Turbine Generator Bearings Using Generic versus Specific Models from SCADA Data," Energies, MDPI, vol. 11(4), pages 1-22, March.
    12. Roxana POPA STRAINU & Mircea GEORGESCU, 2015. "Support Management Decisions In Small And Medium Companies," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 16, pages 167-181, December.
    13. Alsyouf, Imad, 2007. "The role of maintenance in improving companies' productivity and profitability," International Journal of Production Economics, Elsevier, vol. 105(1), pages 70-78, January.
    14. Yu-Chung Tsao & Thuy-Linh Vu, 2023. "Electricity pricing, capacity, and predictive maintenance considering reliability," Annals of Operations Research, Springer, vol. 322(2), pages 991-1011, March.
    15. Giancarlo Nota & Francesco David Nota & Domenico Peluso & Alonso Toro Lazo, 2020. "Energy Efficiency in Industry 4.0: The Case of Batch Production Processes," Sustainability, MDPI, vol. 12(16), pages 1-28, August.
    16. de Jonge, Bram & Teunter, Ruud & Tinga, Tiedo, 2017. "The influence of practical factors on the benefits of condition-based maintenance over time-based maintenance," Reliability Engineering and System Safety, Elsevier, vol. 158(C), pages 21-30.
    17. repec:jle:journl:132 is not listed on IDEAS
    18. Muchiri, Peter & Pintelon, Liliane & Gelders, Ludo & Martin, Harry, 2011. "Development of maintenance function performance measurement framework and indicators," International Journal of Production Economics, Elsevier, vol. 131(1), pages 295-302, May.
    19. Lucia Reis Peixoto Roselli & Adiel Teixeira Almeida & Eduarda Asfora Frej, 2019. "Decision neuroscience for improving data visualization of decision support in the FITradeoff method," Operational Research, Springer, vol. 19(4), pages 933-953, December.
    20. Orlando Durán & Andrea Capaldo & Paulo Andrés Duran Acevedo, 2018. "Sustainable Overall Throughputability Effectiveness (S.O.T.E.) as a Metric for Production Systems," Sustainability, MDPI, vol. 10(2), pages 1-15, January.
    21. María Carmen Carnero, 2020. "Fuzzy Multicriteria Models for Decision Making in Gamification," Mathematics, MDPI, vol. 8(5), pages 1-23, May.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:hin:complx:3759514. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.