Skip to main content

Abstract

GAMM (Graphical Analysis for Maintenance Management) is a method that supports decision-making in maintenance management through the visualization and graphical analysis of reliability data. One of the most important features of GAMM is that fosters the combination of reliability assessment with the current asset performance analysis. As a basis for reliability analysis, the GAMM method uses a nonparametric estimator of the reliability function using historical data, sometimes in very limited amounts. For successful results, experience and knowledge in maintenance management are strictly necessary. At the same time, experience shows that the method may become really amicable for managers due to clear visualization and by using a set of basic rules. The analysis can be made per category of assets, per asset, per maintenance skill or per failure mode. In this paper we present certain rules to be applied when using GAMM with the intention to show the capabilities of the method and the possibilities that offers for practical maintenance and asset performance analysis.

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

Access this chapter

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 169.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 219.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 219.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

References

  1. Kobbacy KAH, Jeon J (2001) The development of a hybrid intelligent maintenance optimisation system (HIMOS). J Oper Res Soc 52:762–778

    Article  Google Scholar 

  2. Barberá L, Crespo A, Viveros P, Stegmaier R (2012) Advanced model for maintenance management in a continuous improvement cycle: integration into the business strategy. Int J Syst Assur Eng Manag 3(1):47–63 (Jan–Mar 2012)

    Article  Google Scholar 

  3. Barberá L, Crespo A, Viveros P, Arata A (2013) The graphical analysis for maintenance management method: A quantitative graphical analysis to support maintenance management decision making. J Qual Reliab Eng Int 29(77–87):5

    Google Scholar 

  4. Barberá L, Crespo A, Viveros P, Stegmaier R (2013) A case study of GAMM (Graphical analysis for maintenance management) in the mining industry. Reliab Eng Syst Saf (RESS) 121:113–120

    Article  Google Scholar 

  5. Barberá L, Crespo A, Viveros P, Stegmaier R (2013) A case study of GAMM (Graphical analysis for maintenance management) applied to water pumps in a sewage treatment plant, chile. J Qual Reliab Eng Int

    Google Scholar 

  6. Surucu B, Sazak HS (2013) Graphical methods for reliability data. In Wiley encyclopedia of operations research and management science, pp 1–11. https://doi.org/10.1002/9780470400531.eorms1062. Copyright © 2010 John Wiley & Sons, Inc

  7. Kobbacy K, Proudlove AH, Harper MA (1995) Towards an intelligent maintenance optimisation system. J Oper Res Soc 46:831–853

    Article  Google Scholar 

  8. O’Keefe RM, Balci O, Smith EP (1987) Validating expert system performance. IEEE Expert Winter:81–87

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Adolfo Crespo Márquez .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2019 Springer Nature Switzerland AG

About this paper

Check for updates. Verify currency and authenticity via CrossMark

Cite this paper

Crespo Márquez, A. et al. (2019). Combining Reliability Assessment with Maintenance Performance Analysis Using GAMM. In: Mathew, J., Lim, C., Ma, L., Sands, D., Cholette, M., Borghesani, P. (eds) Asset Intelligence through Integration and Interoperability and Contemporary Vibration Engineering Technologies. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-319-95711-1_11

Download citation

  • DOI: https://doi.org/10.1007/978-3-319-95711-1_11

  • Published:

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-95710-4

  • Online ISBN: 978-3-319-95711-1

  • eBook Packages: EngineeringEngineering (R0)

Publish with us

Policies and ethics