The Survival Analysis for a Predictive Maintenance in Manufacturing - Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems Access content directly
Conference Papers Year : 2021

The Survival Analysis for a Predictive Maintenance in Manufacturing

Bahrudin Hrnjica
  • Function : Author
  • PersonId : 1132109
Selver Softic
  • Function : Author
  • PersonId : 1132110

Abstract

The Predictive Maintenance (PdM) as a tool for detection future failures in manufacturing has recognized as innovative and effective method. Different approaches for PdM have been developed in order to compromise availability of data and demanding needs for predictions. In this paper the Survival Analysis (SA) method was used for the probability estimation for the machine failure. The paper presents the use of the two most popular SA models Kaplan-Meier non-parametric and Cox proportional hazard models. The first model was used to estimate the probability of machine to survive certain amount of cycles time. The Cox proportional model was used to find out the most significant covariates in the observed data set. The analysis shown that use of SA in the PdM is a challenging task and can be used as additional tool for failure analysis. However, due to its foundation there are several limitations in the application of SA which in most cases are the availability of the right information in the data set.identified
Fichier principal
Vignette du fichier
520759_1_En_9_Chapter.pdf (850.88 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-04022124 , version 1 (09-03-2023)

Licence

Attribution

Identifiers

Cite

Bahrudin Hrnjica, Selver Softic. The Survival Analysis for a Predictive Maintenance in Manufacturing. IFIP International Conference on Advances in Production Management Systems (APMS), Sep 2021, Nantes, France. pp.78-85, ⟨10.1007/978-3-030-85906-0_9⟩. ⟨hal-04022124⟩
34 View
18 Download

Altmetric

Share

Gmail Facebook X LinkedIn More