Synapse
⌘+K
Synapse
PulseExploreClubsResearchersJournals
Instagram
HomeClubsExplore
October 3, 2025Applied SciencesOpen Access

Hybrid Architecture to Predict the Remaining Useful Lifetime of an Industrial Machine from Its Specific Energy Consumption

View Full Paper
Ask AI
Bookmark
Share

Authors

DRDiego Rodriguez-ObandoJGJavier Rosero GarcíaEREsteban Rosero

Discussion

Loading...

Member takes

Overview

Data-driven model predicts remaining useful lifetime in industrial machines, highlighting predictive maintenance.

Key Points

  • The hybrid architecture successfully predicts the remaining useful lifetime of industrial machine parts.
  • Using specific energy consumption data, predictions enhance the accuracy and robustness of maintenance strategies.
  • The data-driven approach continuously improves the recursive database, allowing real-time updates and feature extraction.
  • Analyzing real data from a sugarcane shredder machine illustrates the architecture's practical application.

Cite This Study

Rodriguez-Obando et al. (2025) studied this question.

synapsesocial.com/papers/68e040f7a99c246f578b3acbhttps://doi.org/10.3390/app151910657
View Full Paper
Ask AI
Bookmark
Share

Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Hybrid Architecture to Predict the Remaining Useful Lifetime of an Industrial Machine from Its Specific Energy Consumption2025
  2. 2Remaining Useful Life ( <scp>RUL</scp> ) Prediction Methods for Machine Health Estimation and Fault Diagnosis: A Comprehensive Review of Latest Techniques and Future Prospects2026 · 1 citations
  3. 3Degradation index‐based prediction for remaining useful life using multivariate sensor data2024 · 1 citations
  4. 4Toward Proactive Maintenance: A Multi-Tiered Architecture for Industrial Equipment Health Monitoring and Remaining Useful Life Prediction2024 · 2 citations
  5. 5A degradation index model for maintenance prediction run-to-failure in production systems2026