EVALUATING THE EFFECTIVENESS OF PREDICTIVE MAINTENANCE MODELS IN ENHANCING EQUIPMENT RELIABILITY AND REDUCING DOWNTIME IN HIGH-THROUGHPUT MANUFACTURING

Predictive maintenance (PdM) models have emerged as a cornerstone of smart manufacturing, leveraging data-driven insights to enhance equipment reliability and minimize downtime. This study evaluates the effectiveness of PdM models in high-throughput manufacturing environments, highlighting their capabilities in failure prediction, cost reduction, and operational optimization. The paper synthesizes recent advances, identifies critical challenges, and presents empirical evidence supporting the implementation of PdM strategies in improving manufacturing efficiency.

Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-01-22
DOI
https://doi.org/10.5281/zenodo.14715892
Primary Topic
Machine Fault Diagnosis Techniques
Type
article
Field-Weighted Citation Impact
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article

EVALUATING THE EFFECTIVENESS OF PREDICTIVE MAINTENANCE MODELS IN ENHANCING EQUIPMENT RELIABILITY AND REDUCING DOWNTIME IN HIGH-THROUGHPUT MANUFACTURING

Zenodo (CERN European Organization for Nuclear Research)
Machine Fault Diagnosis Techniques
article

EVALUATING THE EFFECTIVENESS OF PREDICTIVE MAINTENANCE MODELS IN ENHANCING EQUIPMENT RELIABILITY AND REDUCING DOWNTIME IN HIGH-THROUGHPUT MANUFACTURING

article en

Abstract

Predictive maintenance (PdM) models have emerged as a cornerstone of smart manufacturing, leveraging data-driven insights to enhance equipment reliability and minimize downtime. This study evaluates the effectiveness of PdM models in high-throughput manufacturing environments, highlighting their capabilities in failure prediction, cost reduction, and operational optimization. The paper synthesizes recent advances, identifies critical challenges, and presents empirical evidence supporting the implementation of PdM strategies in improving manufacturing efficiency.

Zenodo (CERN European Organization for Nuclear Research)
Industry, innovation and infrastructure
Openalex Percentile: Top 48%
Machine Fault Diagnosis Techniques
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EVALUATING THE EFFECTIVENESS OF PREDICTIVE MAINTENANCE MODELS IN ENHANCING EQUIPMENT RELIABILITY AND REDUCING DOWNTIME IN HIGH-THROUGHPUT MANUFACTURING · Zenodo (CERN European Organization for Nuclear Research) (2025) | TGRS Research Map | TGRS