The benefits of predictive maintenance in manufacturing excellence: a case study to establish reliable methods for predicting failures.
preprint
OA: closed
CC-BY-4.0
Abstract
Abstract In the course of manufacturing excellence, decision makers are consistently confronted with the task of making choices that will enhance and meet the plant's requirements. To this end, it is essential to maintain machines and equipment in a timely manner, which can prove to be one of the primary challenges. Predictive maintenance (PdM) technology can enable real-time maintenance, providing numerous benefits such as reduced downtime, lower costs, and improved production quality. This article tries to demonstrate efficient physical parameters used in PdM field. The paper presents a case study operated in industrial production process to compare between the most used algorithm in predicting equipment failures. Future research can improve prediction accuracy with other artificial intelligence tools.
My notes (saved in your browser only)
Citation neighborhood (no data yet)
We don't have any in-corpus citations linked to this paper yet. The paper's references may be in our DB but unresolved to ``paper_id`` (resolution happens at ingest when the cited DOI matches a row we already have). Run the cross-source citation reconcile pass to retry.
Source provenance
- europepmc
- last seen: 2026-05-19T01:45:01.086888+00:00
- unpaywall
- last seen: 2026-05-27T02:00:06.600101+00:00
License: CC-BY-4.0