Implementation of condition-based maintenance (CBM) with FMEA approach to improve productivity of the auto insert machine in electronic component manufacturing
This study explores the implementation of Condition-Based Maintenance (CBM) integrated with Failure Mode and Effects Analysis (FMEA) on the Auto Insert Connectors FFC machine, a critical asset in the assembly process of Flexible Flat Cable (FFC) connectors within the electronic components manufactur...
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| Format: | Article |
| Language: | English |
| Published: |
Universitat Politècnica de València
2025-06-01
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| Series: | Journal of Applied Research in Technology & Engineering |
| Subjects: | |
| Online Access: | https://polipapers.upv.es/index.php/JARTE/article/view/22952 |
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| Summary: | This study explores the implementation of Condition-Based Maintenance (CBM) integrated with Failure Mode and Effects Analysis (FMEA) on the Auto Insert Connectors FFC machine, a critical asset in the assembly process of Flexible Flat Cable (FFC) connectors within the electronic components manufacturing industry. The machine plays an essential role in ensuring precision and consistency during the insertion of connector materials, making its reliability a key factor in overall production efficiency. The primary objective of this research is to optimize the maintenance process by transitioning from a preventive maintenance approach to a condition-based strategy utilizing real-time sensors and monitoring systems. FMEA was employed to identify critical failure modes and calculate Risk Priority Numbers (RPNs) for key machine components, which guided the strategic installation of sensors for continuous performance monitoring. Compared to conventional preventive maintenance methods, the implementation of CBM resulted in a 69.75% reduction in inspection time, indicating a substantial improvement in maintenance efficiency. The findings conclude that integrating CBM with real-time data and FMEA significantly enhances operational productivity and minimizes machine downtime. This approach demonstrates strong potential for broader application across various high-precision industries, particularly electronics, automotive, and mining, where equipment reliability is essential to maintaining competitiveness. |
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| ISSN: | 2695-8821 |