Abstract
This paper explores the challenges of applying digitalization in regulated pharmaceutical manufacturing environments. A large range of complex equipment including pumps, valves and vessels may be associated with pharmaceutical batch production processes. Maintenance of such equipment are often based on reactive or preventative strategies which are not always effective and not completely successful in preventing costly downtime or scrap. This research examines how predictive maintenance Key Performance Indicators (KPIs) can be developed through data capture using non-intrusive sensors and their integration with production data derived from Programmable Logic Controllers (PLCs), Enterprise Resource Planning (ERP) systems, and Product Lifecycle Management (PLM) systems. The significance of regulation and the associated challenges in applying digitalization within such a highly regulated environment are also considered. This research aims to shed light on the potential benefits and challenges of implementing digital solutions for predictive maintenance in regulated manufacturing environments to contribute to the enhancement of operational efficiency and product quality while reducing costs due to outages.
Original language | English |
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Pages (from-to) | 222-227 |
Number of pages | 6 |
Journal | IFAC-PapersOnLine |
Volume | 58 |
Issue number | 8 |
DOIs | |
Publication status | Published - 1 Jun 2024 |
Event | 6th IFAC Workshop on Advanced Maintenance Engineering, Services and Technology, AMEST 2024 - Cagliari, Italy Duration: 12 Jun 2024 → 14 Jun 2024 |
Keywords
- acoustic emission
- condition monitoring
- Digitalization of manufacturing
- dry gas seals
- machine learning
- regulated environments