Abstract
The printing industry faces efficiency challenges due to long setup times, unplanned downtime, and a lack of standardized parameters, resulting in low Overall Equipment Effectiveness (OEE). This study proposes an integrated improvement model that combines the pillars of Total Productive Maintenance (TPM) - specifically autonomous and planned maintenance - with the Single-Minute Exchange of Die (SMED) methodology and Industry 4.0 tools (IoT sensors, OPC-UA protocol, and predictive analytics), applied to a label printing company. The model was evaluated through discrete-event simulation using Rockwell Arena software. The simulation results show a 45% reduction in setup times, a 30% decrease in unplanned downtime, and an OEE improvement from 66.85% to 82% (16 percentage points), with a projected return on investment (ROI) within eight months. The proposed framework provides a replicable approach for small and medium-sized enterprises (SMEs) in the graphic sector, enabling improved machine availability and competitiveness through Lean-Industry 4.0 integration.
| Original language | English |
|---|---|
| Pages (from-to) | 315-319 |
| Number of pages | 5 |
| Journal | Proceedings of the International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT |
| Issue number | 2026 |
| DOIs | |
| State | Published - 2026 |
| Event | 17th International Conference on Mechanical and Intelligent Manufacturing Technologies, ICMIMT 2026 - Cape Town, South Africa Duration: 13 May 2026 → 15 May 2026 |
Keywords
- Digital transformation
- Lean 4.0
- OEE
- Predictive maintenance
- SMED 4.0
- Smart manufacturing
- TPM
- printing industry
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