A non-intrusive Industry 4.0 retrofitting approach for collaborative maintenance in traditional manufacturing

Area of Science:

• Industrial Engineering
• Manufacturing Technology
• Digital Transformation

Background:

• COVID-19 highlighted the need for manufacturing adaptability and asset monitoring.
• Small and Medium-sized Enterprises (SMEs) struggle with Industry 4.0 adoption and advanced maintenance strategies.
• Technical and economic barriers impede digital technology integration in traditional manufacturing.

Purpose of the Study:

• To present a human-machine technological integration solution for traditional manufacturing.
• To enable non-intrusive retrofitting with interoperable Industry 4.0 tools for legacy systems.
• To evaluate physical-digital convergence for older industrial systems using a common, deployable architecture.

Main Methods:

• Developed a non-intrusive retrofitting solution with interoperable Industry 4.0 tools.
• Implemented a hardware and software architecture for HMI-based legacy maintenance.
• Applied digital process and condition-based maintenance (CBM) techniques on CNC and injection molding machines during COVID-19.
• Monitored real-time machine patterns, integrating operational knowledge from experienced staff.

Main Results:

• Successfully deployed digital retrofitting and communication strategies without disrupting operations.
• Enabled real-time monitoring of machine patterns, enhancing condition-based maintenance (CBM).
• Facilitated collaborative updates for workers and industrial systems with augmented digital strategies.

Conclusions:

• The human-machine technological integration solution effectively addresses challenges in traditional manufacturing.
• Proactive CBM environments and augmented digital strategies improve the physical-digital convergence of older industrial systems.
• The approach supports industrial production continuity and workforce skills development in SMEs.