That's a fascinating question about the future of industrial automation! By 2030, I imagine a truly 'self-healing' system would be like having an intelligent factory that can diagnose and fix itself before problems even occur. Picture this: machines with network-connected sensors constantly monitoring their own health, AI algorithms predicting failures weeks in advance, and systems that automatically recalibrate or reroute production when issues are detected - all without human intervention.

The technologies you mentioned are exactly what's building toward this future. Edge computing allows real-time data processing right at the machine level, enabling instant responses to anomalies. Digital twins create virtual replicas of physical systems where you can simulate failures and test solutions before implementing them in the real world. And modular PLCs (Programmable Logic Controllers) are becoming more intelligent, with AI integration that lets them make autonomous decisions about maintenance and optimization.

What's really exciting is how these technologies are converging. Edge computing handles the immediate, time-sensitive decisions, while cloud platforms analyze broader patterns. Digital twins provide the testing ground for self-healing strategies, and modular PLCs serve as the intelligent nodes that execute those strategies. By 2030, we'll likely see factories where predictive maintenance becomes truly autonomous - systems that not only detect problems but also implement fixes, reallocate resources, and optimize operations in real-time, dramatically reducing downtime and maintenance costs.