How do experienced automation engineers approach the 'PLC vs. PAC vs. Industrial PC' debate when designing a new line that needs to handle both traditional ladder logic and emerging AI/ML inference at the edge?

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Hey there! That&#39;s a fantastic question that really gets to the heart of modern industrial automation challenges. Experienced engineers typically approach this as a layered architecture decision rather than an either/or choice. Here&#39;s how they think about it:First, they start with the core control requirements. For traditional ladder logic and deterministic control loops that need millisecond-level precision, PLCs are still the go-to choice. They&#39;re rock-solid reliable for safety-critical functions.Then they consider where PACs fit in - these are great for more complex, distributed systems that need advanced programming capabilities (like C/C++) and can handle larger data processing tasks. PACs bridge the gap between simple PLCs and full computers.For AI/ML inference at the edge, that&#39;s where Industrial PCs really shine. Experienced engineers often create hybrid architectures where PLCs handle the real-time control, while Industrial PCs run the AI models alongside them. This way, you get the best of both worlds: deterministic control from the PLC and advanced analytics from the Industrial PC.The key insight is that it&#39;s not about picking one over the others, but about designing a system where each component does what it does best. The PLC ensures safety and reliability, the PAC handles complex logic and data aggregation, and the Industrial PC provides the computational power for AI inference - all working together seamlessly.

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How do experienced automation engineers approach the 'PLC vs. PAC vs. Industrial PC' debate when designing a new line that needs to handle both traditional ladder logic and emerging AI/ML inference at the edge?

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