Some time ago, I gave a talk at a Control Engineering event titled “The PLC Is No Longer What It Used to Be”, and later published a related article on LinkedIn. To my surprise, despite today’s fragmented digital landscape, the article drew over 5,800 views and generated thoughtful responses from automation professionals around the world.
But frankly, the real message behind this piece is not about whether the PLC of today is still the same PLC — it’s about how automation engineers are no longer the same engineers they once were.
Even if the PLC has evolved from a simple logic controller into intelligent controllers, AI‑enhanced controllers, cloud PLCs, and virtual PLCs, none of these new forms truly convey the real core value of automation — the “engineering” and the remarkable work of engineers themselves.
A humble PLC—a product or technology in itself—falls short compared to today’s smartphones. After all, phones are wrapped in high‑impact concepts: 4G/5G connectivity, streaming, cameras, video editing. They’ve replaced CD players, tape decks, landlines, even TVs. Countless apps enrich our lives. In comparison, the PLC—plain and functional—even with AI or cloud capabilities, has not seen mass consumer adoption.
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| A typical PLC in a control cabinet drives machine efficiency |
Yet, those smartphones and devices—computers, mobile networks—that we rely on cannot be manufactured without PLCs. PLCs orchestrate diverse tasks: machine logic, loop regulation, motion control, vision system integration, CNC and robotics, network communication, and system management. Hidden within the harsh environments of manufacturing equipment, PLCs precisely control servo drives and motors, manage data flows from the shop floor to ERP/MES systems, and quietly permeate every corner of industry.
This is the PLC: unassuming, yet a silent powerhouse underpinning our complex world — fueled and driven by the extraordinary work of automation professionals.
Every machine has a soul
Machines are the essential assets of manufacturing and the engines of product creation. Our standard of living improves thanks to factory-deployed machinery. Early machines with PLCs controlling binary logic and variable-frequency drives already massively outpaced manual systems. Today’s machines are far more sophisticated: handling various materials, precision, speed, and flexibility. On physical processing equipment, efficiency relies on integrated process control and motion regulation.
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| Beverage and liquid filling system with PLC control |
If a PLC was only for logic, it couldn’t handle complex process variations. Rather, it must respond to physical material behavior in processes like injection molding, extrusion, die-casting, coating/printing, composite layering, machining (turning, milling, drilling), metal forming (spring coiling, stamping), battery tab pressing, semiconductor deposition, liquid filling, powder compaction, and more.
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| Injection molding workflow |
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| High‑speed printer control (registration, tension, color alignment) |
Each product is shaped via machines to account for material physics and run software—the industrial know‑how—that resembles modular “apps.” This software far transcends basic PLC logic. As machines age, their complexity grows, requiring engineers to be proficient in mechatronics, process algorithms, signal processing, communications, and HMI design. An engineer’s domain is no longer limited to basic logic control.
A colleague once said, “Every machine has its soul.” That soul is the embedded know‑how that enables machines to adapt and manufacture high-quality products at low cost. And as these complexities rise, the value of electrical/mechatronics engineers has likewise risen.
Engineering is innovation
Many see “innovation” as only a 0→1 leap—like digital cameras upending film or smartphones replacing feature phones. However, engineering is inherently creative. Science discovers; engineering innovates via applied technology. The bridge between science and tech is engineering.
Solving complex industrial problems means breaking them down under constraints to find new combinations—this is the engineer’s role.
In discrete manufacturing, everything boils down to physical formation—manipulating materials through temperature, pressure, stress, electromagnetic fields. Controlling these processes ensures stable, functional characteristics: ink flow on pen tips, liquid behavior in fills, molecular absorption in fabrics, stress relief in metals or concrete, and elasticity springback. This is engineering in a convergence process.
Academic PLC work often feels undervalued unless jazzed up with terms like “intelligent,” “neural networks,” or “multimodal.” But genuine technical value is in understanding and modeling the core control algorithms—and that requires engineers.
PLC logic is just the baseline—real PLC work combines algorithm development, process adaptation, and hardware-software fusion. Over the past two decades PLCs have evolved to integrate tightly with field systems — solving real-world engineering challenges.
In the 1990s, drive for open automation—led by companies like Beckhoff—pushed PLCs onto mainstream hardware (e.g., Intel, ARM) with open programming languages (C/C++). The goal: users customizing and extending systems instead of relying on proprietary black boxes. Today, open automation stretches into digital integration, AI, robots, and vision systems—CNC and robots can now be controlled with PLC architectures, replacing expensive, specialized controllers.
Innovation through integration
Automation innovation comes from blending user needs and horizontal technologies: bringing new tech into hardware and software platforms to help users build adaptive machines efficiently. Engineering isn’t about using the trickiest tech—it’s about applying the most economical tech under constraints.
Engineering converges; science diverges. Engineers seek optimal solutions in cost, materials, speed, labor, footprint—the path never ends.
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| Engineering is interdisciplinary innovation |
Innovation is not just technical prowess—it’s commercial success. Engineering must solve real-world problems now and drive value. Without that, great tech means little.
PLC’s digital evolution
PLCs are becoming more digital: bridging IT and OT. On one side, IT extends into manufacturing; on the other, OT reaches upward. PLCs integrate with PC platforms, cloud services, and AI capabilities based on site demands. This isn’t theoretical—the trajectory of PLC development is driven by what manufacturers need.
So debates about controller types miss the point: the real question is whether they economically solve user problems.
Control (cyclic, signal-based tasks) and computing (data-based tasks) are different. PLC+PC hybrids handle both: PLC for I/O, PID loops, motion; PC for path planning, optimization, analytics, scheduling, OEE, vision inspection, defect detection. Machines are data assets; efficiency, quality, traceability all rely on PLC-collected data.
PLCs evolve to meet demands in quality, cost, delivery—driven by industry transformation and the evolution of engineers themselves.
Automation engineers have transformed too
Let’s talk about the engineers behind the technology.
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PLC = logic? Then it undervalues engineers. If a PLC only did logic, you wouldn’t need an engineer—just a technician. In Western countries, PLC programming once belonged in vocational training; electrical/electronic engineers with a bachelor’s degree focus on broader system development.
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Engineer = coder? No. If engineers merely write code, you’ve oversimplified. Some think generative AI will replace engineers—but AI only assists in coding. Engineering is full-lifecycle: concept, requirements, architecture, coding, testing, scaling, ongoing optimization. It’s iterative. Unknowns—from mechanical or material interactions—require on-site investigation and problem-solving.
Good engineers design for usability, readability, maintainability, and error handling. Complex machines—like ASML’s lithography tool—require continuous iteration over years.
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Full-stack engineers? Rare. That term comes from IT. Early on, one engineer might user design HMI, logic, networks. Today, automation systems include robots (automation engineers, robotics), vision systems (vision specialists), flexible conveyors (mechatronics), HMI/UX designers, AI/data scientists, database and network experts. Effective automation requires cross-disciplinary collaboration.
A modern automation engineer—whether system integrator, FAE, or factory engineer—is part of a multidisciplinary team.
Key competencies today:
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Cross‑disciplinary coordination: You can’t master every domain, but you must understand enough to communicate and coordinate—e.g., knowing AI capabilities, even if not designing neural nets. Complex problems combine mechanical, electrical, process dimensions.
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Engineering mindset & efficiency: Projects involve tight constraints—time, budget, material. Testing is costly. Use simulation, parallel development, structured project management. Design is a conscious creative act, balancing unknowns using scientific thinking and hypothesis testing.
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Leadership: Western engineering programs emphasize leadership—engineers must collaborate across specialties, often lead development teams or later product lines. Many industrial founders are engineers. Leadership is critical—understanding, motivating, coordinating technical experts.
In conclusion
As engineers creating automation equipment, I see clearly that engineering work and engineers themselves are where the real value lies—that’s why when I wrote “PLC Is No Longer That Old PLC,” what moved me most was not the device, but the exemplary work of engineers.