The main content of this article is as follows:
· Overview of PLC Technology: Introduces the basic concepts, development history, and core position of PLC in industrial automation, using tables to compare the technical characteristics of PLCs from different periods.
· Core Applications of PLC in Industrial Intelligence: A detailed analysis of PLC applications in smart manufacturing, intelligent warehousing and logistics, smart energy, and municipal sectors, including practical cases and data support.
· Innovative Development Trends of PLC Technology: Discusses innovative directions such as software-defined automation, AI integration, and communication technology upgrades, using tables to compare the characteristics of different communication protocols.
· Assessment of PLC Technology’s Position in Industrial Intelligence: Evaluates the core position of PLC from dimensions such as reliability, flexibility, and integration, analyzing its synergy with emerging technologies.
· Challenges and Countermeasures Facing PLC Technology Development: Summarizes challenges such as technical bottlenecks, talent shortages, and security risks, proposing corresponding solutions.
· Future Outlook: Predicts the architectural evolution of PLC technology, deep integration with AI, and trends in professional talent cultivation.
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1 Introduction: Overview of PLC Technology and Its Context in Industrial Intelligence
Industrial intelligence, as the core concept of the Fourth Industrial Revolution, is profoundly reshaping the landscape and development direction of global manufacturing. In this wave of transformation, the Programmable Logic Controller (PLC) serves as the cornerstone of industrial automation control, continuously playing an irreplaceable key role. Since its inception in 1968, PLC technology has become the most widely used control device in the field of industrial control due to its outstanding reliability, strong anti-interference capability, and flexible programmability. With the deepening of concepts such as Industry 4.0 and smart manufacturing, PLC technology is accelerating its integration with emerging technologies such as artificial intelligence, the Internet of Things, and cloud computing, continuously expanding its application boundaries and functional scope.
Industrial intelligence emphasizes not only the automation of production processes but also the pursuit of intelligent, information-driven, and flexible manufacturing systems. In this context, the role of PLC is undergoing a profound transformation from a mere “control executor” to an “intelligent decision-maker.” Modern PLC systems are no longer simple logic control devices but have evolved into comprehensive automation platforms with data acquisition, computational analysis, communication interconnectivity, and intelligent decision-making capabilities. According to IDC research, by 2026, PLCs with AI capabilities will occupy 35% of the market share, clearly indicating the trend of PLC technology moving towards intelligence.
This article will deeply analyze the current application status, innovative trends, and core position of PLC technology in industrial intelligence from multiple dimensions. First, it will systematically analyze the specific application practices of PLC in diverse scenarios such as smart manufacturing, intelligent warehousing, and energy management; second, it will explore the innovative paths and development trends of PLC technology in conjunction with emerging technologies; third, it will comprehensively assess the strategic value and irreplaceability of PLC in the industrial intelligence system; finally, it will propose countermeasures for the current technical challenges and look forward to the future development direction of PLC technology. Through this comprehensive and in-depth analysis, it aims to provide valuable references for practitioners, researchers, and corporate decision-makers in the field of industrial automation, jointly promoting the accelerated development of industrial intelligence.
2 Overview of PLC Technology: From Basics to Advanced
The Programmable Logic Controller (PLC) is a digital operation system specifically designed for industrial environments. It uses programmable memory to store instructions for executing logical operations, sequential control, timing, counting, and arithmetic operations, and controls various mechanical devices and production processes through digital or analog input/output. The basic structure of a PLC includes core components such as the Central Processing Unit (CPU), memory, input/output interfaces (I/O), power supply module, and communication module.
2.1 Development History of PLC Technology
Since its inception, PLC technology has undergone an evolution from simple to complex, from specialized to general-purpose. The first generation of PLCs in the 1970s primarily functioned to achieve simple logical operations and sequential control, using ladder diagram language to replace traditional relay control cabinets. The second generation of PLCs in the 1980s added numerical operations, data transmission, and analog control functions, beginning to integrate with computer technology. The third generation of PLCs in the 1990s saw significant improvements in processing speed, storage capacity, and communication capabilities, forming a complete network communication protocol. Entering the 21st century, PLC technology has further developed towards high performance, networking, and intelligence, integrating more powerful communication interfaces, open system architectures, and intelligent control algorithms.
Table: Comparison of Main Characteristics of PLC Technology Development Stages
Development Stage Main Technical Characteristics Typical Applications Representative Products
First Generation (1970s) Logic control, ladder diagram, replacing relays Automotive assembly lines, material handling Modicon 084
Second Generation (1980s) Numerical operations, analog control, basic communication Process industries, machine tool control Siemens S5 series
Third Generation (1990s) High-speed processing, network communication, multifunctional modules Flexible manufacturing systems, packaging machinery Allen-Bradley PLC-5
Fourth Generation (2000s to Present) Integration, networking, intelligence, openness Fully integrated automation, smart factories Siemens TIA Portal
2.2 Core Advantages of PLC in Industrial Automation
PLC technology maintains its dominant position in the field of industrial automation due to its multiple core advantages:
· Outstanding Reliability: PLCs are designed for industrial-grade performance, capable of stable operation in harsh industrial environments, with an average time between failures (MTBF) exceeding 100,000 hours, strong resistance to vibration and electromagnetic interference, making them suitable for harsh workshop conditions.
· High Flexibility: Control logic can be changed through software programming without the need for rewiring or hardware replacement, allowing for quick adaptation to changes in production processes. Compared to microcontroller control, PLCs do not require specialized personnel to write low-level code, making modifications easier.
· Powerful Functionality: Modern PLCs integrate diverse functions such as logic control, process control, motion control, data acquisition, and communication networking, enabling complex control tasks without additional equipment.
· Convenient Maintainability: PLCs have comprehensive self-diagnostic functions that can quickly locate fault points, significantly reducing system downtime. In contrast, traditional relay control requires checking connections one by one, which is time-consuming and labor-intensive.
· Open Communication Capability: Modern PLCs support various industrial communication protocols, such as PROFINET, EtherNet/IP, and Modbus-TCP, allowing easy integration into industrial IoT systems for data exchange between devices.
3 Core Application Analysis of PLC in Industrial Intelligence
3.1 PLC Applications in Smart Manufacturing
Within the framework of smart manufacturing, PLCs serve as the core controllers of intelligent production lines, achieving real-time precise control over production processes. For example, in automotive manufacturing, PLCs control motors, sensors, and robotic arms on automated assembly lines to ensure the precise handling, positioning, and assembly of automotive components. Sensors at each production station monitor the position and orientation of components in real-time and transmit the data to the PLC. The PLC quickly analyzes and processes this data based on preset programs and logic, adjusting the actions of actuators in a timely manner to ensure that each component is accurately installed in the designated position, thereby ensuring product quality consistency and stability.
3.1.1 Achieving Flexible Manufacturing
As market demand diversifies, the manufacturing industry increasingly requires flexibility in production lines. The flexibility and programmability of PLC technology make it one of the key technologies for achieving flexible production. In intelligent production lines, PLCs can easily implement mixed-line production of different product models. When production tasks change, only the corresponding control programs and process parameters need to be modified in the PLC, allowing for quick adjustments to the production line’s operating mode and reconfiguration of production equipment and process flows.
The electronics manufacturing sector provides a typical case of flexible manufacturing using PLCs. When a production line needs to manufacture various models of smartphones or tablets, PLC technology allows the production line to automatically adjust production parameters at each station, such as soldering temperature, placement speed, and assembly force, based on product order information, enabling rapid switching between different products to meet market demands for personalized and customized products, thereby improving the company’s responsiveness to market changes. Actual measurements indicate that production lines controlled by intelligent PLCs can reduce product switching time by over 40%, significantly enhancing equipment utilization and production flexibility.
3.1.2 Quality Control in Smart Manufacturing
PLCs also play the role of quality guardians in smart manufacturing. In the food packaging industry, PLCs control filling machines, capping machines, and labeling machines to ensure the accuracy and consistency of product packaging. By detecting the speed of the conveyor belt with encoders, PLCs adjust the action frequency of equipment at each station based on speed signals, ensuring that “the next process starts immediately after the previous one is completed,” maintaining production synchronization and stability. When a station experiences material jams or other anomalies, the PLC can immediately stop upstream equipment while allowing downstream equipment to continue running until the material is cleared, avoiding batch scrapping and minimizing losses.
3.2 PLC Applications in Intelligent Warehousing and Logistics Systems
Intelligent warehousing systems are an important component of the smart manufacturing industry, with PLCs playing a central control role, enabling the coordinated operation of automated equipment and robots. In modern intelligent warehouses, PLCs control the operation of Automated Guided Vehicles (AGVs), automated conveyor belts, and stackers.
3.2.1 Coordinated Control of Warehousing Equipment
When goods need to be stored, PLCs receive instructions from the Warehouse Management System (WMS) and control AGVs to transport goods from the inbound area to designated shelf locations, while stackers accurately store goods on shelves according to PLC instructions. During outbound operations, PLCs similarly coordinate the actions of various devices to ensure that goods can be quickly and accurately retrieved and transported to the shipping area. Additionally, PLCs can collaborate with robots in the warehouse, controlling robotic arms to complete tasks such as picking and packaging. Through unified control by PLCs, various devices in intelligent warehousing systems can work efficiently together, achieving automated storage, handling, and distribution of goods, thereby improving warehouse space utilization and logistics operation efficiency.
3.2.2 Data Interaction and Optimization in Warehousing
PLCs not only enable real-time control of intelligent warehousing equipment but also engage in close data interaction with the Warehouse Management System (WMS), providing strong support for optimizing warehousing logistics. PLCs collect real-time operational status data from equipment in the warehouse, such as AGV locations and operating speeds, and the working status of stackers, transmitting this data to the WMS. The WMS uses this real-time data to reasonably schedule and optimize warehousing logistics operations, such as planning AGV travel paths to avoid collisions and improve operational efficiency; optimizing the storage layout of goods based on their inbound and outbound frequency and inventory status to reduce handling distances.
At the same time, the WMS sends order information and inventory management strategies to the PLC, which controls the equipment to perform corresponding operations based on these instructions. Through data interaction and collaborative work between PLCs and WMS, intelligent warehousing systems can achieve efficient inventory management and precise order processing, reducing logistics costs and enhancing the level of supply chain management for enterprises. Practical applications indicate that PLC-based intelligent warehousing systems can improve logistics efficiency by over 13%, while significantly reducing labor and operational costs.
3.3 PLC Applications in Smart Energy and Municipal Systems
In the fields of energy management and municipal infrastructure, PLC technology acts as a guardian of stable operation, ensuring the reliable functioning of critical facilities. In substation automation systems, PLCs automatically switch capacitor banks to adjust power factors based on grid voltage and current signals, and can cut off circuit breakers within 0.1 seconds when detecting short circuit faults to prevent accidents from escalating.
3.3.1 Smart Energy Management
Water treatment plants are a typical scenario for PLC applications in the municipal sector. PLCs control the operation time of various equipment in the sequence of “grit removal → sedimentation → aeration → sedimentation → disinfection,” automatically adjusting the aeration intensity of aeration tanks based on changes in water quality to stabilize the effluent compliance rate. By uploading operational data to the dispatch center through communication modules, remote monitoring and operation are achieved, reducing the need for on-site personnel and achieving unattended operation.
The intelligent control system for air compressors at Yangcun Coal Mine showcases the innovative application of PLCs in the energy sector. This system uses a network of sensors distributed throughout the units to continuously “sense” the “heartbeat” and “pulse” of each air compressor—current, voltage, power signals, temperature, and pressure signals—and uploads this data to the logic control center, enabling various protection, alarm, and monitoring functions for the air compressors. Based on this real-time data, the PLC system can automatically and smoothly schedule the operation of equipment in the fleet according to the peak and valley changes in underground gas demand, ensuring that the total pressure remains stable within the optimal range, completely eliminating the reliance on “experience and manual operation” and achieving stable and efficient gas supply quality.
3.3.2 Predictive Maintenance of Energy Systems
In terms of maintenance for energy equipment, PLC systems establish a scientific predictive maintenance management system. Acting as the “equipment steward,” they continuously record the cumulative operating time, load cycles, and key parameter history of each device. Through big data analysis, they can accurately predict the performance degradation trends of equipment, proactively prompting maintenance before components reach their lifespan limits, achieving “preventive maintenance” and significantly avoiding unplanned downtime, effectively extending the overall service life of the equipment. This PLC-based intelligent maintenance system has improved the fault warning accuracy of energy equipment by 40%, saving enterprises hundreds of thousands of yuan in maintenance costs annually.
3.4 PLC Applications in Intelligent Transportation and Building Systems
Traffic control systems represent another important area for PLC applications. In intelligent transportation systems, PLCs control traffic lights, railway signaling systems, and airport baggage handling systems, ensuring smooth and safe transportation operations. For instance, in modern airport baggage handling systems, PLCs coordinate numerous conveyor belts, sorting machines, and identification devices to ensure that passenger luggage is efficiently and accurately transported from check-in counters to corresponding flight loading areas, significantly improving the efficiency and accuracy of baggage handling.
In the intelligent building sector, PLC technology is widely used in building automation systems to achieve centralized control over air conditioning, lighting, elevators, and security systems. Through unified control by PLCs, various devices within buildings can automatically adjust based on environmental changes and usage demands, improving energy utilization efficiency and creating a comfortable and safe living and working environment. Particularly in elevator control systems, the logic control and fault diagnosis functions of PLCs are crucial; by monitoring parameters such as motor current and contactor status in real-time, they can immediately stop operation and display fault codes when issues like “phase loss” or “contactor sticking” are detected, guiding maintenance personnel to quickly resolve problems.
4 Innovative Development Trends of PLC Technology
4.1 Software-Defined Automation and Cloud PLCs
Software-defined automation is an important development trend in current industrial control systems, centered on using virtual controllers (such as containers and virtual machines) running on general-purpose computing devices (like industrial PCs and servers) to replace traditional hardware controllers, constructing control systems. This new control system architecture is more flexible, cost-effective, and eliminates the strong binding of hardware and software suppliers, making upgrades and maintenance simpler.
The “Smart PLC” released by Jiangsu Telecom is a typical representative of this trend, and it is also the first practice case of softPLC dual-machine backup in industrial production nationwide. This solution, with core advantages of “lightweight, high adaptability, low cost, and strong security,” breaks the limitations of traditional PLC devices’ closed and fragmented nature. By implementing self-developed gateways for master-slave switching and combining Tianyi Cloud with 5G networks, it migrates control functions to the cloud, significantly reducing hardware procurement and wiring costs, simplifying system architecture, and enhancing production line flexibility.
The cloud-based data acquisition and control management platform is a key support for the cloud application of PLCs. This platform addresses the transformation barriers of “non-unified protocols and difficult management adaptation” for industrial devices, being compatible with 256 mainstream industrial protocols and over 40 domestic and international mainstream PLC brands, supporting full-link management from data acquisition to southbound cloud control and business orchestration. This cloud platform has achieved a full chain connection of “pasture-logistics-production-sales” at Weigang Dairy, improving logistics efficiency by 13%, reducing operating costs by 12%, and cutting down 117 personnel, effectively promoting the substantial implementation of “integration of primary, secondary, and tertiary industries.”
4.2 Deep Integration of AI and PLC
The deep integration of artificial intelligence technology with PLCs is driving the shift of industrial control from rule-driven to data-intelligent driven. The application of AI technology in PLC systems mainly manifests in three aspects: dynamic control optimization, predictive maintenance, and programming paradigm innovation.
4.2.1 Dynamic Control Optimization
In dynamic control optimization, traditional PID regulation has significant limitations under complex working conditions, while AI algorithms based on deep reinforcement learning (DRL) can complete control parameter optimization within a 1ms cycle. Siemens’ application case in steel continuous casting production lines shows that AI dynamically adjusts the vibration frequency of the crystallizer, reducing slab cracking rates by 18%. ABB uses AI to coordinate the tension control of 240 servo motors in paper machines, reducing paper break incidents by 27%. In terms of implementation results, traditional methods require 200 hours for parameter tuning, while AI solutions compress this time to 8 hours and can continuously optimize.
4.2.2 Predictive Maintenance
Predictive maintenance is an important area where AI empowers PLCs. Early warning systems based on multi-modal data such as vibration and current have become a competitive focus for the intelligentization of industrial equipment. Schneider Electric’s innovative solution integrates the SoundSight acoustic analysis model into the Modicon M580 PLC, accurately identifying early bearing wear (F1-score 0.93). Siemens collaborates with Senseye to develop an AI fault library, achieving average 72-hour fault prediction on semiconductor equipment. AI platforms like DeepSeek utilize few-shot learning technology, requiring only 500 data sets to build diagnostic models, reducing data requirements by 80% compared to traditional methods, significantly lowering implementation barriers.
4.2.3 Programming Paradigm Innovation
Faced with a global shortage of 300,000 PLC programmers, AI is changing traditional programming methods. ABB Ability™ Genix can convert natural language instructions into ST code, shortening the development cycle of tank control systems by 45%. Siemens’ TIA Portal AI Assistant automatically detects over 70% of logical conflicts through program semantic analysis. The DeepSeek platform supports mixed generation of ladder diagrams and function blocks, achieving 100% functional coverage in packaging machinery testing, significantly reducing programming difficulty and development costs.
4.3 Communication Technology Upgrades and Integrated Development Environments
The demand for real-time communication and data exchange in modern industrial control is increasing, and the communication capabilities of PLCs are continuously upgrading. Traditional field buses centered on OT, such as DeviceNet, are gradually being replaced by industrial Ethernet and even wireless Ethernet. Ethernet-APL (Advanced Physical Layer) technology is changing the process automation field by achieving high bandwidth and seamless Ethernet connections with field devices, addressing challenges that have historically limited the use of Ethernet in the field, including power, bandwidth, wiring, distance, and use in hazardous locations.
Table: Comparison of Characteristics of Mainstream Industrial Communication Protocols
Communication Protocol Technical Characteristics Main Application Areas Transmission Rate Topology
PROFINET Real-time Ethernet, supports cyclic transmission Factory automation, motion control 100Mbps-1Gbps Star, line, ring
EtherNet/IP Based on standard Ethernet, CIP protocol Discrete manufacturing, process control 100Mbps-1Gbps Star, tree
EtherCAT Real-time Ethernet, master-slave structure High-speed motion control, synchronous control 100Mbps Line, star
Modbus-TCP Simple, open, low cost Device-level communication, SCADA systems 10/100Mbps Star
OPC UA Platform-independent, information model IT/OT integration, vertical data exchange Depends on underlying network Client/server
Fully integrated development environments are another important development trend, integrating programming, development, configuration, and debugging functions related to automation, such as PLCs, Human-Machine Interfaces (HMIs), drive devices, and communication networks, into a unified development platform. Users can complete cross-device programming, configuration, and debugging within the same development environment, enhancing convenience, achieving more centralized and efficient data management, and accelerating simulation debugging.
The CODESYS integrated development environment (IDE) provides a consistent approach to creating code using standard languages for cross-platform deployment on industrial controllers. However, these efforts have not fully addressed modern programmers’ preference for more contemporary IT-based languages (such as C++ or Python). It is noteworthy that despite these trends towards open and modern programming languages, classic ladder logic will continue to exist in the foreseeable future, as it has a large application base and remains the preferred simple coding method for many electricians, technicians, and even developers.
5 Assessment of PLC Technology’s Position in Industrial Intelligence
5.1 An Indispensable Core Foundation of Industrial Automation
In the industrial intelligence system, PLCs maintain an irreplaceable foundational position. Even in the face of competition from emerging technologies such as edge controllers and industrial PCs, PLCs continue to dominate the industrial control field due to their unique advantages. IDC research indicates that PLCs, as the “invisible cornerstone” of industrial automation, will not disappear in the foreseeable future but will continue to develop as a foundational automation platform through continuously improving technology and meeting user needs.
The irreplaceability of PLCs primarily stems from their outstanding performance in real-time deterministic control. Even in challenging operational environments, PLCs can implement deterministic control and reliable monitoring of physical devices on-site, achieved through dedicated processors, operating systems, and programming environments built into the platform. For industrial applications requiring high reliability, rapid response, and precise timing control, the millisecond or even microsecond deterministic response provided by PLCs is difficult to replace with general computing platforms.
Secondly, the industrial-grade reliability of PLCs is a crucial guarantee of their lasting value. Industrial environments are often accompanied by harsh conditions such as vibration, dust, electromagnetic interference, and temperature fluctuations, and the industrial-grade design of PLCs enables them to operate stably in such environments, with an average MTBF exceeding 100,000 hours. This reliability is vital for continuous production processes and safety-critical applications, which many IT technologies or commercial computing devices cannot match.
Furthermore, PLCs have a deep accumulation in technology inheritance and talent reserves. After decades of development, PLCs have established comprehensive technical standards, programming specifications, and application ecosystems, with millions of engineers worldwide familiar with PLC programming and maintenance. This technical inheritance and talent reserve make PLCs’ position in the field of industrial automation difficult to shake, forming a strong ecosystem barrier.
5.2 Edge Intelligent Nodes in the Industrial Internet System
In the industrial internet architecture, PLCs are evolving from standalone control devices to edge computing nodes, playing a key bridging role in the integration of IT and OT. Modern PLCs have data storage, analysis, and networking capabilities, allowing them to store collected device status data locally or in cloud servers, generating simple reports; through Ethernet, PROFINET, Modbus, and other communication protocols, they interact with HMI (Human-Machine Interface), SCADA systems, and industrial IoT platforms.
The edge intelligent role of PLCs in the industrial internet is mainly reflected in three aspects:
· Data Collection and Preprocessing: PLCs directly connect to on-site sensors and actuators, collecting operational data in real-time and capable of local data filtering, compression, and preliminary analysis, reducing the burden on upper-level systems. For example, in the intelligent control system for air compressors at Yangcun Coal Mine, PLCs use a network of sensors distributed throughout the units to continuously “sense” the current, voltage, power signals, temperature, and pressure signals of each air compressor, providing a data foundation for intelligent control.
· Edge Analysis and Decision-Making: With enhanced processing capabilities, modern PLCs can run lightweight AI algorithms, achieving real-time intelligent decision-making at the edge. Siemens’ S7-1500 series integrates AI Core modules, supporting TensorFlow Lite model deployment; Schneider’s Modicon M262 PLC can implement real-time inference of energy consumption prediction models, achieving a 12% energy saving in automotive factories. This edge intelligence capability allows control systems to respond quickly to on-site changes, reducing dependence on the cloud.
· Vertical Data Integration: PLCs support vertical integration of OT data into IT systems through IT-friendly protocols such as OPC UA and MQTT. The OPC UA over TSN unified standard allows Schneider PLCs to read ABB robot data, minimizing sampling synchronization errors. This data integration capability provides real-time production data for upper-level management systems such as Manufacturing Execution Systems (MES) and Enterprise Resource Planning (ERP), supporting enterprise-level intelligent decision-making.
5.3 Key Enabling Technology for Flexible Intelligent Manufacturing
The flexibility and programmability of PLCs make them a key enabling technology for achieving flexibility in intelligent manufacturing. In the context of diversified market demand and shortened product life cycles, manufacturing enterprises need flexible manufacturing systems that can quickly respond to production changes, and PLC technology plays an irreplaceable role in this regard.
In intelligent production lines, PLCs can easily implement mixed-line production of different product models. When production tasks change, only the corresponding control programs and process parameters need to be modified in the PLC, allowing for quick adjustments to the production line’s operating mode and reconfiguration of production equipment and process flows. This flexible production capability enables enterprises to meet market demands for personalized and customized products, improving their responsiveness to market changes.
PLCs are also a key foundational technology for achieving digital twins. By mapping the PLC control logic of the physical world to virtual space, a virtual mirror synchronized with the physical production line can be constructed, enabling simulation optimization and predictive maintenance of production processes. Siemens’ digital twin + AI optimization has improved the OEE of BMW’s Shenyang plant’s stamping line to 91.2%, demonstrating the core value of PLCs in digital twin applications.
6 Challenges and Countermeasures Facing PLC Technology Development
6.1 Technical Bottlenecks and Breakthrough Paths
Despite continuous advancements in PLC technology, it still faces various technical challenges during its development, necessitating effective breakthrough paths.
6.1.1 Real-Time Bottlenecks
As industrial applications demand higher control precision and response speed, the real-time performance of PLC systems faces severe challenges. This is particularly true in scenarios involving complex AI algorithm integration, high-speed motion control, and precision process control, where traditional PLC processing capabilities have proven insufficient. To address this bottleneck, the industry is adopting various innovative methods:
· Hardware Acceleration: Rockwell Automation has integrated Xilinx Versal AI cores into ControlLogix 5580, achieving inference delays of <500μs, significantly enhancing real-time performance.
· Model Lightweighting: DeepSeek’s NanoFormer architecture compresses ResNet-18 to 0.3MB, meeting PLC memory limitations, making it possible to run complex AI models on resource-constrained edge devices.
· Time-Sensitive Networking (TSN): Siemens’ SCALANCE XC-200 series switches ensure AI instruction transmission jitter of <1μs, providing communication guarantees for high-precision synchronous control.
6.1.2 System Complexity Challenges
As PLC functionalities continue to enhance, system complexity has also increased exponentially, posing significant challenges for design, programming, and maintenance. Modern PLC systems need to handle multiple tasks such as logic control, motion control, process control, data acquisition, and communication, with system complexity far exceeding traditional PLC design scopes.
To address this challenge, the industry is moving towards fully integrated development environments, consolidating programming, development, configuration, and debugging functions related to automation, such as PLCs, HMIs, drive devices, and communication networks, into a unified development platform. This integrated development environment allows users to complete cross-device programming, configuration, and debugging within the same environment, enhancing convenience and achieving more centralized and efficient data management, accelerating simulation debugging.
6.1.3 Data Barrier Issues
In the context of the industrial internet, data interoperability between different devices and systems has become a key obstacle to intelligent transformation. Due to historical reasons, factories often have various brands and generations of PLC devices, forming data silos. Strategies to break down data barriers include:
· Promotion of Standard Protocols: OPC UA over TSN as a unified standard allows Schneider PLCs to read ABB robot data, minimizing sampling synchronization errors.
· Middleware Development: The DeepSeek toolchain can automatically generate adaptation middleware for protocols such as Profibus and EtherCAT, reducing system integration difficulties.
· Federated Learning Applications: Mitsubishi Electric has established a PLC parameter sharing model among 10 automotive companies, protecting data privacy while improving fault identification rates, providing new ideas for data collaborative innovation.
6.2 Talent Shortages and Innovative Cultivation
The development of industrial intelligence relies on the support of professional talent; however, the PLC field is facing a severe talent shortage. It is estimated that there is a shortage of 300,000 PLC programmers globally, which has become one of the bottlenecks restricting industry development. The reasons for this situation mainly include:
· Rapid Knowledge Structure Updates: The integration of PLC technology with AI, IoT, and other new technologies places higher demands on the knowledge structure of practitioners.
· Insufficient Integration of Industry and Education: There is a disconnect between higher education talent cultivation and actual enterprise needs, resulting in graduates lacking practical skills.
· Decreased Attractiveness of Traditional Programming Methods: The younger generation of programmers is more familiar with modern IT languages and has less interest in traditional ladder diagram programming.
To address the talent shortage issue, innovation is needed at both the higher education and enterprise training levels:
As a key base for professional talent cultivation, higher education institutions need to optimize the curriculum of related majors based on the innovative application needs of PLC technology in smart manufacturing. They can increase course content on the integration of PLC technology with emerging technologies in majors such as automation, electrical engineering and automation, and intelligent manufacturing engineering, offering courses like “Application of PLC and Artificial Intelligence Technology” and “Integration of PLC and IoT Technology,” systematically teaching students the principles, methods, and application cases of combining PLC with AI and IoT technologies. At the same time, emphasis should be placed on practical teaching, increasing the proportion of experimental courses and course design, providing students with opportunities to operate PLC equipment and develop smart manufacturing application projects, cultivating their hands-on abilities and problem-solving skills.
For enterprises, strengthening internal employee training and re-education is key to enhancing employees’ capabilities in mastering PLC innovative application technologies. Enterprises should regularly organize training courses on new PLC technologies and applications, inviting industry experts and technical backbones to train employees, covering the latest developments in the integration of PLC with emerging technologies, practical case analyses, and operational skills. Additionally, employees should be encouraged to participate in external technical seminars, industry exhibitions, and other activities to broaden their technical horizons and understand cutting-edge technologies in the industry. Furthermore, enterprises can establish internal training platforms to provide online learning resources, facilitating employees’ self-study during their spare time.
6.3 Security Risks and Protective Strategies
As PLC systems transition from closed to open and from isolated to interconnected, the security risks they face are becoming increasingly severe. Traditional PLC system designs primarily consider functional safety and reliability, with insufficient attention to network security, posing significant risks in interconnected environments. The security threats faced by PLC systems mainly include:
· Unauthorized Access: Attackers gain control of the system through weak passwords or vulnerabilities.
· Malicious Code Injection: Insertion of malicious code during program downloads or updates.
· Communication Eavesdropping and Tampering: Interception and alteration of communication data between PLCs and other devices.
· Denial of Service Attacks: Flood attacks that exhaust PLC system resources, causing control system paralysis.
To address these security challenges, a multi-layered, deep defense security strategy is needed:
· Hardware-Level Security: Use hardware modules with secure boot functions to ensure firmware integrity.
· Communication Security: Encrypt and verify the integrity of communication data between PLCs and other devices.
· Access Control: Implement role-based access control to restrict unauthorized operations.
· Security Monitoring: Real-time monitoring of PLC operating status to detect abnormal behaviors and potential attacks.
· Regular Updates: Timely installation of security patches to fix known vulnerabilities.
Additionally, it is necessary to promote the formulation of security standards and the cultivation of security awareness. The AI-PLC security certification framework (TR 63283-1) being developed by IEC will provide standard guidance for PLC security. At the same time, enhancing engineers’ security training and improving overall security awareness will help build a comprehensive PLC system security protection system.
7 Future Outlook: Development Prospects of PLC Technology in Industrial Intelligence
7.1 Intelligent Autonomous Control Systems
In the next decade, PLC technology will further develop towards intelligence and autonomy. Through deep integration with artificial intelligence technology, PLC systems will gradually acquire self-learning and self-adaptive capabilities, achieving a leap from “automation” to “autonomy.” This evolution will mainly manifest in three aspects:
· Hybrid Intelligent Architecture: PLCs will run lightweight AI models locally to handle real-time control tasks while collaborating with the cloud to continuously update knowledge bases. Siemens’ Industrial Copilot is a typical representative of this direction, providing intelligent programming assistance to engineers and enhancing development efficiency.
· Self-Evolving Systems: Through online learning technologies, PLC control systems will achieve continuous self-optimization of control strategies. Similar to the self-play mechanism of AlphaGo Zero, future PLC systems can optimize control parameters through continuous interaction with the environment and themselves, adapting to changing production conditions.
· Human-Machine Symbiotic Interfaces: Augmented reality (AR) technology will deeply integrate with PLC systems, intuitively presenting PLC decision-making bases and equipment status information. Schneider is testing the HoloLens 2 industrial kit, which can overlay the logical states and data analysis results of PLCs visually onto real devices, greatly simplifying system debugging and maintenance processes.
Research by Boston Consulting Group indicates that fully AI-enabled PLC systems can reduce factory operating costs by 22-35%. This data clearly demonstrates that the intelligent development of PLC technology will bring significant economic benefits to enterprises, propelling industrial intelligence into a new stage of development.
7.2 Open and Collaborative Ecosystems
The future development of PLC technology will increasingly trend towards openness and collaboration, breaking the closed ecosystems of traditional industrial automation. This shift will primarily manifest in two aspects: technical standards and industrial ecosystems:
In terms of technical standards, open standards such as IEC 61131-3 and IEC 61499 will further popularize, providing a foundation for interoperability among devices from multiple manufacturers. Cross-platform development environments like CODESYS will become industry standards, enabling PLC programs to be seamlessly ported across different hardware platforms. At the same time, PLCs will increasingly support modern IT programming languages (such as Python and C++), attracting more IT developers into the industrial automation field and promoting cross-disciplinary integration of technology and talent.
In terms of industrial ecosystems, the traditional closed vertical supply chain will transform into an open and collaborative industrial ecosystem. Platform-based and modular PLC architectures will allow flexible combinations of hardware, software, and application services from different manufacturers to meet personalized needs. As demonstrated by Jiangsu Telecom’s “Smart PLC,” telecom operators, cloud service providers, automation manufacturers, and vertical industry application developers will jointly build a diversified industrial ecosystem, driving innovation and application of PLC technology.
This open and collaborative ecosystem will significantly lower the technical barriers and costs of industrial intelligence transformation, enabling small and medium-sized enterprises to also benefit from advanced PLC technology. Jiangsu Telecom’s lightweight and quick-deployment service model has helped Hainuo Furnace Industry save 700,000 yuan in travel expenses annually and reduce equipment maintenance time by 70 hours per month; it has assisted Wuhua Electric in achieving an average reduction of 2 hours in production scheduling time, saving 300,000 yuan in labor costs annually. These cases demonstrate that the open and collaborative PLC technology ecosystem will create tangible value for enterprises of different scales.
7.3 Specialized Talent Cultivation Systems
In light of the rapid development of PLC technology and the current talent shortage, there is a need to build a more comprehensive specialized talent cultivation system. This system should encompass higher education, vocational education, and enterprise training at multiple levels, forming a complete talent supply chain integrated with industry and education.
In higher education, it is necessary to break down traditional disciplinary barriers and construct an interdisciplinary curriculum system. Programs in automation, computer science, mechanical engineering, and electronic information should strengthen cross-disciplinary integration, offering interdisciplinary courses such as “Industrial Internet and Smart Manufacturing” and “Industrial Intelligent Control Systems” to cultivate students’ systems thinking and comprehensive abilities. The experimental teaching component should introduce industrial-grade PLC equipment and real industrial application scenarios, enhancing students’ practical skills and engineering literacy through project-based learning.
In vocational education, training content and certification systems should be updated in a timely manner to keep pace with technological development trends. Specialized vocational competency standards and training courses should be developed for the integration of PLC with AI, IoT, and cloud computing, helping in-service engineers update their knowledge structures and master the application capabilities of new technologies and tools.
In enterprise training, a regular technical training mechanism and knowledge management system should be established. Large enterprises can set up internal academies or training centers in collaboration with universities and research institutions to customize professional talent cultivation. Small and medium-sized enterprises can rely on industry associations and public service platforms to access talent cultivation resources and support.
By constructing this multi-level, comprehensive talent cultivation system, a solid talent guarantee can be provided for the continuous innovation and application promotion of PLC technology, supporting the smooth implementation of industrial intelligence strategies.
8 Conclusion: Strategic Value of PLC Technology in Industrial Intelligence
Through multi-dimensional in-depth analysis, it is clear that PLC technology holds irreplaceable strategic value in the process of industrial intelligence. As the core cornerstone of industrial automation, PLC technology has not only driven the automation process of industrial production over the past few decades but has also consolidated and strengthened its key position in industrial control systems through continuous technological innovation and functional expansion in the era of smart manufacturing.
The strategic value of PLC technology is first reflected in its support for the foundation of industrial intelligence. With outstanding reliability, strong real-time performance, and flexible adaptability, PLCs provide a stable and reliable control foundation for industrial intelligence. In an increasingly complex and interconnected industrial environment, this foundational role of PLCs has not diminished; rather, it has been further strengthened by the higher demands of smart manufacturing. Whether in flexible production lines in discrete manufacturing, smart factories in process industries, or the intelligent upgrades of critical infrastructure in energy and transportation, PLC technology is indispensable.
Secondly, the strategic value of PLC technology is reflected in its bridging role in the integration of IT and OT. Modern PLCs achieve vertical integration of data from underlying devices to upper-level information systems by supporting various industrial communication protocols and IT-friendly interfaces, providing the technical foundation for the implementation of the industrial internet. At the same time, as edge computing nodes, PLCs alleviate cloud computing pressure through local data preprocessing and edge intelligent analysis, ensuring the real-time and reliability of control systems. This bridging role makes PLCs an indispensable key component in the architecture of industrial internet systems.
Thirdly, the strategic value of PLC technology is reflected in its continuous innovative evolution capability. In the face of the impact of new technological waves, PLCs have not remained stagnant but have actively embraced change, continuously integrating software-defined automation, artificial intelligence, the Internet of Things, and other new technologies to expand functional boundaries and application scenarios. From hardware PLCs to software-defined PLCs, from logic control to intelligent decision-making, and from isolated devices to cloud-edge collaboration, PLC technology demonstrates strong vitality and adaptability. This continuous innovative evolution capability ensures the ongoing relevance of PLC technology in the era of industrial intelligence.
Finally, the strategic value of PLC technology is also reflected in its extensive industrial ecosystem. After decades of development, PLC technology has formed a complete industrial chain and a rich application ecosystem, with numerous suppliers, system integrators, and developers participating globally. This rich industrial ecosystem provides users with diverse choices, reduces technological dependency risks, and continuously drives the ongoing innovation of PLC technology.
In summary, PLC technology, as a core supporting technology for industrial intelligence, will continue to maintain its strategic position in the foreseeable future. With the continuous evolution of technology and the ongoing expansion of application scenarios, PLCs will deepen their integration with emerging technologies, strengthen their edge intelligent role in the industrial internet, and provide a solid technical foundation for the digital transformation and intelligent upgrading of manufacturing. For China, seizing the strategic opportunity of PLC technology transformation and upgrading, strengthening core technological breakthroughs and industrial ecosystem construction, is of significant practical importance for achieving the strategic goal of becoming a manufacturing powerhouse.