The Industrial Internet, as an emerging business model and application paradigm formed by the deep integration of next-generation information technology with the industrial economy, serves as the critical foundation for industrial enterprises to achieve digital transformation. In recent years, numerous integrated solutions have emerged through innovation tailored to the production characteristics and pain points of key industries. Examples include supply chain collaboration in high-end equipment manufacturing, remote operation and maintenance of major equipment, energy conservation and emission reduction in the steel industry, and production safety monitoring in the petrochemical sector. These solutions fully leverage the industrial internet's aggregation and amplification effects, driving the digital transformation of manufacturing and delivering core value in quality enhancement, cost reduction, and efficiency gains.
Industrial Internet platforms provide capabilities for aggregating, integrating, storing, processing, computing, and analyzing massive industrial data, enabling enterprises to build unified, full-lifecycle operational control data platforms. Numerous platform-related technologies are undergoing continuous iteration and advancement (e.g., microservice components, containers, batch data processing, stream processing). These technologies progressively empower us to conduct in-depth analysis of heterogeneous, massive industrial data while accelerating the accumulation of industrial knowledge, decoupling of hardware and software, and rapid deployment of innovative applications. However, we recognize that these advanced, open-source technologies are fundamentally tools to help enterprises achieve intelligent manufacturing-not the end goal itself. Leveraging such platforms, large enterprises can optimize production across the entire manufacturing scope, enhance the full value chain of assets and operations, and ultimately achieve lifecycle-wide value optimization. For instance, the Abu Dhabi National Oil Company (ADNOC) Group leverages its panoramic digital command center to centrally monitor and optimize the asset and operational performance of 14 operating companies from its headquarters. Through solutions like predictive maintenance and value chain optimization, it has identified potential value optimization opportunities worth $60 million to $100 million for the group (providing oil and gas value chain optimization solutions, integrating asset and operational value chains, and maximizing production and operational returns).
The Industrial Internet offers numerous solutions in scenarios like service extension, networked collaboration, and personalized customization by connecting enterprises, users, and products. However, it remains in an exploratory phase for intelligent production scenarios, and enterprises still face significant challenges in production operations.
Challenges Facing Today's Manufacturing Enterprises
Market Challenges: Global economic and market uncertainties are compelling manufacturers to rapidly adjust strategies to adapt to more frequent and faster-paced market demands while navigating fluctuations in raw material and energy costs. This trend is forcing companies to rethink their operational approaches: they must continuously launch new products while shortening equipment procurement cycles, new product development timelines, and time-to-market. They need to establish demand-driven, supply chain-coordinated optimization business models and flexible production systems like large-scale mixed-line production-particularly critical for the discrete manufacturing sector.
Human Resources and Knowledge Retention Challenges: As older generations of workers retire, the expertise they possess in control systems, operations, and maintenance risks being lost. Industrial enterprises face significant challenges from workforce transitions. The new generation of digital natives expects industrial automation knowledge to be embedded within the systems they use, while traditional OT talent becomes increasingly scarce.
Challenges in Total Cost and Compliance: How to optimize and reduce costs for new construction projects and operational expenses while complying with increasingly stringent national environmental protection laws and regulations to enable sustainable development.
Industrial managers hope that Industry 4.0 and Industrial Internet technologies will help them address these new challenges. Industry analysts estimate that more flexible, next-generation production technologies could boost manufacturing productivity by 30%. However, research also indicates that 60% of companies fail to advance their projects beyond the pilot phase. This outcome stems from diverse factors related to personnel, processes, and technology. On the technological front, most manufacturers struggle to achieve higher returns from these innovations, primarily because their operational plant systems remain closed, proprietary setups. Since the 1970s, when DCS and PLC systems entered industrial automation, proprietary systems have evolved. To date, the market has developed around hardware-software bundling models, with each automation and information system vendor creating its own software ecosystem. This forces users to maintain multiple OT and IT systems, fostering high dependency on system vendors.
Current Bottlenecks at the Edge of the Industrial Internet
Non-Digital Architecture-Most modern automation systems are highly optimized for real-time control but fail to leverage the rapidly advancing technologies emerging from the IT domain. These cutting-edge digital technologies-including analytics, artificial intelligence/machine learning, object-oriented approaches, and service-oriented architectures-are essential for achieving intelligent manufacturing.
Hardware-Centric Business Models-While hardware enhancements can optimize existing control environments, they are not the most critical aspect of digital transformation. The true key lies in software-driven innovation that intelligently addresses operational technology challenges. Consequently, business value is steadily shifting from hardware-driven to software-driven models.
Limitations of Proprietary Systems-Currently, automation applications developed for one system cannot run on another. However, over the past decades in IT, open operating systems like Linux have fostered third-party application development, enabling rapid ecosystem expansion and the creation of rich software portfolios that meet business needs across multiple industries and market segments. Regrettably, proprietary systems in the industrial sector create barriers to innovation: users cannot reasonably cost-effectively enhance production systems or integrate and match best-in-class products from different suppliers. Their innovation pace is constrained by their reliance on proprietary system vendors. These barriers ultimately increase total enterprise costs.
For original equipment manufacturers (OEMs), the challenge lies in balancing two priorities: leveraging virtual debugging capabilities during modular design to bridge the virtual and physical worlds-thereby reducing costs, mitigating risks, and accelerating time-to-market-while simultaneously enhancing machine value-added services to expand markets and drive business growth.
System integrators (SIs) face a critical gap: automation systems lack tools connecting IT and OT domains. Ultimately, they find themselves compelled to invest significant human resources in developing highly complex customized solutions. Crucially, such bespoke services are difficult to replicate widely in the market. They seek software functional blocks that protect their industrial knowledge and industry-specific solutions, thereby reducing low-value engineering effort (by reusing objects and process algorithms across multiple projects). This allows their technical experts to focus more intently on resolving pain points and challenges within Manufacturing, Operations, and Maintenance (MOM) processes, ultimately creating greater value.
On the end-user (EU) side, addressing these challenges urgently requires comprehensive system management to minimize unplanned downtime, ensuring product delivery during peak seasons and reducing reliance on external technical support. There is a desire for flexible systems/production lines to ensure manufacturing agility, enabling greater production flexibility when demand shifts or maintenance schedules change.
Effectively resolving these issues and truly establishing a "software-defined industrial" digital industrial ecosystem requires addressing closed OT systems, standards, and ecosystem challenges at their source. This entails adopting open automation systems and standards while integrating additional technical capabilities to accelerate IT-OT convergence.
The Future of Open Automation Systems
Future automation system architectures will inevitably evolve toward openness, distributed deployment, and inherent security. Industrial automation technology and edge computing form the foundation of these open systems. Compared to traditional proprietary systems, open automation architectures will exhibit the following transformations:
It is evident that open automation architectures accelerate engineering development, enhance system agility, production flexibility, and overall efficiency. This shift represents more than a technical upgrade-it fundamentally redefines how processes and machinery are designed. Long-term, low-value programming for proprietary controllers will transition to plug-and-play automation systems. These systems will leverage extensive, thoroughly validated software function blocks developed by a vast ecosystem. They will run across diverse hardware from multiple vendors-spanning embedded control systems to powerful edge intelligence devices.
Open standards are essential for building open automation systems, and IEC 61499 is the key standard unlocking this new frontier. By defining object-oriented modeling rules, it encapsulates the control models and algorithms of controlled objects into "black boxes" (software function blocks). These verified function blocks can be reused across different scenarios, significantly reducing repetitive programming efforts. For users, it suffices to understand the functionality provided without needing to know the implementation details, thereby protecting developers' intellectual property. Unlike traditional function blocks, those defined by this standard operate based on event triggering rather than cyclic scanning. This aligns with object-oriented concepts and programming approaches in the IT domain, making it a natural IT/OT convergence technology. It facilitates improved controller CPU efficiency and load balancing, is particularly suited for distributed systems, and enables seamless integration of advanced IT technologies into automation systems. The standard further defines rules for application models, system models, and device/resource models. Their integration enables users to design applications independently of underlying automation hardware. This hardware abstraction approach shortens project timelines and reduces dependence on equipment manufacturers. Combined with the object-oriented development of function blocks, it significantly simplifies online adjustments for production lines and equipment. Naturally, the standard also provides methods for composing basic function blocks into composite blocks and for quickly connecting different function blocks (via simple drag-and-drop), significantly reducing software programming debugging workload and program error rates. In summary, achieving device interoperability, system reconfigurability, and software portability are its core objectives. Organizations like the Open Process Automation Forum (OPAF) and the International Association of Process Industry Automation Users (NAMUR), which are currently led by end-user participation, are advocating for a shift away from existing proprietary automation system frameworks based on this standard-the best illustration of this pursuit.
In recent years, edge computing technology has also experienced rapid development. Container technology provides effective methods for batch updating/upgrading applications for edge control and ensuring timely data transmission and processing. Container technologies, primarily Docker, and container orchestration tools like Kubernetes are now maturing. Microservices architecture continuously enhances resource utilization efficiency at the edge, promotes functional decoupling and reuse, accelerates application development, and has become a key trend in edge computing technology. Standards like OPC UA and Time-Sensitive Networking (TSN) provide international frameworks and deterministic networks for field device interconnectivity, meeting diverse data transmission and exchange requirements in industrial applications. The integration of these next-generation information and communication technologies with IEC 61499 standard technologies will accelerate the progress of open automation. This openness extends not only to standards but also to networking, hardware, software, and system architecture, laying a solid foundation for achieving digitalization, networking, and intelligence in factories and workshops.
Open automation will drive the rapid development of the Industrial Internet, ultimately addressing pain points for end users, system integrators, and OEMs. This approach achieves flexible production, shortens time-to-market, reduces engineering time and costs, enhances operational and production efficiency, and protects intellectual property. Indeed, a recent comparative study by an international third-party firm highlights this effectively: For completing a typical small-scale automation project (tasks including creating applications, importing relevant databases, establishing logic, configuring devices, developing HMIs, and deploying the project), traditional automation software tools required 40 hours. In contrast, using an open automation system reduced this time by 68%. To test system agility, controllers were manually swapped between devices and new controllers configured for the original devices. These operations proved cumbersome with traditional proprietary systems, whereas open automation systems executed them 70% to 80% faster.
In summary, whether the future Industrial Internet can overcome current bottlenecks and further advance the digital transformation of industrial enterprises in depth and breadth depends on establishing an open automation system built upon new concepts, architectures, and standards. Traditional hardware-centric proprietary systems will be replaced by software-centric open systems. More cloud technologies will be applied to edge computing, enabling a large pool of IT talent to deeply integrate with industrial application knowledge within this open framework. We can foresee that the Industrial Internet will forge a healthy, sustainable path forward by leveraging this open ecosystem.