Industrial Networking and Digital Transformation

The field of networking is undergoing a massive transformation as more artificial intelligence-based tools make their way into products and services. Traditional enterprise networks are immediately poised to benefit and grow as more tasks that used to require costly networking expertise are automated. Although industrial networking is a smaller market, advances in enterprise networking will eventually be tuned and incorporated into industrial networking applications, providing similar benefits and growth to a manufacturer’s production process, efficiency, and overall cost. Manufacturers are best served by achieving full OT connectivity while planning for future communications growth.

“As an engineer working on a project, aim to design with future capabilities in mind.”

Author contributor: Solutions Architect, CISSP CCNA, Matt Smith

Introduction

Because of its ability to automate processes, artificial intelligence (AI) is a powerful new technology that is finding new use cases in almost every market space. Machine learning, a subset of artificial intelligence, can analyze large amounts of data to uncover previously unknown trends, resulting in better decision-making and thus increased efficiency and productivity. Enterprise networking is no exception, with machine learning tools now widely available to automate network configuration, security, management, and maintenance.

Because it is a niche market with specific requirements, industrial networking tools often lag behind those designed for enterprise applications. While the OT network has unique data requirements, current trends in enterprise networking automation are likely to find their way into industrial networking, resulting in new benefits. Digital transformation, also known as Industry 4.0 manufacturing, is defined by connectivity. Manufacturing companies that position themselves to be able to adopt AI-driven technologies as soon as possible will reap the most benefits.

Enterprise Networking Trends

Enterprise networking describes the infrastructure and systems that connect a large organization. It entails the design, implementation, and management of an organization’s connectivity and communication needs. It can encompass multiple departments, physical locations, cloud-based environments and remote access. Enterprise networking aims to ensure seamless and secure communication among all connected resources.

As AI-based tools make their way into networking, simpler (flat) architectures are being deployed in enterprise environments, delegating complex network architecture, management and security to software platforms running on independent servers. Cisco’s DNA Center is one such example of a flat architecture that uses machine learning to automate a wide range of networking tasks. With all devices on one singular flat network, machine learning data analytics can take over the tasks that were previously accomplished with more complex and inflexible network structures, including:

  • Streamlined device deployment by identifying device types based on MAC address, and assigning appropriate access rights.
  • Benchmarking network traffic for better understanding.
  • Optimizing network performance.
  • Detecting traffic anomalies to identify security risks.
  • Automatic response to security threats

The end result is a highly-adaptable network that is configured and managed by powerful servers with onboard intelligence.

OT Networks: Distinct Requirements

The primary role of an OT network is to ensure that industrial control systems and equipment operate reliably and safely. Because its role differs from enterprise networking, so do its requirements. Some distinctions are:

  • Real-time, reliable data connections between control systems and equipment: Time-sensitive connectivity is critical for precise control and coordination of robotics and equipment. IEEE 1588, also known as precision time control (PTP) is a standard used for highly-accurate clock synchronization across a network. This accuracy is required for servo-based systems, robotics, and other feedback control systems to function properly.
  • Network architecture that supports control applications and security: Micro-segmentation is generally beneficial to OT networks. This architecture reduces the potential spread from a cyber attack, and also allows for time-sensitive connectivity.
  • Distinct OT and IT networks with DMZ: To ensure that process data is visible to management, networks must be connected. This connectivity is driving digitalization and Industry 4.0, allowing for increased plant visibility and data-driven decision-making.

Because these networks have different data communication and security requirements, it is still best practice to separate them with a firewall and a demilitarized zone (DMZ). Then, if a computer joins the network, it is automatically connected to the IT layer. If the computer needs to connect to equipment on the OT network, it will do so via the firewall and additional security measures within the DMZ, protecting the equipment from potential security threats.

The Future of Industrial Networking

OT networks require specialized tools that are tailored to the specific requirements of the connected equipment. While today’s automated AI-driven solutions designed for enterprise networking may not be the precise fit in their current state, over time these challenges are expected to be overcome and OT networking will see similar streamlining and automation of network processes.

Connectivity: The Key to Efficiency, Troubleshooting, and Security Gains

Moving toward a fully connected facility is critical for being ready to integrate new networking tools as they become available. With a strong data connection between the OT environment and the enterprise network, management has complete access to process data, equipment status, and line issues. Data-driven decisions can be made to improve efficiency, troubleshooting becomes easier, and cybersecurity measures can be implemented.

Efficiency: Access to process data enables identification of bottlenecks in plant performance. Machine learning algorithms can be used to identify patterns in data, resulting in a better understanding of how the plant operates. Production rates can be analyzed and interpreted, allowing management to make data-driven decisions about maintenance intervals, equipment upgrades, and new equipment investments.

Troubleshooting: When all of the plant’s equipment is networked, troubleshooting becomes much easier. While many alarms and events are common in a fault situation, they are all caused by the initial fault condition. As a result, root cause analysis is critical. When equipment is connected to a network, fault analysis tools can be fully utilized for debugging purposes. In networking, this is known as a security information and event management (SIEM) system. With access to all network data, the SIEM system logs all events, making it easy to identify the initial fault.

Visibility tools increase efficiency by simplifying troubleshooting. They provide a clear picture of the specific devices that have failed, as well as the communication errors that have resulted. As an example, a recent client was having persistent problems restarting a system following a power cycle, resulting in extended downtime. By connecting tools that provide network visibility, E Tech engineers were able to obtain the necessary communications information to diagnose the underlying problem.  The problem was readily addressed, and the extended downtime issue was resolved.

Security: The need for a secure OT network should be considered a high priority for all industrial manufacturing facilities, as discussed in detail in the blog “The Case for Investment into Cyber Security.”

A secure plant starts with network connectivity and visibility for all devices. There are an array of tools available for network visibility and security. Claroty’s platform specializes in cybersecurity for OT Networks. It contributes to the zero trust network architecture by continuously monitoring all network activities and connections in industrial environments, ensuring that no device is trusted by default and that only authenticated users can interact with equipment. Claroty queries all network devices, obtains their current firmware version and generates a Purdue model diagram that depicts all lines of communications between them. Furthermore, it compares the firmware version associated with each device to the searchable advisory, providing the organization with an actionable list specific to their plant or environment.   

Plan Ahead: Take Steps Towards Industry 4.0

Industry 4.0, a popular term for the transformation of manufacturing and industrial processes through integration of digital technologies, machine learning-based data analytics, and automation starts with the connectivity of all devices. The following list is relevant for any facility, at any stage of digitalization to take steps toward automated, connected, and cyber-secure manufacturing:

  • Assessment of the current system An in-depth IT/OT assessment will detail the current state of all equipment, including associated vulnerabilities with current software and firmware, as well inefficiencies and vulnerabilities in OT Network Architecture. 
  • Connect all equipment in a secure manner Work to connect all equipment to a robust and secure OT network. The advantages of digitization grow as more devices are connected.
  • A note on air-gapped devices An air-gapped device is one that is not directly connected to the OT network. This mitigates, but does not eliminate its cybersecurity vulnerability. It remains a threat vector because the device will most likely be updated through connection to an insecure computer.
  • Assess the current communication capacity Current communication bandwidth within a system is often fully utilized. The addition of automation increases the required communication bandwidth.  As a result, it’s generally advisable to increase bandwidth and processing capability above the minimum requirements to support future growth and scalability.
  • Stay up to date with TIA communications standards Electrical engineers in the industry benefit from staying current with TIA communications standards, which should be considered during panel design and wiring sizing.
  • Keep informed of changes within the industry All engineers must keep up with the industry’s rapid changes while keeping in mind that training obtained as recently as ten years ago may no longer be valid today. Attending trade and automation shows, as well as connecting with online peers in forum-based communities, are all effective ways to keep knowledge up to date.
  • Use a Registered Communications Distribution Designer (RCDD) Hiring an RCDD to design and implement required communications systems ensures that industry standards are met while also considering future scalability and long-term reliability. This type of designer is reasonably priced and capable of developing a system warrantied for 25 years.

Managers who plan for increased connectivity position their facilities to be early adopters of automated networking technologies, resulting in greater efficiency, ease of troubleshooting, and enhanced cybersecurity.

In conclusion, the integration of AI into enterprise networking is leading to highly flexible and automated network configuration and management solutions. OT networking has its own distinct requirements that currently disqualify these enterprise solutions. However, the expectation is that in due time these requirements will be addressed and OT networking will follow a similar trend of automation and flexibility. The transition to a fully connected OT network positions a manufacturing facility to benefit from data-driven decision-making, enhanced operational performance and robust security. By taking proactive steps towards Industry 4.0—such as connecting all devices, increasing communication capacity, and staying updated with industry standards—manufacturers can ensure they are well-equipped for future growth and automation in OT networking technology.


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