Transformative Technologies Move Automation Forward

Transformative Technologies Move Automation Forward
Transformative Technologies Move Automation Forward

Advances centered around Internet protocol (IP) technology are dramatically improving industrial control and automation communications. Advanced physical layer technologies including single-pair Ethernet as well as time-sensitive networking (TSN) improvements enable industrial automation to leverage Internet of Things (IoT) technologies and standards, bringing the benefits of IP to industrial edge devices including sensors, actuators, vision, robots, controllers, contactors and drives.

Single-pair Ethernet (SPE)10BASE-T1 is an exciting development enabling seamless Ethernet connectivity from sensor to enterprise. 10BASE-T1 is a 10 Mbps single-pair Ethernet physical layer network technology under the IEEE 802.3cg specification focused on automotive and industrial applications. It lowers cost, weight, cable diameter, and connector size using the IP. SPE data transport consistent with global standard IP communications will accelerate this trend.

The SPE two wire design lowers installed cost with more than 75% smaller cable diameter, reduced weight, lower cost, smaller connector size, and 30% more bend radius than CAT 5. SPE also opens the possibility to reuse existing installed twisted pair field wiring for Ethernet communications simplifying plant and machine retrofits.

SPE is an enabler for intelligent field devices including sensors, actuators, vision, robots, controllers, contactors, vibration monitors and motor drives. These intelligent devices perform control at the edge and communicate non-control operations data including quality measurements, production efficiency, asset monitoring, diagnostics, and predictive maintenance advisories directly to manufacturing operations, business enterprise, and cloud systems. System-on-Chip (SoC) technology makes immediate processing in any field device practical due to lower cost with high performance since they are being used in volume products such as smartphones and personal health trackers.

Multidrop configurations are possible with the 10BASE-T1S part of the specifications providing collision-free, deterministic Ethernetbased transmission over a multi-drop network without Ethernet switches, which means even greater total installed cost savings. 10BASE-T1S implemented without switches requires fewer cables and less power. Multidrop technology already has been providing installed cost advantages when using existing automation networks, including Modbus, DeviceNet, Profibus, and CANopen. This can now be accomplished with SPE using standard IP communications.

The power over data lines (PoDL) feature of the specifications provides a way to power remote devices. The specification allows for 12-, 24-, and 48-volt operation; 12 volts is convenient for battery powered and mobile applications, while 24 volt is a common voltage for control panels and controllers.

Single-pair Ethernet is the basis for the advanced physical layer (APL) being developed to bring Ethernet to field-level instruments in hazardous areas. Ethernet at the field level will make digitalization for process industries a reality with its universality and speed. Current and voltage will be limited to have an intrinsically safe solution for Zones 0 and 1/Div. 1. The main goal is to adopt proven technologies and options in the process automation field. The general topology will be based on the well-known trunk-and-spur configuration.

The FieldComm Group, ODVA, Profibus, and Profinet International joined to support the standardization of an APL suitable for use in demanding process instrumentation applications. This initiative leverages the work of the IEEE 802.3cg Task Force, including amendments to the IEEE 802.3 Ethernet standard for an Ethernet physical layer operating at 10 Mb/s over single-pair cable with power delivery. Additional developments define the requirements and develop the necessary technology to achieve an industrial Ethernet suitable for use in hazardous locations up to Zone 0, Div. 1.

TSN holds the promise of providing a unifying deterministic network shared by all applications throughout the computer industry. The TSN vision is a common multivendor shared network for multimode communication for general computing, voice-over-IP (VoIP), professional audio, video, file transfer, industrial automation, building automation, and any other data communication.

Since TSN is a totally managed shared network architecture, all network traffic including new TSN Ethernet switches and routers and all industrial protocols in the plant would need to conform and be compliant with the TSN set of standards to achieve deterministic and reliable communications.

Time-Sensitive Networking Task Group of the IEEE 802.1 is the working group developing the standard for this highly deterministic synchronized networking. The TSN Task Group was formed in November 2012 by renaming the existing Audio Video Bridging Task Group and continuing its work. The standards define mechanisms for the time-sensitive transmission of data. However, creating a practical multivendor TSN architecture has challenges and adds new layers of complexity for industrial Ethernet networking. Network timing has been tightly coupled to network configuration and management. To take advantage of TSN time scheduling, control programming software and controller firmware would have to be redesigned to accommodate the definition of input/output (I/O) points and variable timing specifications.

Since the goal is to support multiple industrial network protocols along with data multimedia applications, this will require an industrywide shared network manager and an application programming interface (API) standard to which all vendors need to conform. These standards are evolving.


5G wireless

The idea of wireless industrial automation has long been an elusive goal on the wish list of many users but may become more mainstream with 5G communications that delivers higher performance and determinism. 5G may well be the ideal wireless industrial automation networking mechanism, and companies are installing private 5G networks in manufacturing plants. 5G technology is ramping up to high-volume production for consumer, commercial, and IoT applications that will increase capabilities and lower costs. This is the same phenomena that created the compelling case for standard Ethernet to be adopted for industrial communications networks (i.e., Modbus TCP/IP, EtherNet/IP, Profinet, EtherCAT)

Another factor is IoT devices are extremely rugged, inherently meeting industrial automation requirements off-the-shelf. Expectations are running high for the potential of 5G wireless communication for industrial applications. 5G makes monitoring and controlling a broader range of devices practical, such as using the connected screwdriver and nut runner to automatically control torque as well as communicate data quality, track and trace, and productivity data. 5G technology is being deployed by mobile companies.

The 5G technology offers benefits for manufacturing and wireless communications in production plants including control and automation for a wide range of applications including:

  • Sensors and actuators
  • Automated guided vehicles
  • Augmented reality devices
  • Wireless tooling
  • Video cameras (defect detection, auto ID reading, track and trace, etc.)
  • Remote expert audio/video devices
Companies are already starting to deploy private 5G networks within plants and are seeing increases in performance, determinism, low latency, and reliability. There are three major benefits of 5G networks, according to IEEE: High data rates (1-20 Gbit/s), low latency (1 ms), and larger network capacity and scalability.

According to the report published by Allied Market Research, the global industrial 5G market generated $12.47 billion in 2020, and is estimated to garner $140.88 billion by 2030, witnessing a CAGR of 27.5% from 2020 to 2030. The report offers an extensive analysis of changing market dynamics, value chain, top segments, regional scenarios, key investment pockets, and competitive landscape.

There are many working to support the growth of 5G wireless in industrial organizations. The 5G Alliance for Connected Industries and Automation (5G-ACIA) serves as the central and global forum for addressing, discussing, and evaluating relevant technical, regulatory, and business aspects with respect to 5G for the industrial domain. The 5G Alliance notes that one of the main differences between 5G and previous generations of cellular networks lies in 5G’s strong focus on machine-type communication and IoT. The capabilities of 5G thus extend far beyond mobile broadband with ever-increasing data rates. 5G supports communication with reliability and extremely low latencies, while facilitating massive IoT connectivity.

5G-ACIA says manufacturing may see 5G having a disruptive impact as related building blocks such as wireless connectivity, edge computing, or networks will find their way into future smart factories. The organization has published a whitepaper, “5G for Connected Industries and Automation,” which provides an overview of 5G’s basic potential for connected industries, in particular, the manufacturing and process industries, and outlines relevant use cases, requirements and other information.


The OPC ecosystem

OPC Foundation standards, semantic data models, and ecosystem are growing significantly making multivendor secure and reliable data exchange in industrial automation applications. They are becoming widely adopted by IT, operational technology (OT), and cloud suppliers creating a valuable and efficient distributed industrial manufacturing architecture. The ecosystem is a community that uses the OPC data model standards and contributes OPC Companion Specifications to address use cases to achieve a unified vendor independent data interchange that simplifies data exchanges, lowers application engineering labor, and improves quality. Stakeholders include developers, users, software, services and other stakeholders.

OPC UA standards are platform-independent and ensures the seamless flow of information among devices from multiple vendors. Since 1996, the OPC Foundation has facilitated the development and adoption of the OPC information exchange standards with the mission is to enable industry vendors, end users, and software developers to achieve interoperability in their manufacturing and automation assets—secure and reliable interoperability for moving data and information from the embedded world to the enterprise cloud. The Foundation serves more than 850 members worldwide in the industrial automation, IT, IoT, IIoT, M2M, Industry 4.0, building automation, machine tools, pharmaceutical, petrochemical, and smart energy sectors. OPC’s most recent projects include:
  • The OPC Field level communications (FLC) initiative has a goal of delivering an open, cohesive approach to implement OPC UA in field devices using harmonization and standardized application profiles including sensor I/O, motion control, safety, system redundancy, standardization of OPC UA information models for field level devices in online and offline scenarios (e.g., device description resp. diagnostics), and mapping of OPC UA application profiles related to real-time operations on Ethernet networks including TSN. A major goal is vendor-independent end to end interoperability into field level devices for all relevant industry automation use cases.
  • OPC companion specifications support OPC UA scalability. OPC UA supports a wide range of application domains, ranging from field level (e.g., devices for measurement or identification, programmable logic controllers), to enterprise management support with companion specifications. The growing number of companion specifications created by a wide range of industry groups focus on applications that simplify engineering and provide a common semantic model for multivendor interoperability.
OPC Foundation has three ways companion specifications can be created:
  • Internal: These are models created by OPC internal working groups. They are associated with the Unified Architecture specification.
  • Joint: These are models created in a joint working group between the OPC Foundation and other organizations. These joint specifications represent the majority. The released joint companion specifications can be found here. The Joint working group program is defined here.
  • External: Companion specifications can also be created independent of the OPC Foundation. To support creating companion specifications, the OPC Foundation created a template. It is available for download here.


VDMA companion specifications

The VDMA is a host of several European and global sector committees that represents the broad machine building and parts of the process industry (Figure 1). VDMA contends that interoperability is key to success. This interoperability will be brought about by:
  • interface development through standards
  • integration into the shop floor through standard interfaces
  • access to standardized production data.
OPC UA for Machinery forms the basis for interoperability because it can be referenced from other companion specifications or implemented as standalone model. It can be developed together with all OPC UA working groups. It defines harmonized basic building blocks for broad use. Forty of the VDMA working groups standardize the interfaces of machines and components in individual industries. All basic information models are brought together in the Companion Specification.

As an open interface standard, OPC UA is a central prerequisite for the successful introduction of Industry 4.0 into production. OPC UA ensures the interoperability of machines and systems, which can be linked and redesigned as required. OPC UA serves as basis for the Global Production language. VDMA envisions interoperability through cross domain information models, domain-specific harmonized information models, OPC UA meshed communication networks, and proprietary communications To make this vision a reality, VDMA is working with its member companies to develop industry specific OPC UA Companion Specifications, thus creating a global language of production.

Figure 1: Overview of OPC UA in the VDMA organizations.


CESMII OPC UA Cloud Library

The CESMII OPC UA Cloud Library is an example of jointly created companion specifications. The OPC Foundation in cooperation with Clean Energy and Smart Manufacturing Innovation Institute (CESMII) launched a globally available OPC UA cloud library. The co-developed online library has growing contributions from all major cloud vendors leveraging open interfaces and is available for sharing, finding, and collaborating on OPC UA information models.

The UA Cloud Library already contains more than 65 OPC UA information models created by individual companies as well as international standards organizations like AutoID, DEXPI, MDIS, MTConnect and more than 30 VDMA working groups as part of the OPC UA Companion Specification work. The UA Cloud Library can be accessed from the OPC Foundation website at: http://UACloudLibrary.OPCFoundation.org The open-source reference implementation can be accessed at: https://github.com/OPCFoundation/ UA-CloudLibrary. Specifications, thus creating a global language of production.

Figure 2: The UA Cloud Library contains more than 65 OPC UA information models created by individual companies as well as international standards organizations.


Edge control and automation

Distributed manufacturing architecture (DMA) requires processing at the manufacturing processes to achieve performance, simplify system architecture, and ensure high reliability and availability. Processing in edge computers and CPUs embedded in field devices including, sensors, actuators, motor controls, bar code readers, cameras, and other field devices host local control and optimization with the ability to access and use remote computing resources for complex calculations and tuning internal algorithms based on digital twin, analytics, and artificial intelligence (AI) host analysis. These edge CPUs run standard operating software platforms to take advantage of a wide range of multivendor applications. Edge computing is a growing trend. As noted by Gartner, “What Edge Computing Means for Infrastructure and Operations Leaders” predicts 75% of data will be created and processed outside traditional centralized data centers or the cloud by 2025.

Enterprise, cloud, and edge computing are complementary creating a more responsive synchronized system architecture that increases performance and reliability. Time critical applications execute onsite, using real-time data by eliminating network latency and provide higher cybersecurity protection. Coupled with a cohesive plan for managing the data and infrastructure creates a more responsive system architecture unifying workflows from edge to enterprise/ cloud. Edge computing reduces communications latency and ensures bandwidth is available for necessary systemwide communications.

Edge computers. The growing trend is to use industrial edge computers as a preferred platform in place of programmable logic controller (PLC) and distributed control system (DCS) controllers as a fundamental building block to efficiently digitize and integrate the entire manufacturing business from enterprise to sensors and actuators. Industrial automation is the only industry that still uses dedicated proprietary computers, PLCs, and DCS controllers, rather than standard computing platforms at the edge of systems for local control, optimization, analytics and data refinement. Linux containerized architectures provide a platform for multiple functions to run virtualized on industrial computers.

Field devices. CPUs embedded in field devices host local control and optimization on standard operating software platforms to take advantage of a wide range of multivendor hardware and applications. System-on-Chip (SoC) technology makes immediate processing in field devices practical since they are being used in high volume, driving costs down, and increasing power. The SoC is an integrated circuit (IC) that includes various electronic parts such as a central processing unit (CPU), I/O ports, internal memory, analog input, output blocks, and in many Ethernet, Wi-Fi, Bluetooth and other communications.

The NAMUR Industry 4.0 for Process and other initiatives envision how distributed control across field devices perform in-situ control, optimization, and diagnostics. These field devices also communicate non-control operations data (i.e., quality, production efficiency asset monitoring, etc.) directly to enterprise and cloud systems.

AI chips. An exciting development are inference chips that execute AI, machine learning (ML), and other sophisticated applications in parallel with multiple processors at high speed. Server and cloud, AI, and ML solutions can enhance a wide range of applications but compute costs, network communication speed, and latency factors pose limitations for many real-time industrial and process applications. This new class of “AI chips” brings the computing right into edge devices.


Robotics explodes with possibilities

The application of robotics is accelerating and considered broadly includes large robots, collaborative robots, autonomous guided vehicles, and innovative combinations for production and material flow. Accelerating the application of collaborative type of robots is the integration of vision systems, image recognition, AI, location awareness, and digital manufacturing system integration. which enables a wide range of new applications.

Robots programmed like playing a game are a high impact automation development for increasing manufacturing productivity and are particularly effective for small and medium manufacturing enterprises. Collaborative robots are a new breed of lightweight and inexpensive robots, with safety features that enable people to work cooperatively with these devices in a production environment. Collaborative robots can sense humans and other obstacles and respond by automatically stopping so that they cause no harm or destruction. With these robots, protective fences and cages are not required and therefore they can enable flexibility and lower implementation costs. These robots are particularly attractive with high return on investment.

This breed of robots is following a similar pattern that ignited the personal computer revolution, providing a product with less power than larger offerings, but with added value for a broader number of users. The rate of robot adoption is accelerating throughout the world, particularly in China, which has become the largest purchaser of robots in the world.

Robot sales continue to grow in Europe, Asia, and the Americas. In 2021, a new record of 486,800 units were shipped globally—an increase of 27% compared to the previous year. Asia/Australia saw the largest growth in demand: Installations were up 33% reaching 354,500 units (Figure 3). The Americas increased by 27% with 49,400 units sold. Europe saw double digit growth of 15% with 78,000 units installed. These preliminary results for 2021 have been published by the International Federation of Robotics. For more trends on the global robotics market please visit IFR´s website.


Figure 3: Asia/Australia saw the largest growth in demand, with a 33 percent increase in installations, reaching 354,500 units.

There are a number of these being manufactured today including Hailo, Nvidia, Intel Myriad-X, and Google Edge TPU. The high-volume application driving the price of these down is image processing and recognition, particularly for security systems. The chips are already available on industry-standard add-on modules using the M.2 and mPCIe connector standards found in many computers including embedded industrial PCs at single piece prices under $90 U.S. Applications possibilities include optimization of production, processes, track and trace, logistics, quality, machine functions, and predictive maintenance by eliminating inherent limitations of server and cloud solutions with processing at the edge.

The Allied Market Research recently published noted the global artificial intelligence chip industry accounted for $8.02 billion in 2020, and is expected to reach $194.9 billion by 2030, growing at a CAGR of 37.4% from 2021 to 2030.

Hybrid cloud. Cloud providers have added hybrid cloud software to run on standard platforms onsite for high performance and reliability, providing greater flexibility. This is ideal for digital manufacturing systems. For example, AI and ML applications running at the enterprise or cloud build models downloaded to the edge processing running these applications in real time with no dependency on network latency and availability. As the physical controlled and optimized process

This feature originally appeared in Bill Lydon's 7th Annual Industrial Automation & Control Trends Report.

About The Author


Bill Lydon brings more than 10 years of writing and editing expertise to Automation.com, plus more than 25 years of experience designing and applying technology in the automation and controls industry. Lydon started his career as a designer of computer-based machine tool controls; in other positions, he applied programmable logic controllers (PLCs) and process control technology. Working at a large company, Lydon served a two-year stint as part of a five-person task group, that designed a new generation building automation system including controllers, networking and supervisory and control software. He also designed software for chiller and boiler plant optimization. Bill was product manager for a multimillion-dollar controls and automation product line and later cofounder and president of an industrial control software company.


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