The post How to Succeed with the Industrial Internet of Things first appeared on the ISA Interchange blog site.
More than just hype, the Industrial Internet of Things (IIoT) offers significant potential value for manufacturers and other industrial organizations. The key is to create a long-term vision with an associated value proposition, identify the right applications to target initially, and employ the appropriate operational and information technologies, much of which is likely either already in place or readily available.
The Industrial Internet of Things encompasses four main components:
Industrial companies have pursued horizontal and vertical connectivity within their operations for some time now in their ongoing efforts to improve performance and achieve operational excellence. Most existing sensor and actuator points in an industrial automation system are there to support process or production control, safety, and regulatory compliance. However, in the past, adding sensors to support condition-based maintenance or other noncontrol uses was done infrequently due in part to the costs of adding the sensors and associated software systems to existing hierarchical control systems. But new approaches, including technologies such as less expensive strap-on sensors, Wi-Fi connectivity, predictive analytics, and cloud computing can make condition-based maintenance and other “connected world” applications practical. ARC and other industry observers and participants believe that these can enable new levels of performance and new business models.
Industrial companies can use information from these connected entities to lower costs, optimize processes, and execute efficiently. Intelligent connected devices and machines can help improve performance and reduce downtime through remote diagnostics, troubleshooting, and condition monitoring capabilities. These support predictive maintenance approaches that minimize unplanned downtime, improve maintenance productivity and effectiveness, and enable assets to operate in an optimal manner. This—combined with the ability of authorized parties (both internal and external to the organization) to remotely access data from appropriate Internet-connected devices, machines, and other plant equipment—can deliver incremental business benefits.
Everyone understands that unplanned downtime is highly detrimental to production performance. Incrementally improving this metric through remote asset monitoring by internal or external service and operations personnel provides business value that can help industrial organizations justify adoption of the IoT and connected devices. Connected devices can help reduce downtime through remote monitoring of sensor data like vibration and temperature for predictive maintenance. For example, remote service personnel could identify specific problems and potentially perform configuration fixes or update software or firmware without having to travel to the facility, saving time and travel expense, plus the need to involve typically time-strapped on-site technicians.
The IIoT and its potential to transform production operations is one of the hottest current topics in manufacturing. Along with Industrie 4.0, information technology (IT)/operational technology (OT) convergence, and smart manufacturing, the IIoT is cited as the latest means for making manufacturing production more flexible, more cost effective, and more responsive to changes in market demand. Not surprisingly, numerous market forecasts attempt to quantify the potential inherent in the IIoT, promising that billions of “things” or devices, worth trillions of dollars, will soon be connected.
Needed technologies are already available and require no substantial technological breakthroughs. Well-thought-out reference architectures have been created, and compelling use cases are being developed. Techniques for adding IIoT’s “digital umbilical cord” capability to existing industrial systems—allowing companies to securely supply asset performance information to the asset manufacturers and others—are coming to market. What is lacking is broad recognition of what has become possible and the vision to use these new technologies for business value.
The IIoT architecture builds upon current and emerging technologies, such as mobile and intelligent devices, wired and wireless networks, cloud computing, big data, analytics, and visualization tools. With most of the technological components already available, concerns over cybersecurity, technology standardization, and intellectual property ownership remain the most prominent potential obstacles.
The four main parts of any IIoT system are intelligent assets, a data communications infrastructure, analytics and applications to interpret and act on the data, and people. Intelligent assets include machines or other assets enabled with sensors, processors, memory, and communications capability. In certain cases, these assets may have an associated virtual entity or support software-defined configuration and performance. Intelligent assets generate more data and share information across the value chain. Some intelligent assets will eventually be self-aware or operate autonomously.
In addition to the Internet, data communications between these assets and other entities will often leverage network technologies such as LTE, ZigBee, Wi-Fi, IEEE 802.15-4, and cloud-based computing infrastructure with the storage to accommodate big data requirements.
Powerful analytics and related software will enhance asset optimization as well as system optimization. Predictive analytics will be deployed to reduce unplanned downtime. Newly available information generated by these tools will lead to new, transformative business models supported by new applications. Instead of offering physical products for sale, companies will increasingly offer products “as a service.”
People will participate by having access to much more data, better analytics tools, and better information, and will increasingly make decisions based on the analysis generated by these resources. Quantified decision making will become much more common, and “intelligent” information will appear when and where people need it. But people will also continue to become better connected to others and to machines and systems through social and mobile tools and applications.
At the OT level, a large number and variety of difference sensors, intelligent field devices, controllers, systems, mobility devices, application software, networking, and security components come into play relative to the IIoT. Although these come in a wide variety of “shapes and sizes,” all feature some degree of built-in intelligence, self-diagnosis capabilities, connectivity, and support for analytics. Examples include:
Certain types of industrial equipment, machinery, and other assets used in operations are already “connected” and remotely monitored or operated examples of the IIoT. A leading example is the heavy mobile machines used in agriculture or mining. Many large mining and earth-moving machines, as well as autonomous or semi-autonomous harvesters and other machines, are already actors in the IIoT. A second type is large rotating machines that generate electric power, lift, or thrust. This type includes jet engines, hydraulic pumps, and power generation turbines. A third type is machines and equipment used to produce commercial products. This category includes a great variety of equipment such as pumps in refineries or other continuous processing plants; robots in automotive plants; retorts in thermal processing of low-acid foods in cans, pouches, jars, or bowls; and mixers, tanks, and compressors. Industrial companies can improve operations by adding intelligence, sensors, and communications to these machines and connecting them to new applications and analytics as part of the Internet of Things.
How can industrial companies help their operations equipment vendors do a better job for them? One possibility is to share in-service performance data in real time. Makers of heavy mobile machines for mining and agriculture already incorporate sensors, intelligence, and communications technology in their machines to monitor performance in the field. Makers of pumps, compressors, robots, turbines, and other industrial equipment used in factories and industrial plants also want in-service information from the products they manufacture to use as industrial assets.
A real-time feed of select machine sensor data lets the vendor monitor and analyze machine performance, suggest alternative operating parameters, improve its product designs, predict failures in advance, reduce warranty support costs, provide better maintenance and support services, and more. By monitoring a large set of its deployed products, an asset vendor may discover new patterns and failure modes that individual users would not be able to identify.
How can industrial companies share in-service performance data safely and securely with trusted vendors? In certain applications, it is possible to add low-cost sensors that collect performance data and communicate this through plant Wi-Fi networks. In the not-too-distant future, equipment will come with the necessary sensors, intelligence, and communications capability built in. Until then, a sensible approach to deploying this “connected asset value chain” is to leverage the existing data infrastructure and add a secure cloud-based system to share selected performance data with vendors and service providers.
Because many leading automation suppliers have offered the service of remotely connecting to and monitoring the control systems installed in their customers’ plants to maintain or improve performance and availability levels, the argument could be made that these types of remote services are early examples of the IIoT. Often, the remote monitoring extends beyond the control system (which is largely invisible to users as an industrial asset) to smart, connected sensors and other automation-related devices. In many respects, this indeed is very similar to the type of remote supplier service for industrial assets described above. Both can involve real-time data and sophisticated analytics, and both raise potential security concerns. Even though this early example of the connected asset value chain almost never employed Internet technology, a broad view of the IIoT encompasses all relevant forms of connectivity.
Many industrial manufacturers have devoted significant resources over the years to internal operational improvements via performance monitoring, pursuit of best practices, overall equipment effectiveness, and similar pursuits. For today’s high-performing manufacturing firms, improving the profitability and revenue potential of their service operations once the product is shipped to the customer frequently represents a new revenue opportunity.
GE, for example, has been very public about reporting the benefits of connected products, including the company’s ability to remotely resolve 53 percent of service issues in its power and water business. Manufacturers in general can use the IIoT to proactively monitor products in the field and use that information to reduce mean time to repair and the number and frequency of technician dispatches.
The IIoT promises improved performance of manufacturers’ service operations through remote connectivity, as well as incremental connectivity-based revenue streams that are entirely new opportunities. Clearly, the value proposition for the IIoT extends beyond simple connectivity into the ability to build new products and services using that connectivity as a base.
Service capabilities increasingly are a means for manufacturers to achieve competitive differentiation. Adoption of IIoT-based device connectivity enables predictive maintenance, continuous uptime, rapid service response, and the opportunity to offer incremental, revenue-producing products and services.
Providers of IIoT-connected devices will also gain competitive advantage by delivering incremental value, differentiating products from competitors, and fostering new revenue streams. Manufacturers that offer connected products will be able to remotely access the installed base and provide a direct path to maintaining customer satisfaction, reducing service costs, improving profitability of service and warranty management, and delivering products as a service. The shift to the product-service hybrid model will affect machine manufacturers in several important ways. There will be new product hardware and software requirements, the need for a more data- and information-intensive operation, new service delivery metrics and models, new required competencies and expertise, and a different selling model.
To better serve their customers, manufacturers of industrial equipment, systems, and other industrial assets want access to in-service operating data from their products. Today, operating assets often have at least some associated sensors and operating information (e.g., cycle count). But typically, this information is read only by a programmable logic controller (PLC), distributed control system (DCS), or plant floor application such as manufacturing intelligence software, asset-based historians, HMI, or a manufacturing execution system (MES). These applications may also provide a basic hierarchical plant model that names, classifies, and locates the asset (i.e., “Pump P-004”). If other applications or systems need the information, it is shared via the application’s program interface and possibly some intermediate software.
By adding cloud-based solutions, this existing information infrastructure could become the basis for securely sharing certain information with the asset vendors. Companies can take advantage of public cloud services such as Microsoft Windows Azure. These can be a secure private computing platform for software-as-a-service applications that could help ensure that only certain information is shared with specific trusted vendors who can subscribe, subject to constraints and conditions, and possibly payment of service fees. This approach eliminates having to wait for standard ways of doing things to emerge, which in any case, would not likely easily accommodate legacy assets.
The cloud-based solution enables immediate participation in a company’s connected asset value chain. Asset vendors can monitor their products’ real-time performance “in-service,” and act upon the information gathered from these assets to better serve their customers.
Retrofits and upgrades to existing equipment are an ongoing part of manufacturing improvement; one that frequently eliminates the need for costly new installations to meet business objectives. Most customers will not discard an existing installation solely to upgrade connectivity, which is more often implemented as part of a multipurpose replacement.
Being able to retrofit the installed base with connectivity, whether by adding a new module or other communication interface, is important in the manufacturing marketplace. Retrofits allow customers to leave their installations in place while adding incremental connectivity. This is a valuable characteristic given the cost of industrial equipment and production downtime.
There is a huge installed base of unconnected devices throughout industry. Many of these devices can be retrofitted to capture previously isolated data points (“stranded data”), generate incremental performance advantages, or perform remote service.
The retrofit component has a significant impact in both discrete and process manufacturing, since many automation devices can be retrofit for connectivity by adding a new module. PLCs, used almost equally in process and discrete sectors, are a good retrofit example, because many customers want to leave their installed I/O in place. Most PLC designs allow incremental communication modules to be added to existing installations. The use of DIN rail form factors in an increasing number of discrete automation devices makes it relatively easy to add communications for the IIoT. More and more PLC-based controllers also come with Ethernet connectivity built in.
Process manufacturers tend to avoid switching out the installed base, which in some cases has been in their operation for decades. Some manufacturers have certified or validated installations they do not want to jeopardize, while other installations may represent years of continuous improvement efforts and accumulated tribal knowledge. For these manufacturers, it is far easier to retrofit existing equipment with connectivity, sensing, data acquisition, and other peripheral components of the IIoT rather than perform a complete tear out.
The plethora of automation and other devices that can potentially connect to the IIoT leaves plenty of room for confusion. Some end user organizations may opt to develop internal management strategies by machine type; others choose different criteria such as geography or supplier. Companies should focus first on connecting the specific types of devices that are core to their schemes for specific operational or asset-management improvements, and then use that knowledge as the foundation to roll out a broader IIoT strategy.
For starters, original equipment manufacturer (OEM) machinery will be one of the earliest and largest IIoT adopters. IIoT offers a significant value proposition in OEM machinery, because it can remotely monitor, diagnose, troubleshoot, update, and cost effectively manage this equipment. All these activities contribute to reducing downtime and maximizing machine performance—core value propositions driving interest in the IIoT.
Logic and motion control devices such as PLCs and drives are at the core of automated OEM machinery. These devices are also where key IIoT components, such as networks and software for design, configuration, optimization, and visualization, interface to the overall machine. Remember, too, that PLCs are not just of concern to discrete manufacturers—they are widely used for logic control in the process manufacturing industries as well in machinery, safety, and other applications. For example, the food and beverage industry is now the largest consumer of PLCs globally (exceeding even automotive manufacturing) due to their use in both packaging and processing machinery. A huge number of drives are likewise shipped every year for use in machinery applications.
In the continuous process and, to a lesser extent, batch manufacturing industries, DCSs are the primary process automation systems applied. Each DCS can contain multiple controllers, HMIs, servers, sensors, and other devices, but our assumption is that DCSs will primarily interface with the IIoT at the system rather than component level.
The network infrastructure for interfacing connected devices is a flash point for IT/OT convergence. As industrial installations increasingly adopt Ethernet and wireless connectivity, control will be shared more and more between enterprise/IT and operations, and both entities will need to contribute to device-level IIoT strategies. This trend will accelerate with IIoT adoption as enterprise systems ranging from maintenance to big data and analytics increasingly need connectivity with industrial devices to achieve desired performance improvements.
Most industrial organizations purchase machinery from a variety of suppliers. In an IIoT context, this could ultimately result in a wide variety of vendor-specific interfaces being installed, resulting in added cost to maintain and update multiple installations. Companies that are considering adopting connected devices or machines and, ultimately, the IIoT, should focus on establishing their own internal, non-vendor-specific standards for network and software interfaces as new connected devices are acquired. Companies are familiar with specifying the types of controllers used in these machines. Now, they need to extend the specifications to include network, software, and IIoT platform interfaces, as well as access control.
Availability of connected industrial devices has skyrocketed as industrial automation applications have increasingly adopted commercial-off-the-shelf- (COTS) based Ethernet and wireless connectivity. In many device categories, virtually all suppliers offer industrial Ethernet or wireless interfaces as either standard or optional equipment. Concurrent with this trend is industrial Ethernet’s continued penetration of the device level and access to the plethora of products formerly served by serial networks. We expect support for COTS-based connectivity, and the associated availability of connected devices, to continue its strong growth.
Some formal and de facto industry standards are already available to consider as part of an IIoT strategy. These include industrial Ethernet protocols, IEEE wireless standards, and software interfaces like OPC-UA, but there will be further developments as the IIoT progresses. Whichever is right for your company, the important point is to begin marshalling a non-vendor-specific device interface strategy in anticipation of an increasing flood of connected devices.
In parallel with assembling a business case for IIoT adoption, industrial organizations should review standardization of network and software interfaces for connected devices as well as security and access control practices. This approach can save numerous headaches in the long run by reducing the number of operational variables and reducing or eliminating the need to maintain and update disparate technologies.
Companies should take the following actions regarding IIoT-specific device interface strategies:
Chantal Polsonetti is vice president, advisory services, for ARC Advisory Group. Polsonetti focuses on the IIoT, industrial Ethernet switches and devices, wireless networks, device networks, and intelligent train control and rail signaling. She also administers the ARC Industrial Internet of Things group on LinkedIn.
A version of this article originally was published at InTech magazine.
Source: ISA News