In large-scale processes such as oil and gas exploration, mining, manufacturing, and energy delivery, many pieces of equipment need to collaborate and coordinate to get things done. Teams of people must communicate with each other constantly to avoid mistakes or accidents. Industrial control systems, in particular supervisory control and data acquisition (SCADA) systems, are an effective tool to coordinate all these machines and people.
SCADA systems comprise machines, controllers, graphical user interfaces, computers, and data networks. The machines come from different manufacturers, so it can be challenging to integrate the data from different sources for analytics. However, the effectiveness of SCADA can be improved with large real-time datasets that enable processes to be fine-tuned.
The Industrial Internet of Things (IIoT), with components like sensors, data storage and integration, data analytics, and machine learning, can be applied to SCADA systems to improve interoperability and coordination among different machines. The sensors collect new data from various equipment and feed the data into the analytics continuously. This way, machine learning algorithms can learn from past data and fine-tune the settings on different machines for thousands or even millions of cycles to reach the optimal point of the entire system. The IIoT also enables remote monitoring of systems located in harsh environments.
The IIoT can be applied to many large systems with multiple components, such as oil rigs, utility grids, wind turbines, airports, and even cities.
Oil and Gas IIoT
The business of extracting and transporting oil and gas can be costly and dangerous. In addition, unexpected equipment breakdowns can lead to expensive delays. With the increasingly strict regulatory environment, monitoring and remote monitoring are crucial to ensuring equipment compliance and reducingcosts. During monitoring, managers need real-time and precise data to make accurate decisions.
Relying on humans for monitoring is not only labor intensive and inefficient but also expensive and dangerous. Satellites enable remote tracking, but they are too complicated and costly. Fortunately, there is a third option: industrial control systems that take advantage of the IIoT’s strengths can reduce costs while increasing effectiveness.
In drilling, the situation becomes more dangerous as the rig digs deeper. Increased pressure on the annulus or the bradenhead can result in a shut-in, increased workovers, or even accidents. The necessity for manual repairs or other workovers to restart work will increase the risk to the crew. And while injections make possible higher extracted material recovery, incorrect injections add costs, cause production losses, and decrease recovery efficiency. Lastly, miscommunication between the control center and the rig can lead to over-or underproduction.
Companies like Ambyint and WellAware offer IIoT solutions for wellhead and pumpjack monitoring, such as determining correct vacuum pressure levels or deciding when and what amount of chemicals or steam should be injected into the well. According to these companies, their IIoT solutions will help reduce expenses and minimize downtime while ensuring worker safety and regulatory compliance.
Larger companies in the sector are also beginning to incorporate IIoT solutions into their operations. For example, Shell has been able to extract 10 percent more oil and 5 percent more gas in its smart oil fields than in its traditional fields. In addition to enabling remote monitoring by linking high-tech wells with fiber-optic cables, Shell recently launched a digital twin initiative for one of its offshore rigs in the southern North Sea.
In another case, the Danish rig contractor Maersk Drilling has partnered with Siemens to create a digital twin for each of its hundred-plus key equipment assets. Using the data streaming from the IIoT sensors on these assets, Maersk schedules predictive maintenance, enabling the company to reduce downtime and maintenance costs by 20 percent.
The IIoT is also proving a boon for pipeline management, particularly for addressing pipeline leakage. Businesses are relying on IIoT sensors to monitor the thickness, temperature and erosion of pipes and wells. The data thus gathered makes it possible to detect and prevent equipment failure or gas leaks by proactively scheduling maintenance or repairs. And with such a system in place, deploying employees to handle repairs becomes more effective. Taking away unnecessary inspections and maintenance also reduces the risk of workplace injury. According to Bain & Company, proper analytics can potentially improve production by 6 to 8 percent. Relying on IIoT connectivity to track ships and fleets during cargo shipping can optimize fleet movement and energy consumption.
Utility Grid IIoT
Major utility companies in the U.S. are spending tens of billions of dollars annually to upgrade aging grids and make them smarter. Smart grids can detect, prevent and even predict outages more quickly. When an outage does occur, intelligent grids can identify and isolate it so that it does not escalate. They can also restore electricity after disturbances more rapidly, minimizing downtime. In addition, smart grids can balance energy consumption and peak demand. Moreover, smart grids can adapt to regional events, such as drought, wildfires and earthquakes, adjusting output to meet specific demands.
For a grid to become smart, it needs data from its infrastructure and endusers for analytics and inference. The IIoT, with its sensors and prowess for analytics, is a perfect fit for the job.
Among the many examples of the IIoT’s application to utility grids is Duke Energy’s development of a smart grid. The Florida-based utility company’s grid can detect and isolate a problem and restore power via rerouting automatically.
In addition, Pacific Gas and Electric (PG&E) is testing the use of drones to monitor electric infrastructure in remote places, potentially reducing risk to its employees. The company is also testing gas sensors that will be used to detect gas line leaks.
The UK’s National Grid is using IIoT technology to aggregate energy consumption, so the energy supply can ramp up or down to meet demand. The up or down adjustments mean the grid can respond to demand more quickly, help consumers manage their consumption, and free up capacity. A UK power and gas supplier, E.ON, is applying IIoT technology to its wind farms to enable more efficient management of the infrastructure.
Lastly, GE Digital’s Predix Asset Performance Management software is being used in multiple power plants. By integrating the data from sensors placed on key infrastructure, the software can perform analytics that will help optimize operational efficiency.
Wind Turbines IIoT
To harvest the largest amount of energy, wind farms must be located in windy areas. But locating them in such places also means that wind turbines, which cost more than one million dollars each, are vulnerable to severe disturbances. For example, the wind farm in the North Sea has been losing so many turbines that engineers have had to refit all 206 units.
An EU-sponsored initiative, ROMEO, which represents “reliable operations, maintenance decision tools and strategies for high levelized cost of electricity/energy,” aims to optimize turbine performance while reducing attrition by using the IIoT, predictive maintenance, and cloud computing.
Under the initiative’s pilot test program, turbines on two wind farms in the UK and one offshore wind farm in Germany will be outfitted with power-conditioning technology and nearly 1,000 sensors. These sensors will include those serving as actuators, integrating strain gauges, and bearing monitors. The sensors will stream data to the cloud so that it can be analyzed. Analytics will enable the detection, diagnosis and prognosis of faults in the turbine components to maximize turbine lifespan and minimize operation and maintenance costs.
Siemens is also using IIoT technology to monitor the health of wind turbines remotely and enable more real-time control of the turbines. For example, during a storm, the control system can adjust the turbines to maximize energy harvesting and balance wind load across the turbines. In addition, analytics will enable predictive maintenance of the machines.
Airports IIoT
Airports are large and complex systems that can be chaotic and stressful to many travelers. Like other multicomponent systems, airports can benefit from the application of IIoT technologies.
For example, making passenger check-in part of the IIoT can automate this activity, saving time for customers and costs for airlines. Bluetooth beacons, nearfield communication (NFC) tags, Wi-Fi, and geolocation can help passengers navigate the airport more easily. For example, the Helsinki Airport prevents bottlenecks and shortens passenger lines with Wi-Fi and iBeacons to track passengers and offer location-based assistance.
Similarly, the Miami Airport deploys a network of beacons and a mobile app to provide personalized service at various airport terminals and shops. The Birmingham Airport in the UK makes use of IIoT connectivity to measure and predict waiting times, while Denmark’s Billund Airport puts IIoT components to work to measure passenger flows, lines, and time spent in its parking lots. The London City Airport is also deploying IIoT technology to monitor passenger flow. Turkish Airlines’ customers can find popular books to enjoy in the airport lounge, thanks to the airline’s use of iBeacon technology.
Because airports are high-value targets, those responsible for their security are looking to the IIoT, with the Dubai International Airport, for example, automating passenger identification at customs. The IIoT also plays a role in the flight’s onboard, landing, and luggage claim stages. For example, IIoT connectivity assists Lufthansa passengers in tracking their luggage.
While the many applications of the IIoT are passenger focused, the technology’s strengths can also play a role in increasing revenue and reducing operating costs. For example, Rolls-Royce is working with Microsoft to manage multiple aspects of flights, such as plane engine health, air traffic, rerouting, and fuel use. In addition, airlines like Delta and KLM are using the IIoT to improve airplane maintenance.
Smart Cities IIoT
Cities are like airports scaled up in size and complexity. Capitalizing on what the IIoT and its connections enable, city planners can create a digital twin of a city. Planners can then model different scenarios to find the optimal solutions for a variety of challenges facing a city.
For example, with their city’s digital twin, Singapore planners could analyze the possible outcomes of flooding, energy consumption, traffic jams, and even disease outbreaks. The digital twin can also help the government make buildings greener by finding the best location for solar panels, water-retention features, sewage systems, and emergency exits and routes. In addition, the digital twin can help planners decide where to install ramps for the elderly or disabled.
The IIoT is also helping make cities safer by offering the connectivity for establishing restrictions for certain areas, for example, or for maintenance surveillance of sensitive locations. Lastly, the IIoT can help reduce the energy it takes to light and air-condition buildings.
Conclusion
The implementation of the IIoT in large complex systems is only the beginning of this technology’s applications. As the cost of sensors and data storage goes down, and the performance of data analytics goes up, there will be broader and more creative IIoT applications. Also, the advent of the 5G network will further enable processes that can benefit from real-time decision-making, such as a network of autonomous vehicles or manufacturing processes that require a high level of precision.
In addition, once high-value networks of machines or processes, such as oil fields, utility grids, airports, military bases, and cities, become hyper-connected via the IIoT, data and personnel security will become critical. New emerging technologies such as blockchain may provide a way to address such concerns. Finally, the IIoT is expected to eventually replace SCADA. But because SCADA has been widely used and its standards have been established, the replacement may take some time.