Using The Industrial Internet of Things to Transform Heavy Industries
Two or three decades ago, it was a privilege to connect a work computer to the Internet, and it was only possible through wired connections. During its early days, the Internet was purely for emails and work-related activities.
Today, this has changed and the number of internet-connected devices is more than the entire human population. Technologies such as the Internet of Things (IoT) and Industrial Internet of Things (IIoT) are seeing more and more non-computing devices joining the internet.
The number of connected devices is increasing and expected to pass the 20-billion mark by 2020, according to Gartner Research.
Today, a majority of business leaders believe that the IIoT technology will be a critical component for success in a wide range of industries.
What is IIoT and how does it work
IIoT is a technology that uses sensors, the Internet, and data analysis tools to enhance engineering and industrial processes. The technology employs a network of different sensors to collect data from industrial machines and facilities, which is then uploaded to a cloud platform for analysis. Data analytics, artificial intelligence, and other digital tools turn the sensor data into valuable insights about the status and performance of the industrial facilities.
An IIoT ecosystem consists of a diverse range of hardware and software technologies, as well as the internet that enables connecting the various components to the data storage and analysis platforms. Using technologies such as data analytics and artificial intelligence, the platforms can determine if the monitored assets or processes are operating within the prescribed limits. It also identifies a wide range of performance issues, defects, impending failures and more.
This helps the manufacturing or heavy engineering firms to improve efficiency, safety, compliance, and productivity while cutting wastage and operational costs. One area that IIoT helps a lot is enabling better predictive maintenance, preventing abrupt equipment failures and shutdowns.
How does IIoT differ from IoT
Industrial Internet of Things and traditional IoT have some similarities and differences. Each technology relies on sensors, the Internet, and data analysis tools to collect, extract, and present valuable information about physical equipment or the environment. However, IoT focuses more on providing user comfort and convenience through connected appliances in office and domestic settings. On the other hand, IIoT applies the technologies to the industries such as manufacturing, utility and heavy engineering where it helps to improve productivity, efficiency, and safety while reducing costs and resource wastage.
Because of their impact, the IIoT applications are costly. They also have additional enhancements that make them more accurate, secure, scalable, programmable and interoperable. This is important in preventing malfunctions of critical industrial equipment which can lead to huge losses in the event of wrong data or cyberattacks. Also, they are more serviceable, relies on low latency networks while some deployments include automation options.
Key components of an IIoT system
An IIoT ecosystem is a complex integration of different technologies that support automatic, real-time interaction between the physical assets and digital tools.
A typical system comprises of
- Sensors and controllers
2. Communication networks and infrastructure
3. Data collection platform or device
4. Digital analysis and representation tools
The sensors collect information from the equipment, machines or environment and then transmit to a processing platform. These are usually electronics devices such as optical, vibration, temperature, magnetic, proximity sensors, etc. In a typical deployment, each sensor has its unique identifier that enables teams to determine its exact location and equipment.
Communication and data infrastructure manages the transmission and processing of data and control signals. This comprises of the gateways, wired and wireless networks, internet technologies, storage and processing platform such as an on-premise data center or a highly scalable cloud-based system.
The intelligent software tools extract and analyze the sensor data and present useful information to the stakeholders in the correct format. Some advanced systems incorporate automatic remedial actions such as making necessary optimization adjustments or shutting down malfunctioning equipment.
Generally, implementing a successive IIoT project requires proper selection of the sensors, platform, connectivity technologies, and analysis tools. Most often, these vary from one industry to the other depending on the objective, equipment models, applications and environment.
Potential of IIoT
Today, inefficiencies, breakdowns, and a waste of resources are preventing engineering firms from delivering quality products and services within the timelines and budgets. However, they can address most of these challenges by deploying digital technologies such as IIoT and machine learning.
The IIoT technology is making pumps, HVACs, conveyor belts, mining equipment, trucks, and other heavy industrial assets in an engineering environment smarter. However, the systems for different industries may differ in complexity and how they respond after detecting an issue. For example, some systems will send alerts when there are problems while an automated deployment will send an alert and automatically take a preprogrammed action, such as shutting down a pump, adjusting speed or disconnecting power. This prevents damage or other undesired consequences such as spillage, overheating, explosion, etc.
Typical applications of IIoT in industries
- In industries such as steel manufacturing, maintenance is critical in reducing failures and production costs. However, with equipment maintenance accounting for about 15% of the production costs, it is important to do it at the right time. Servicing the equipment too early, when it is not necessary, maybe a waste of money. On the other hand, waiting too long could result in expensive repairs and even shutdowns, hence the need for proper timing which IIoT can offer.
- Adding sensors to the excavators, crushing machines, cranes, grinding mills, conveyor belts, and other equipment in the cement manufacturing industry provides an opportunity to gather a wide range of valuable data. Monitoring the equipment such as trucks in the quarries helps to determine their locations, usage patterns, operating hours, fuel consumption and maintenance requirements.
For example, the Rio Tinto mining company uses Caterpillar and Komatsu autonomous haul trucks for the huge open-pit mine environments. Since truck maintenance service centers are usually far from the mines, a breakdown can lead to lengthy shutdowns. However, adding the IIoT sensors to the trucks makes it easier for the company to monitor them and address any performance issues in good time. The use of these autonomous trucks has seen an increase in efficiency, production and safety in addition to a reduction of maintenance and operational costs. - In the oil and gas industry, the companies are adding the sensors to various components in the wells, pipelines, production facilities, storage tanks, and other areas. This helps them to monitor the operations, pumps, pipelines, turbines, valves and other assets. In addition to sending alerts, the IIoT technology can activate automatic remedial actions such as closing valves or, shutting down pumps upon detecting a life-threatening condition such as an explosion.
Benefits of IIoT in engineering and manufacturing
IIoT benefits both the customers and the manufactures or engineering firms. It enables remote monitoring and control of the machinery, improving maintenance and productivity, and costs. The embedded sensors collect the critical data from the assets, including from the hard-to-reach and invisible locations, without interfering with the operation of the equipment.
This enables managers and maintenance personnel to gain insights into the various assets and environmental conditions, allowing them to make better data-driven optimization and maintenance decisions.
Other benefits of IIoT
- Providing visibility into the facility processes, assets, and resource usage, as well as environmental conditions such as contamination, temperature, humidity, and others.
- Enabling remote monitoring of assets and processes. This enables the company to easily assess their facilities and equipment and make faster and better data-driven maintenance and optimization decisions.
- Improving predictive maintenance activities since the technical people can identify and address potential failures before they occur. Proper maintenance extends the service life of the equipment while reducing the frequency of unscheduled shutdowns.
- Timely and accurate data enables the company to maximize the utilization of available assets and resources. It also helps to identify energy savings and other cost-cutting opportunities.
- Monitoring the facilities remotely saves on inspection costs and lost production when there is a need to stop some operations to perform the routine checks. By eliminating the physical presence of the employees, the firm can improve safety and cut on insurance costs.
Challenges when deploying IIoT
An IIoT ecosystem comprises of a combination of different hardware, software, and processes. These include industrial machinery, communication networks, sensors, intelligent data analysis, automation tools, and more. A perfect blend of these technologies ensures a reliable interaction between physical assets and digital tools. However, companies may face unique challenges that range from non-standard networks and protocols to secure and different data formats.
Lack of common standards
With a diverse range of non-standard technologies, it becomes a challenge integrating, working with or upgrading the different components and systems. The challenge is much bigger when connecting thousands of components from different hardware manufacturers and software developers. Also, firms are usually afraid of getting locked to a particular vendor due to incompatibility issues.
High implementation costs
The upfront cost of deploying an IIoT system can be very high, especially for large engineering firms with thousands of different components and processes to monitor. Considering that they have to purchase the hardware, software, analysis tools and other technologies in addition to deploying the right infrastructure, most companies may shy away from implementing the system.
One way of going around this challenge is to implement the IIoT gradually, — starting with the critical areas and scaling the systems as they evaluate the benefits of each deployment. This will also enable the firm to experiment and determine what works and what requires improvement or a different approach.
Insecure devices and networks
Security is a big challenge as hackers continue to target critical connected infrastructure components such as water services, gas pumps, electrical power transmission systems, and others. Insecure devices allow criminals to obtain the commercial intelligence that they can then use for sabotage, service disruption, and downtimes. This can cause huge financial and reputation losses. For example, a criminal can even control the manufacturing process remotely, shut down equipment or drive it in a way that it causes damage to the equipment.
Most IIoT systems suffer from a wide range of threats due to weaknesses and vulnerabilities in the different components and technologies in the ecosystem. Since every component in the hardware, software, protocols, and communication channels is a potential target, the attack surface is wider for IIoT systems.
Also, because of the fragmented devices and nonstandard networks, sensors and applications, protecting every point can be a challenge. The situation is worse in large organizations with hundreds or thousands of different sensors, processes, and networks.
Network connectivity challenges
Building a stable and reliable communication network of the various devices is usually a challenge due to incompatibility and other issues. There are many different types and possible combinations of devices, sensors, and networking technologies. However, without a common standard, connecting the devices can be difficult, especially when there are thousands of sensors spread across different geographical locations.
Potential of bottlenecks increase when there are thousands of devices trying to communicate simultaneously. Furthermore, the sensors produce data in different formats and this may present a problem.
Lack of data analysis tools and skills
As the technology evolves, lack of the right tools with the ability to accurately extract, process and present valuable information from the sensors has been a challenge. Issues such as different formats, unstable networks, and corrupt data increase the risk of incorrect interpretation by the analysis tools.
Also, some legacy data analysis tools can only handle structured data, and in batches. However, some of the IIoT sensors generate nonstandard or unstructured data in real-time and processing this can be a challenge. Today, some developers are building digital tools that support a wider range of data sets and formats, overcoming some of the challenges.
Future of IIoT
Several ongoing developments will provide many opportunities for the engineering and manufacturing sectors. This includes advances in the IIoT hardware and software; cloud computing, connectivity, big data analytics, and artificial intelligence. Although sensors will have more processing power, they will continue to shrink in physical size, become more energy-efficient and less costly.
Widespread implementation of wireless networks such as the 4G LTE and LPWA will provide reliable, faster and better connectivity while the 5G technology is likely to offer more opportunities as it matures.
Integrating technologies such as robots, virtual reality, augmented reality, AI and machine learning and others will provide many more optimization and cost-saving opportunities to the heavy engineering industry.
Besides improving performance, energy and cost savings, the emerging technologies and data from the sensor will allow the technical teams to pinpoint and resolve problems or service the equipment much faster. For instance, combining IIoT and Augmented Reality (AR) provides technicians with average skills with the ability to service or repair complex equipment, even when they are seeing it for the first time.
Conclusion
IIoT is a combination of different technologies that make physical assets and processes intelligently, enabling managers to monitor their conditions in real-time. This enables the companies to capture real-time production data, identify potential or existing defects and inefficiencies, as well as optimization opportunities such as energy-saving and other cost-cutting measures.
The technology has the potential to unlock a wide range of opportunities in equipment performance management, industrial control, optimization, maintenance and other areas that support intelligent manufacturing and engineering practices. Generally, it provides managers with timely and accurate data, enabling them to gain valuable insights about their assets, and consequently make better business and maintenance decisions.
