What is Internet of Things?
The “Internet of Things” refers to the concept that the Internet is no longer just a global network for people to communicate with one another using computers, but it is also a platform for devices to communicate electronically with the world around them. The result is a world that is alive with information as data flows from one device to another and is shared and reused for a multitude of purposes. Harnessing the potential of all of this data for economic and social good will be one of the primary challenges and opportunities of the coming decades
IoT systems allow users to achieve deeper automation, analysis, and integration within a system. They improve the reach of these areas and their accuracy. IoT utilizes existing and emerging technology for sensing, networking, and robotics. IoT exploits recent advances in software, falling hardware prices, and modern attitudes towards technology. Its new and advanced elements bring major changes in the delivery of products, goods, and services; and the social, economic, and political impact of those changes
What Exactly Is the IIoT?
Industry experts and market analysts define the IIoT.
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“The Industrial Internet of Things (IIoT) is the next wave of innovation impacting the way the world connects and optimizes machines. The IIoT, through the use of sensors, advanced analytics and intelligent decision making, will profoundly transform the way field assets connect and communicate with the enterprise.”
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“Leading O&G companies are building an infrastructure where sensors, data management, advanced analytics and automation are being used to unlock production, reduce operating costs and optimize assets.”
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“The Industrial Internet, a connected network of intelligent machines working the way they are intended, will transform business as dramatically as the consumer Internet has changed our lives.”
Another way to define the IIoT is to look at industrial network in the form of layers shown in Figure
At the bottom of the stack are the devices (systems) on the factory or process floor. These can be field sensors, controllers, or PCs, and all of these hardware systems can include (or not) aspects of hardware security. These end devices must have useful data to communicate and are generally connected to communication hubs, gateways, and switches so that the data is put in the cloud (or an intranet) as big data.
Once this data is out “there,” different analytics and optimization software can be developed to optimize the manufacturing assets for a myriad assortment of tasks: system uptime, scheduled maintenance, power efficiency, and more efficient resource utilization.
But that is not all. The IIoT promises that this data can be integrated within the manufacturer’s ERP and CRM software. The manufacturing operation can not only be used to plan and cost out manufacturing processes more efficiently, but even to use customer information to change assembly lines and process parameters in real time.
The bottom two stacks in Figure impact the design of system hardware, and the top layers affect software development and integration.
If industrial market segments have been deploying automation for decades, what makes IIoT different?
There really are only three main distinctions: ubiquitous sensing, advanced analytics, and IT methodologies. Each of these is described briefly below.
1.Ubiquitous Sensing
Analogous to the broader IoT space, which envisions ubiquitous connectivity of intelligent devices,
Industrial IoT is characterized by ubiquity of connected sensors and actuators. Where traditional
automation employed sensors and actuators primarily for the most critical elements of control, IIoT
includes sensors and actuators for facility operations, machine health, ambient conditions, quality, and a variety of other functions. Virtually everything that can be measured and controlled within the
industrial context is fair game for IIoT. The ubiquity of sensing and control is key to enabling the next
cornerstone of IIoT – advanced analytics.
2.Advanced Analytics
Advanced analytics enables the IIoT system to realize higher levels of operational efficiency by extracting meaning from a vast array of deployed sensors. Similar to cloud datacenters, where sensors data is used to optimize virtually every aspect of operational efficiency, smart factories and other IIoT applications utilize analytics to improve uptime, optimize asset utilization, and reduce overhead costs. Improved operational efficiency provided by advanced analytics is the primary motivator for IIoT adoption today.
3.IT methodologies
The third defining characteristic of Industrial Internet of Things is the transformation of traditional automation techniques to utilize technologies that have been historically associated with information technology. This transformation has three key benefits. First, migration to IT technology enables the IIoT operator to utilize the large IT talent pool to deploy, monitor, and optimize their IIoT application. Second, standardization around IT practices helps to eliminate islands of proprietary equipment within the installation and provide tighter integration between the control domain and the operations domain. Lastly, adoption of IT methodologies enables IIoT companies to leverage the large existing base of IT hardware and software solutions when appropriate. Each of these benefits offers significant potential for capital and operational savings.
The Benefits of the IIoT
We need to be very clear about why everyone wants to make the IIoT viable. The overriding answer is systems optimization, and all the benefits that optimization usually brings. These benefits can be broken down into three primary buckets: asset, process, and business optimisation addressed in that order. It is easier to optimize a motor than to optimize a whole drilling operation which, in turn, is easier to optimize than the many manufacturing lines of a large enterprise
Asset Optimization
The first level of analysis and interaction occurs at the edge. The data is collected from a sensor, perhaps a wind turbine sensor, or a motor encoder, or the vibration signature. This data is processed locally to help operators understand how to adjust parameters for the highest efficiency, or for an early indication of a potential failure.
Process Optimization
The next level of analysis happens at the control room. Here sensor data from multiple end devices and even multiple assembly lines is aggregated to enable more intelligent decisions that could positively impact factory efficiency and multiple processes. For example, with more accurate sensor data, a control room can make smarter decisions about when end devices should be idle or asleep. One positive benefit is better hardware usage and, probably, a reduced power profile.
Business Optimization
There is a common denominator evolving from this discussion: more data and smart data usage. We are all familiar with how data can positively impact asset usage and process operations. But the IIoT envisions not just an increase in data collection and analysis at the first two stages. The IIoT also promises to integrate the process data with the enterprise data; thus, enabling really interesting, smarter management decisions that, so far, have not been made.
Consider, for example, an assembly line that can now be programmed to manufacture higher volumes of a product enjoying a market explosion, or programmed to bypass sub assemblies with diminishing market value. Even a combination of operating and financial data might be used to provide more insight to the CFO office.
Applications of IIot
- Digital/connected factory
- Facility management
- Production flow monitoring
- Inventory management
- Plant Safety and Security
- Quality control
- Packaging Optimization
- Logistics and Supply Chain Optimization
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