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What is the Industrial Internet of Things (IIoT)?
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- Automation and Internet Cloud Computing are evolving and merging into a space allowing for Artificial Intelligence or AI programming
- to facilitate improvements in productivity and efficiency with many economic benefits.
- Along with Internet Cloud computing and other advancements with the Internet, we are now in the middle of the next industrial revolution
- mining and turning data into information. This period of evolution is called Industry 4.0
- or the Fourth Industrial Revolution which includes Industrial Internet of Things (IIoT)
- and Digital Transformation mechanisms that facilitate this evolved 4th generation period of Automation.
- In this lesson, we will learn about, “What is the Industrial Internet of Things or IIoT”?
- While the Industrial Internet of Things does fall under the Internet of Things or IoT area of influence,
- the key difference is IIoT concentrates on the connection of machines and devices in industries like manufacturing,
- healthcare, and logistics. IoT is commonly used to define consumer-based devices like Fitbits,
- and a wide range of smart home devices for example refrigerators, ring video doorbells, lighting, thermostats, and alarm systems.
- IIoT is about getting information that every single consumer needs in their hands when they want it
- and Digital transformation is the digitization of a business
- in how we must move to a unified organize data space using the International Society of Automation standard
- for developing an automated interface between enterprise and control systems or ISA 95. ISA 95 essentially provides a hierarchical model for the Enterprise,
- Site, Area, Line, and Cell. Each level of this architecture uses a specific software system
- to gather data for that part of the organization needs, in which creates a problem for communication between these disparate applications.
- With most organizations, the data is not real-time and lacks efficiency
- inhibiting key stakeholders to make informed decisions. IIoT is about making decisions from information received real-time
- and not from a report created from yesterday’s data. The Industrial Internet of Things is all about interconnected instruments,
- sensors, and many other devices that are networked together and communicating with computer-driven industrial applications
- for many manufacturing and energy management areas of business. IIoT is an evolution of a control system
- that allows for a significant improvement in automation by using cloud computing to enhance and optimize process controls.
- Industrial IoT depends on many technologies but the key technologies primarily consist of Artificial intelligence,
- Cybersecurity, Cloud Computing, Edge computing, and Data Mining. Artificial intelligence or AI and machine learning or ML
- are fields that are part of computer science. AI is where intelligent machines are developed and respond like humans
- and ML is where machine learning is a part of AI predicting and a more accurate outcome delivered without programming.
- Cybersecurity technology becomes an important basic platform for IoT and IIoT enabling disconnected machines to physically connect and communicate in a secure method.
- Cloud computing is basically using IT services and the files to be uploaded and downloaded from Internet-based servers
- opposed to using local extranet-connected servers. Edge computing is a distributed computing model
- bringing data storage closer to the location where it is needed and optimizes sensors, industrial computers, and devices
- that are part of the IIoT system for publishing and consuming data for faster processing.
- Data mining and analytics are about collating and examining large amounts of data stored from various parts of the enterprise.
- OK, so why should we go through this somewhat major transformation, and what are the benefits?
- Companies want to be more competitive, increase efficiency with just-in-time manufacturing in meeting higher customer demand
- with better inventory control. We can do all of this
- with the creation of the organizations’ overall automation a digital twin. A digital twin is a virtual representation
- referring to a digital replication of the actual companies’ physical assets, processes in place, automation systems, and devices.
- The twin uses real-time data to enable learning and reasoning for improved decision making.
- The digital twin allows experimentation with new information that is generated by cloud-based AI functions
- without having to shut-down production, or be concerned with personal safety because testing is performed in a virtual space.
- Also, the digital twin could be used as a training ground for new employees without impacting the live system.
- And when comparing IIoT and IoT failures, IIoT create much higher risks than IoT.
- Life-threatening situations or major financial losses could happen from an actual system failure or downtime for example.
- While we may benefit from a long list of benefits through the IIoT transformation, there are some concerns and risks we should be aware of.
- Some of the potential risks of adopting IIoT are expense of the cost of data integration,
- lack of experience, and difficulty of implementation, and the devastating cyber threats.
- Data Integration is one of the biggest obstacles to IIoT implementation. You could be looking at building a system with
- thousands of existing connected sensors and devices, adding new equipment and software systems,
- and interfacing legacy equipment to communicate using standard IIoT protocols. There is a high cost of integration preparing for IIoT,
- requiring new software, hardware, and equipment. You will need to consider the costs of associated training your existing workforce
- and hiring new staff and the time needed to get workers productive.
- And the lack of expertise with integrating IIoT requiring automation companies to be fully experienced
- with an organizations layers of systems starting with the plant floor transmitters,
- process PLCs, operation HMI and SCADA, reporting based on Database Administration,
- manufacturing execution systems or MES for warehouse control and Enterprise Resource Planning or ERP or accounting systems.
- Now integrators are required to have expertise in machine learning, data science, and real-time analytics.
- In the long term, IIoT could more than pay for itself, but many organizations are still justifiably concerned about investing so much in IIoT.
- On the bright side, the benefits of IIoT in manufacturing,
- pharmaceuticals, agriculture, mining, Oil and Gas, and retail are gaining ground
- and many companies are embracing this new paradigm for solutions in optimizing operations and personnel productivity.
- Many manufacturers have already achieved process performance and have reductions in downtime.
- And while manufacturing is certainly leading the way with IIoT adoption, other industries are becoming open to the idea of embracing IIoT for example.
- This concludes the video, “What is the Industrial Internet of Things IIoT?”
- If you have any questions about the “Industrial Internet of Things” in general feel free to add them in the comment section.
- We read each and every comment and reply to it in less than 24 hours.
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