You already know that IoT (Internet of Things) is a term that identifies items that have enough intelligence and communication abilities to send messages across the internet. Kevin Ashton supposedly coined the phrase "Internet of Things" while working for Procter & Gamble in 1999.
At first, IoT was largely focused on the consumer. The connected home, the connected car, wearables, smart lights are the common examples.
The news media has always told us that Al Gore invented the Internet, but who started the industrial/business version of IoT? Most agree it was the General Electric Company, a pioneer in embracing IoT technologies and applying it to industrial scenarios. They even renamed it, “the Industrial Internet”. Now we are seeing that low cost sensors, wireless connectivity, and sufficient computing power are being implemented in industrial manufacturing at an increasing scale.
General Electric is the most visible leader in the development of IoT applications. They manufacture some extremely expensive and complex industrial products which are now equipped with sensors to generate millions of data elements for analytical purposes. They capture and analyze data to predict failures and schedule maintenance and replace parts. GE is making constant improvements rather than massive disruptive technology change because small cost savings for huge expenditures and expense items add up to massive savings.
Examples of what GE has developed include:
- Thousands of sensors on aircraft engines are being used to identify ways to improve flight patterns, predict maintenance needs, and reduce fuel costs.
- GE designed a software platform for Union Pacific, the largest railroad in the U.S., that gathers crucial information like weather data and track conditions from the sensors placed on the trains and on the tracks themselves. It helps UP improve scheduling, asset utilization, and maintenance requirements.
- Grid IQ Insight helps major utility customers to improve management of the electric grid. It consolidates data from many sources, including sensors, weather monitoring devices, smart meters other intelligent grid power equipment, and even social media content. This platform enables utilities to minimize customer disruption and respond more quickly to outages.
Machine to machine (M2M) is a broad label that can be used to describe any technology that enables networked devices to exchange information and perform actions without the manual assistance of humans.
Moving into the supply chain, let's look at the various transport functions that could benefit from inclusion in the IoT. As RFID is becoming more available at different levels of itemization, the tags need to be read, and the data collected by reading the tags incorporated into messages. Typically those readings are done as items transition from one location to another, or as a person scans items or an area.
But it is conceivable that some of the things in the IoT could include the carrier's truck, the pallet mover, the loading dock, and the shelf on the store floor. With the proper programming these things can be made to trigger events that create documents to update item status. These could include events like change in temperature or G-force in the truck, change in quantity of items at any point in the chain, and inventory counts in real time.
It's interesting to see how the individual pieces of this ongoing puzzle continue to interact and build capability as new functions become available. Feeding the data produced by the IoT into Big Data storage and analysis engines will go a long way toward bringing real time visibility to the entire supply chain. IoT (industrial internet) brings together Mobile, Cloud and Big Data!
So how does the Industrial Internet support predictive maintenance scenarios? It is really about applying IoT technologies such as sensors and analytics to industrial equipment and then being able to process the information coming from the sensors in real time to help identify trends in data and how it is then possible to predict when a component such as a water pump is likely to fail. If you can predict when a component is likely to fail, you can replace a faulty component as part of a predictive maintenance routine and the piece of equipment is less likely to experience any unexpected downtime. So you are selling results not just products? Sounds like SaaS (Software As A Service)?