If you manage factories, airlines, hospitals, or farms, you probably know something about the Internet of Things. If you don’t, your thoughts on the IoT may start and end with wondering why a coffeepot needs to talk to a toaster. But the fact is that the continuing development of precision technologies could dramatically transform our planet’s fundamental infrastructure.
This article describes the types of technologies that can help build precision machines and discusses the benefits of using such machines to enable, for example, precision health care, precision power, and precision farming.
Sensors are decreasing in cost and increasing in variety. Even your cell phone has 12 sensors, including a barometer, accelerometer, thermometer, and proximity detector.
With lower cost, industrial Things will continue to be increasingly instrumented. For example, modern wind turbines have more than 200 sensors. Sensor data available every second, and in some cases many, many times per second, can be connected to public and private cloud services and collected.
Advanced analytic and machine-learning technologies then can be applied. With the knowledge gained, companies that build wind turbines, or those that create farm equipment or blood analyzers, for example, can not only improve the machines’ availability, performance, and security, they also can reduce the cost of delivering the machines.
Machine vs. Nomic Data
Before we discuss the benefits of using precision machines, there is an interesting question of who owns what data: machine maker or machine user?
There are two kinds of data derived from machines like agricultural equipment, compressors, and gene sequencers: machine data and what I call nomic data. A gene sequencer has machine data such as the power level of the laser and the volume of chemical reagents. There is also genomic data — the actual gene sequence.
On farms there are seed spreaders and fertilizer sprayers. Again there is machine data, like speed, oil pressure, and location, as well as agronomic data like the nitrogen level of the soil or the moisture level of the grain.
Should machine users make all machine data available to the builders of machines? On the one hand, clearly the manufacturer can use the data to build more reliable, secure, and performant products.
On the other hand, car manufacturers might not want to share data from the robots used to make the cars, as such information might help outsiders forecast the car company’s quarterly financial results. Semiconductor manufacturers might not want sensitive process data outside of their four walls. Chinese wind turbine companies might not want to send their energy data to a foreign country.
We are only at the beginning of this debate, which promises to be ongoing. But if machine-using enterprises were to find ways to share the data, what benefits would they reap from smarter, more precise machines? Read on to find out.
Lower Consumable Costs
Many machines consume materials during operation — fuel in the case of an airplane, ink for a high-speed printer, chemical reagents in a gene sequencer.
Often, these consumables form a large portion of the operational cost structure. As anyone with an inkjet printer knows, the cost of the printer is not near as much as the cost of the toner cartridge you buy every year before tax day. For a large airline, the single largest operational cost is fuel — in some cases it’s nearly 30% of the flight’s total cost.
In the railroad business, New York Air Brake has engineered a product to help operate trains more precisely. Called LEADER, it’s being used by railroad operator Norfolk Southern, which operates 22,000 route miles in 22 Eastern states. The company attributes a 5% fuel savings to its deployment of LEADER, resulting in not only 10.8 million gallons of diesel fuel saved per year, but also the avoidance of 110,000 metric tons of greenhouse gas emissions.
Leroy Walden at McKenney’s engineered a solution to enable more precise power management at Eglin Air Force Base in Florida. One of the world’s largest military bases, covering more than 700 square miles and including 131 buildings, Eglin received a 2015 energy and water conservation award from the Department of Energy’s Federal Energy Management Program.
The award recognizes Eglin’s innovative approach for combining advanced technologies with common sense to save critical energy resources and reduce utility costs for the base. By integrating direct digital controls, facility sensors, and comprehensive energy analytics, the project saved 181 billion BTUs of electricity and natural gas across all the buildings. That translates to a savings of $3.4 million per year.
For utilities, airlines, or farms, connecting their machines, collecting data and learning from it should improve the precision of their operations. As an example, consider how precision coal-mining machines enable higher output.
Joy Global builds mining machines. One is called a longwall system, composed of the shearer, powered-roof-support system, armored face conveyor, belt conveyor, power supply, monorail, and pump stations. Massive shearers cut coal from a wall face, which falls onto a chain conveyor belt for removal. A typical system can extract 2,200 tons of material per hour, which will fill a 100-ton railcar in less than a minute.
The manufacturer has developed some sophisticated algorithms that, based on mining-nomic data, can predict a roof collapse. A roof collapse is very expensive, as when the roof falls, it covers the walkway and miners have to clear all of the debris. It takes an average of 7 to 10 days to dig out the machine, and the cost of being offline is $15,000 per minute of downtime.
Collection of the data is enabled by the system’s thousands of sensors. They include vibration sensors, which make data available at 10,000Hz — that’s 10,000 times per second — and sensors that measure roof support pump pressure. As of this writing, there have been no roof faults in mines using Joy Global’s longwall systems for more than nine months.
Nick August is a precision farmer in England. He owns August Farms, a family owned farm for more than 70 years. The 1,235-acre farm produces wheat, rapeseed, and peas. Nick estimates that by using precision agricultural machines and a technique referred to as controlled traffic farming and no-till crop establishment, he can reduce fuel consumption from 60 liters per hectare to 5.9 liters per hectare for crop establishment.
But he’s also using various fertilizers and pesticides. While reducing the consumption of these chemicals reduce cost, it also creates a healthier product and does less damage to the environment.
Last year’s derailment of an Amtrak train in Philadelphia left six people dead. It also created chaos on the heavily traveled Northeast corridor the next morning, cutting off all direct rail service between Philadelphia and New York City and causing many other delays up and down the East Coast.
Train operators can be trained on how to operate trains more efficiently. But it’s a short step from there to just having less-fallible computers do it.
This year, the first automated train will run from the north of Australia to Perth to deliver iron ore. Not only will it reduce the railroad’s labor costs, a reduction in human error will result in a safer railroad.
Technology is not only cool, it transforms businesses. Almost everyone is aware that technology companies like Google, Uber, and eBay have reshaped the consumer world, but IoT technology has the potential to do the same for producers and consumers of the machines used in many types of businesses.
For a manufacturer of Things, technology can not only reduce the cost and improve the quality of service, but also deliver new revenue sources. As a consumer of this next generation of Things, your company will be able to use precision machines to deliver higher-quality and lower-cost food, power and water; safer, less-expensive transportation and health care; and much more.
Timothy Chou is a lecturer on cloud computing at Stanford University. He is a former president of Oracle on Demand. For more information about IoT and how it might reshape your business, check out his new book: “Precision: Principles, Practices and Solutions for the Internet of Things” and his online class Precision IoT: The Class.