The global Industrial Internet of Things (IIoT) market is anticipated to reach more than 771 billion by 2026. There are many reasons why industries worldwide are looking for new business models to construct a connected enterprise for merging their operational and information departments. 

The IIoT is transforming traditional, linear manufacturing supply chains into dynamic, interconnected systems that can more readily incorporate ecosystem partners. A bit fuzzy on how IoT is revolutionizing our industrial world? 

3 PRACTICAL IIOT EXAMPLES 

1
LOCAL GOVERNMENT

US municipality has implemented smart meter monitoring for all the town’s residential and commercial water meters. The project involved placing water meter sensors on 66,000 devices that used to be manually read and recorded.

RESULT

The US municipality that switched to smart meters for its water usage monitoring saw immediate and sustained savings. Its data collection process evolved from a manually intensive process (in which field technicians traveled to every meter) to one where meter readings were automatically recorded and transmitted to a central database. This saves a lot of money, both in work-hours and in field equipment, such as trucks. The town is projecting a total savings of $28 million and a net savings of approximately $10 million over the lifetime of the initiative.

The indirect savings came when the organization was able to make a fundamental shift to a proactive service-oriented organization. Now the town can identify issues within hours, rather than weeks or months. With better and more accurate data, the town proactively reaches out to households to mitigate overuse or unexpected fees. The billing and management teams have shifted from an internal reporting organization to a customer-facing hub that provides residents a markedly better experience.

2
UTILITY COMPANY

A US oil and gas company is optimizing oilfield production with the Internet of Things. In this IoT example, the company is using sensors to measure oil extraction rates, temperatures, well pressure and more for 21,000 wells.

RESULT

The oil and gas company is now able to monitor the performance of oil wells at the end of every day or week. This allows it to identify opportunities for improvement (such as increasing production levels) and areas of potential concern. Ultimately, the company can take this information and disseminate it to field crews to make adjustments or repairs. The result is reduced downtime and increased production levels. The company estimates that it loses $500 for every hour that a single oil well is not in operation. After analyzing the initial impacts of sensor deployment, the organization estimates that quicker oil well repairs saves approximately $145,000 in cost avoidance per month per field.

3
MANUFACTURING COMPANY

An international truck manufacturer created a new revenue stream by outfitting trucks with sensors for predictive maintenance. The system automatically schedules repairs when needed and orders the required parts for the repair. More than 100,000 trucks have been outfitted with devices that transmit more than 10,000 data points a day for each truck.

RESULT

This is a mature example of using sensor data. Sensors in the trucks, combined with predictive models, detect when a mechanical failure is likely to occur. When this happens, the system schedules a maintenance appointment for the truck based on the truck’s route and optimized for scheduled delivery times. Further, the system orders and ships the appropriate parts to the identified service center, and then notifies technicians about what needs to be fixed. The result is an interconnected web of sensors and operational systems that communicate to save time and money across the operation.

In each of these cases, bringing the Internet of Things and industrial-grade analytics together yielded significant and persistent business enhancements.

As you can see, IIoT technologies help to change the way that products are made and delivered, increasing efficiency, ensuring better safety for human operators, and, in some cases, saving millions of dollars.  (Source credit: https://www.sas.com/en_us/insights)

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