How the Internet of Things Is Improving Predictive Maintenance

Todd Henderson
Todd Henderson | 3 minute read

At Losant, we often hear that manufacturers are looking to help control unpredictable overhead costs that are largely a result of maintenance and repairs for expensive machinery. Fortunately, Internet of Things (IoT) technology is helping to bring predictive maintenance projects into reality as well as drastically improve their effectiveness.

“Up to 90% of the maintenance perform is conducted on a reactive rather than proactive basis.”

Jeff Owens, Plant Engineering

Maintenance costs go beyond the actual price a business must pay to repair or replace a piece of machinery. Manufacturing and engineering businesses must also cope with the costs of operational delays and similar expenses that stem from an unexpected breakdown. IoT, however, stands to eliminate some of those costly (and often destructive) expenses through improvements to predictive maintenance.

Machine to Machine Communication Enables Real-Time Alerts

Writing for Bosch, MachNation founder Steve Hilton extols the virtues of predictive maintenance as a proactive approach to industrial equipment and machinery. By capturing sensor data, humans and their hardware and software programs can make accurate predictions about a machine's life cycle. According to Hilton, Predictive maintenance...helps lower operating and capital costs by facilitating proactive servicing and repair of assets.

When a sensor detects a problem with machinery, it can communicate the issue to a computer or other device that analyzes the available data. From there, humans operators can decide how to interpret that data.

Furthermore, machines have become significantly more powerful, capable of capturing and analyzing Big Data at impressive speeds. While the industry needs further development in terms of processing power, predictive maintenance initiatives already benefit from both Big Data and M2M communication.

Connected Devices Can Transmit and Store Big Data

With regard to predictive maintenance, M2M communication and the IoT provide ample benefits to industrial businesses for predicting problems with machinery. However, connected devices can also store copious amounts of data and provide "snapshots" of every machine's life cycle since the business began using the technology.

By taking advantage of machine learning smart devices can learn from experience. As businesses use them, they collect and apply data that applies specifically to the equipment in question. Based on previous events, for instance, the device might learn that when a certain set of variables appears, breakdowns become imminent.

Monitoring asset health in real time and applying predictive analytics can make businesses more efficient, effective, and competitive. This is especially true when it comes to operations in the field. Though businesses don't always have "eyes" on their equipment, they can rely on M2M communication and the IoT to learn of impending trouble. 

Manufacturers Become Smarter Every Year

According to a recent article in Quality magazine, an engineering staff becomes 12 percent more productive when it's equipped with tablet computers. Even the simplest changes in connectivity in the workplace can have a profound impact on a business's operational integrity. 

If connected devices extend from tablets to the equipment required to produce a product or carry out a process, the potential gains increase exponentially. According to the Quality article, predictive maintenance becomes even more effective when the data gathered by the equipment is transmitted to mobile devices. Human workers can obtain the data while in the field and act on it immediately. 

Additionally, M2M communication and the IoT can have a tremendous impact on quality control. Improving the accuracy of product data management enables businesses to track all the changes to a particular piece of equipment over time and to corral metadata in one place. This applies to a company's infrastructure (such as its machine assets) as well as the products it creates.

Predictive maintenance is slowly becoming the industry standard when it comes to taking care of equipment and machinery. Preventive and reactive maintenance results in higher costs, reduced efficiency, and a higher probability of on-the-job injuries and asset damage. By harnessing the IoT and connected devices, engineering and manufacturing companies gain more control over their assets and keep more money in their pockets.