Lyle Hauser’s Vantage Group on Predictive Maintenance

With smart technology becoming a greater and greater part of everyday life, it has grown increasingly likely that the average homeowner will find him- or herself as well-acquainted with predictive maintenance as the average business owner. Keeping a focused eye on the trends, Lyle Hauser’s Vantage Group knows how essential predictive maintenance will be for everyone in the future. And in an era when there is an increased accent on efficiency (particularly as it pertains to energy usage), that is a very promising idea indeed.

Predictive maintenance, which can be defined as the ability to examine certain factors to predict when equipment failure might occur (and thus nip it in the bud), is more prevalent than ever, a result of advances made in recent years in the Industrial Internet of Things (IoT). Using artificial intelligence and machine learning to their best effect, predictive maintenance has been found to reduce machine downtime by half, which is no small matter, as each idle hour results in $100,000 in lost productivity. Moreover, it reduces the use of time-based maintenance, 33 percent of which has been found to be too frequent anyway -- and half of which has been found to be ineffective.

According to Lyle Hauser of The Vantage Group, this method — common in the oil and gas industry, manufacturing, transportation and construction — is finding its way into the home -- which stands to reason, given the many interconnected devices that can be found there. There are smart thermostats, lights, security systems, and entertainment systems, among other things. It is estimated, in fact, that there will be some 31 billion interconnected gadgets in circulation by the end of 2020, and that in two years the smart home market will exceed $53 billion.

Naturally, Google is among those at the forefront of the home predictive maintenance trend, laying the groundwork for technology that can detect irregularities in the performance of certain appliances, or allow homeowners to maximize the usage of their gadgetry. Another company, OneEvent, has even developed sensors that can detect the possibility of a fire breaking out, well before standard smoke detectors sound.

As with predictive maintenance applications used in industry, those used on the home front follow the same protocol. Data is collected through sensors. Then that data is put into context -- i.e., melded with information about the use, age and model of a given device. Patterns are discerned as to when problems have occurred in the past, and ML algorithms develop predictive models.

Predictive maintenance has been particularly successful in the oil and gas industry, whether in the exploration/production phase, the transportation/storage phase or the refining/processing phase. And while there are concerns about the manner in which IoT systems might mesh with legacy systems, the upshot is that they lead to a 25 percent increase in output, a 30 percent reduction in maintenance costs and a 45 percent decrease in equipment downtime.

Lyle Hauser’s Vantage Group reasons that while results may vary on the home front, technology’s prevalence will position us to wisely expect otherwise -- that predictive maintenance will only become a bigger and bigger part of our everyday lives.