Predictive maintenance with smart analytics

Machines break. Sadly, despite huge advances in engineering, it is inevitable. For forecourt operators equipment downtime can come at great financial cost and can heavily impact customer satisfaction. It can also lead to customers replacing parts too early, again at great financial cost. But what if operators could predict when equipment was going to break and take the necessary steps to prevent it? This might sound like the stuff of legends but by using artificial intelligence, Faschang Service & Management has been able to create a technology that does just that.

Faschang, established in 2005, specialises in efficient maintenance. Their cloud-based solution omis4.0 (Object Maintenance Information System) performs important maintenance and service tasks for companies, allowing operators to manage multiple sites and knit together the resources and capabilities of the corporate office with the insight of the local fuel station.

“With omis4.0, site operators can manage all the equipment on their site. On a forecourt that can mean everything from the dispensers through to the refrigerator cooling systems in the c-store.

“Behind each equipment you have detailed information; such as the year of manufacturing, warranty time, warranty period, who is the responsible service contractor as well as a other technical information which can be added in. All this information means we can manage the whole maintenance process in a very high level, automated way.

“At the moment, if diesel is not working at pump number one, the software will flag this up and send an automatic email notification to the responsible service contractor. When repair work is completed this is entered into omis4.0 and allows us to calculate their response time and the availability of the equipment,” he added.

Whilst the current process, which is in operation at sites in 7 European countries as well as in the United States, has been proven to save Faschang’s clients time, resources and money, we saw an opportunity to use the information they were gathering to create a solution that was more proactive than reactive. By using easy to implement sensors, smart algorithms and a user-friendly dashboard alongside the existing omis4.0 systems, customers can not only manage the maintenance, but actively tackle unplanned equipment downtime.

Through smart algorithms, the software can analyse and interpret all gathered data. Warnings are visualised at the dashboards and reports are generated automatically before a problem occurs. This gives site operators plentiful time to plan the downtime and maintenance efficiently.

OMIS is gathering the information, not from staff on the station, but from the devices themselves. So the software will issue a warning that a part will run out in the next two weeks. You no longer have reactive maintenance, you have active, planned maintenance which will reduce costs, increase availability and increase turnover.

The predictive maintenance solution is currently in the testing phase and Faschang are working with customers to run pilot projects over the next 12-18 months. Once the pilot phase is completed the new solution will be launched as an omis4.0 module - ‘Smart Analytics’.