Break/Fix is Dead. You Must Predict and Prevent.

May 04, 2021 • Features • Artificial intelligence • White Paper • Digital Transformation • IFS • Covid-19

In the second article of a series of excerpts from a recent e-book published by IFS, we discuss how IoT and machine learning make predictive maintenance a reality.

This feature is just one short excerpt from an e-book published by IFS.

www.fieldservicenews.com subscribers can read the full e-book now by hitting the button below.

If you are yet to subscribe you can do so for free by hitting the button and registering for our complimentary subscription tier FSN Standard on a dedicated page that provides you instant access to this white paper PLUS you will also be able to access our monthly selection of premium resources as soo as you are registered.

Data usage note: By accessing this content you consent to the contact details submitted when you registered as a subscriber to fieldservicenews.com to be shared with the listed sponsor of this premium content IFS who may contact you for legitimate business reasons to discuss the content of this white paper, as per the terms and conditions of your subscription agreement which you opted into in line with GDPR regulations and is an ongoing condition of subscription.

Break / Fix is Dead.

The Challenge

As innovators vie to stand out and become leaders in today's highly competitve landscape, the traditional model of break-then-fix is no longer holding weight with the consumer.

To embrace the service delivery models of the future, businesses need to evolve over time from reactive to proactive to democratized and ultimately, to predictive and prescriptive maintenance.

The Solution

IFS' advanced asset monitoring technologies enable you to establish a higher level of service above and beyond fixing individual pieces of equipment when requested. It guarantees your customer continued operation and focuses on building a long-term partnership to increase their asset lifecyles and enhance their operational performance.

IoT measurements and readings draw your attention to possible faults and anomalies before they occur, allowing service teams to deliver quick and appropriate response to avoid downtime.

IFS predictive maintenance adds machine learning power from sensor data and historical asset service information to identify under - or over - maintained assets. You can revise and optimize maintenance plans, moving from time-based preventive action to condition-based predictive action for increased uptime and asset output.

IFS customer Eickhoff, like many manufacturers, has been redefining the role service will play in the company's ability to differentiate. Eickhoff's 1300 employees worldwide support two business units: mining equipment and gearboxes for industrial and wind turbine applications. Its mining customers are focused heavily on uptime and output since any downtime of the equipment is incredibly costly.

"IoT and data analysis are critical to Eickhoff's evolution. Porting notable events from our IoT environment into IFS's platform is helpful in terms of history and documentation, in detecting event that are worth alerting customers to take action on, and to schedule out and event predict service needs. But moreover, the insights we can glean are a new line of customer value. Their ultimate goal is uptime, so not only can we provide the machinery but also insights to help them achieve that goal."

Dietmar Schmitz, Head of Product Development Service, Eickhoff.

We're helping our customer Icelandair to analyze data from multiple sources while utilizing predictive modelling that's powered by machine learning. Plus, we're using explainable AI to not only predict when an aircraft may experience an issue that requires ground-time within a certain time frame, but also predict which area of the aircraft is most likely to experience a failure.

Instead, businesses need to deliver a customer's desired outcome for their product, equipment or asset, and often before the customer has even thought to ask for it. Whether it's B2B or B2C, all customers want greater value from their investment, and that means providing a service that works for them, exactly how they want it to. The additional challenge, however, is for service organizations to deliver this in a way that's sustainable and cost-effective.

"We're saving costs and increasing our on-time performance."

Lilja Scheel Birgisdottir, Reliability Engineer, icelandair.

Subscribe to access the full e-book where you can watch two videos from Icelandair, where Reliability Engineer, Lilja Scheel Birgisdottir explains how, with the help of IFS, they are able to reduce costs by collecting technical data that enables them to constantly evaluate the health of their fleet.