Predictive Insights Take the Guesswork Out of Aircraft Ops

April 5, 2019 | Author: Josh Melin

The digital era is taking a lot of the guesswork out of aircraft operations. Connected aerospace, the Industrial Internet of Things and advanced data analytics enable airline, business aviation and military operators to use predictive insights to make better decisions about their operations.

For example, the use of predictive insights has had an enormous impact on aircraft maintenance by leveraging the vast amounts of data generated by major aircraft systems. Data-based maintenance approaches are nothing new in aerospace, where descriptive and diagnostic maintenance approaches have long been used to help maintenance teams uncover the source and cause of equipment failure – after the failure occurs.

Now we’ve evolved to predictive maintenance systems that identify and predict faults and performance degradation so they can be addressed before they cause an onboard system to fail. Predictive techniques are used to monitor the health and performance of onboard systems, of course. But they also analyze data and patterns from past events, make assumptions and use sophisticated algorithms to predict when a part will fail.

Identifying potential problems days in advance creates a huge advantage for operators and their maintenance teams, who can now operate in a truly proactive mode. The result is less downtime and better aircraft availability, mission effectiveness, on-time performance and staff utilization. Not to mention lower maintenance costs and happier passengers.

But wait. Big data, cognitive analytics, machine learning and artificial intelligence enable another big advancement called “prescriptive maintenance.” With prescriptive insights, maintenance teams know not only which part is likely to fail, they know the nature of the problem and how to fix it.

GoDirect Connected Maintenance is a prime example of Honeywell’s nose-to-tail domain expertise that is helping our customers improve their operations. In fact, many of our connected maintenance customers have seen a 30 percent reduction in unscheduled maintenance, which has a huge impact on their operational efficiency and bottom-line performance.

Many of Honeywell’s brightest technical staff is working to advance the science behind predictive and prescriptive insights, and they’re making enormous progress in the connected maintenance arena and across the aerospace value chain.

Our unique big data expertise lets us combine data sets from multiple platforms and display useful information on a single screen accessible by every department. Operators will be able to apply information formerly isolated in a single system and will see the impact their decisions have on the enterprise’s overall performance.

For example, they’ll be able to weigh the relative merits and real cost of using the brakes or thrust reversers to slow the aircraft down after landing. One choice impacts maintenance and braking materials costs, the other uses more fuel. With the right data, married and aggregated in the right way, operators will be able to make the best decision.

Honeywell customers are excited about the work we’re doing to take predictive and prescriptive technologies to the next level. We’re helping operators make sense of all the data their enterprise generates and use it to make faster, better, more-informed decisions to improve safety, efficiency and financial performance.

Josh Melin

Josh Melin

Product Line Director

Josh Melin is currently Product Line Director for GoDirect Connected Maintenance with Honeywell Connected Enterprise Aerospace. In this role, Josh is responsible for managing the strategy, business plan, and P&L for Connected Maintenance. Josh has been with Honeywell over 11 years in positions of increasing responsibility in Engineering, Project Management, Lean, Site Operations Leadership, and Product Line Leadership. Josh holds a Bachelor’s of Science Degree in Mechanical Engineering from the Pennsylvania State University and a Master’s of Business Administration from Arizona State University.

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