Treating unstructured data as intellectual property

As we wade further into the information age, the aviation industry stands on the cusp of revolutionary advancements in engineering. Declining costs and the increasing sophistication of information technology (IT), engineering design, and simulation tools are enabling reams of new data to be generated by sensors sitting in vital machines and their components. Breakthroughs in predictive maintenance, product design, customer service, and other major business initiatives should follow.

Although this telemetry data is central to realizing the greatly anticipated promise of advanced analytics and the industrial Internet of Things (IoT), it alone cannot help us to make this leap. Engineers need to aggregate that information with other massive unstructured datasets – such as original product drawings (geometry) and nondestructive product tests (simulations) – that are mission-critical across the equipment’s lifespan, which can stretch to 80 years.

Until now, IT people have led the charge in managing these datasets, implementing point solutions driven by three motivating factors: cost, performance, and scale. These narrow criteria have ignored the temporal element – engineers’ need for ready access to data while the equipment is in the field. Consequently, datasets have become scattered around enterprises where engineers can’t immediately find, retrieve, and collaborate on them.

These datasets are foundational pieces and are critical to the delivery of the next generation of smart design. They are inherently invaluable intellectual property (IP), so engineering heads and C-Suite executives need to treat them like the precious assets they are and take ownership of how they are stored and accessed by the product design team.
 

Access correlates to revenue

Aggregating these datasets and making them accessible for decades aids engineering teams’ core objectives. If your organization’s mission is to eliminate all unplanned outages for customers, for example, then engineers need to be able to access simulations conducted on a piece of equipment before it was deemed ready for the field. They can then compare it to telemetry data collected from both the original test bench and the years since it has been in use. If this part or component is 10 years old, the original simulation file might have been created 12 years ago, and test bench data was likely first saved and stored a few years later. Service organizations need all of this data at their fingertips if they are maintain zero interruptions.

Similarly, if you’re planning to upgrade an engine or turbine equipped with remote monitoring and diagnostics capabilities, you may need access to 20 years’ of telemetry data, original geometry drawings, and the results of tests performed until the day the product was shipped to the customer. Researchers are often forced to recreate geometry (CAD) schematics documents because teams have lost track of them across the decades. If time is money, this represents lost revenue.

Since it is the services cycle in which many industrial equipment leaders create the bulk of their revenue, datasets that exist in the enterprise but are effectively lost because nobody can find them – so-called dark data – actually delay or prevent companies from increasing margins.

The race is on in the aviation industry to tap the full potential of the IoT and the Industrial Internet. Those who get to the finish line first will excel; those who lag behind may not survive long enough to reach the finish line at all. Next-level predictive maintenance capabilities and futuristic new product designs hinge on R&D having unprecedented access to geometry, simulation, and telemetry datasets and the opportunity to examine them across the lifespan of a piece of equipment. There is a huge pot of gold for the companies that overcome this technical challenge – additional revenues from the service cycle and sales of groundbreaking new products.
 

Preventing data assets from going dark

The biggest obstacle to achieving these goals is an IT infrastructure that has evolved to leave data scattered in silos. Every 3-to-5 years, IT departments upgrade technology – updating hardware, reorganizing data centers, and otherwise moving files around. Several technology refreshes may be executed during the full life cycle of a piece of serialized equipment. With each refresh, file pathnames are changed and links are broken, making it harder for product design teams to keep track of unstructured documents – a problem that is compounded as the sensors in these individual physical assets continue to generate exponentially increasing numbers of massive datasets. Moreover, as employees come and go, the locations of these critical files are lost.

During the past 30 years, IT departments have accumulated numerous point solutions – storage products and applications aimed to collect, organize, and store data – but aggregating data from these systems is cost-prohibitive. Meanwhile, engineering divisions have worked around IT for years, figuring out creative yet inefficient methods of keeping tabs on mission-critical datasets. As a result, product designers lose 45 to 120 minutes per day retrieving data from nontraditional solutions.

Now is the time for engineers to take control of their datasets – not through bypassing IT the way some executives have done. IT and engineering heads need to collaborate in the overhaul of the modern corporate IT infrastructure so that product development and service organizations can effectively deliver on the C-Suite’s greater strategic aims.

Sponsorship of such initiatives should come from one or more C-level executives, as well as from leaders of both departments. If data longevity and durability is critical to bringing forth advanced analytics capabilities necessary for long-term company survival – instant access to these unstructured datasets from the moment a product is conceived to the day it is retired from the field – it should not be a problem getting leadership to the table.

Redesigning today’s corporate IT arrangement is not easy. Products from established IT vendors are often not designed with true data access and endurance in mind, and most cloud and big data solutions solve different problems while exacerbating this one. However, boardroom involvement fundamentally changes the way these datasets are viewed – nobody in the company will dispute that they are precious company IP, not just bytes in storage.

Companies that proactively take this outlook will be ahead. Organizations that are slower to adapt to this mindset will find themselves fighting for their survival. Either way, leading aviation organizations will have to treat geometry, simulation, and telemetry data as crown-jewel assets – because their future competitiveness depends on it.

Peaxy Inc.
www.peaxy.net

About the author: Manuel Terranova is the president and CEO of Peaxy Inc., producer of the Peaxy Hyperfiler. He can be reached at info@peaxy.net or 408.441.6500.