In his first job, Joseph A. Martinez converted aerospace design specifications into detailed technical drawings. By today’s standards, this may seem an archaic approach; however, computer-aided design (CAD) programs were just beginning to be embraced by engineers.
Once manual renderings were usurped by CAD, Martinez’s duties evolved from creating renderings to manually analyzing the program’s output; still, it was a tedious process.
“It seemed like I could do it manually faster than the computers at the time,” he recalls. “But technology progressed, evolved and expanded. We’re now where we have all of these machines that are faster, hold more space, and data is generated faster than ever.”
Now, as a senior technical leader in the aerospace industry, Martinez relies on the computational capabilities of modern software, and, perhaps most importantly, the expanding storage capacity in which to stash massive quantities of harvested intel.
“It’s easier to obtain data, but it requires additional space to do that and to be able to access it,” he notes.
Since 2003 Martinez has worked at Belcan. Based in Cincinnati, OH, the corporation provides engineering expertise, cybersecurity services, and technical recruiting for industrial and government organizations, as well as aerospace manufacturers.
Although he’s had many opportunities over his career to experience the efficacy of data management, for Martinez, one project last year uniquely illustrated the practicality and flexibility of data analytics.
“We were tasked to take data, which basically represented components needed to build a jet engine and ensure the engine’s accuracy. The challenge was that there were multiple iterations because the parts are constantly changing in various models that comprise the whole engine,” Martinez explains.
“IT SEEMED LIKE I COULD DO IT MANUALLY FASTER THAN THE COMPUTERS AT THE TIME. BUT TECHNOLOGY PROGRESSED, EVOLVED AND EXPANDED. WE’RE NOW WHERE WE HAVE ALL OF THESE MACHINES THAT ARE FASTER, HOLD MORE SPACE, AND DATA IS GENERATED FASTER THAN EVER.”
Initially, the process took several months. “I looked at the big picture and thought there has to be an easier way. We were looking at thousands and thousands of parts that translated into data. I decided to create data relative to the structure in our two environments. Then I had to figure out how to bring the two different data sets together and communicate with each other, highlighting the unknowns and changes in the iterations,” he explains.
“Once they could communicate, we got an understanding of what had to be added or removed so we had a completed engine that was valid with all of the components required to be in that iteration,” Martinez says this data-dependent approach radically sped up the process.
“We took that timeline from three to four months to one month, and then cut it to a week, then within days and hours for new iterations,” he points out.
“The customer was pleased, and we delivered on time with quality and integrity of parts. That was quite the feat.”
Back when he worked as a drafter, Martinez may not have foreshadowed the specific possibilities of today’s technology, but he knew the momentum would never slow.
“Even back then I was learning that technology is going to improve, and it has, and always will,” he concludes.
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Source: Equal Opportunity Publication
