Vinod Arekar is a service supply chain expert at PTC and as a Fellow he leads strategic initiatives overseeing several accounts to ensure success. Vinod’s strategic thinking and experience have helped bring the concept and application of Service Simulation to PTC. This and other innovations have helped propel Servigistics to be recognized as the industry leading service parts optimization solution. Vinod is a popular presenter at the annual LiveWorx event from sharing exciting success stories together with the clients with which he collaborates.
Good morning from Atlanta—or if you weren’t there in person, let me say this: you missed an incredible moment for the future of military aviation logistics.
On April 9 at the Military Aviation Logistics & Maintenance Symposium (MALMS), I had the privilege of presenting at the Georgia World Congress Center on a topic that’s close to my heart: "Leveraging AI to Revolutionize Materiel Readiness." The room was full of forward-looking leaders eager to explore how artificial intelligence (AI) is already transforming defense readiness—without adding cost or inventory burden. For those who couldn't attend, here's what we covered (and why I hope you'll catch the next one).
AI is Here—and It’s Making an Impact Now
Let’s start with the big takeaway:
AI is already providing significant opportunities to improve materiel readiness without increasing inventory.
But here’s the real secret: the full value of AI comes when it is tightly integrated with your supply chain. As I said during my talk, “AI by itself is not going to make the aircraft fly again. You need the part available in time at the right location for you to go on a mission.”
That’s why we focused on a dual-engine approach: combining AI-powered failure prediction with supply chain optimization. Separately, these systems are powerful and work towards the common goal of improving materiel readiness. Together, they’re transformative.
Failure Prediction Meets Supply Chain Intelligence
Let’s imagine a helicopter blade with a vibration sensor. AI detects that it might need replacement in 10 days. That sounds helpful, right? But it’s not enough.
As I told the audience, “That helicopter blade is not available on Amazon Prime. You can't just get it in 10 days. It might take a quarter to repair—or a year to procure.”
That's where the integration comes in. The predictive signal must flow into your planning engine, which then leverages it to take appropriate supply actions including material movement and procurement/repair. This isn't a future vision—it’s a reality we’ve tested and proven using real-world data.
From Theory to Results: NASA Case Study
We put our approach to the test with a publicly available NASA dataset from their Prognostics Center of Excellence. Over 700 gas turbine engines. Four types. Twenty-one sensors. Huge variability.
We ran it through two engines:
- The Servigistics AI Engine for remaining useful life prediction
- The Servigistics Supply Chain Optimization Engine for planning and stocking strategy
Then we assessed them together using SimAcumen’s Monte Carlo simulations. What we found was nothing short of remarkable.
“Even when AI predictions were not perfect, we saw average wait time reductions of over 23% and fill rate improvements between 8% and 55%.”
Let me be clear: these results were achieved without tuning the AI to perfection. In fact, we deliberately kept accuracy low to reflect real-world variability. Why? Because your AI won’t always have a 98% accuracy rate. Weather changes, use cases shift. Your models need to deliver value even when imperfect.
Tangible Benefits Without the Wait
I often see organizations stall on AI initiatives because they think they must “perfect the model” before seeing results. That’s a mistake.
“There is no need to wait. Readiness benefits are immediately available—even with rough AI.”
One engine type in our case study showed a drop in average wait time from 120 hours to 0.2 hours. That’s operational readiness you can feel. Another allowed us to trade that readiness gain for a 25% reduction in inventory—from 28 spares to 21—without degrading performance.
A Flexible, Mission-Ready Future
So where do we go from here?
- Quantify the gain. You can’t improve what you can’t measure.
- Don’t let imperfect AI stop you. Significant benefits are yours to take, and further improvements can be incremental.
- Use flexibility to align with your goals. Want to reduce cost? Improve readiness? You get to choose between them, or a happy medium.
Our platform allows you to configure and recalibrate based on your operational priorities. Whether you're focused on sortie availability, budget pressures, or sustainability, AI + supply chain intelligence gives you the tools to meet the mission.
It’s Time to Act
To everyone who joined us live in Atlanta—thank you for your energy and questions. You helped make the session dynamic and insightful.
And for those who missed it? All I can say is, I hope to see you next time. Because when we talk about revolutionizing readiness, this isn’t theoretical anymore. It’s here. It’s working. And it’s changing the game for aviation and defense logistics.
“We don’t live in a perfect world. That’s why our solutions must work in the real one.”
Let’s bring AI and supply chain together—and fly smarter, stronger, and more ready than ever.
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Servigistics revolutionizes service supply chain optimization with purpose-built industrial AI innovations.
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