The Future of Reliability—in the AI Age
Article from MHI Solutions Magazine
There is no doubt about it, the dawn of the artificial intelligence (AI) age is no longer approaching. It has arrived—in full force.
As a result, end users must understand how predictive analytics and digital twins are influencing fundamental, traditional reliability practices. After all, they’re jointly strengthening reliability practices throughout the entire material handling industry.
How so? According to Kushagra Thakur, senior product manager, Forge APM, at MHI member Honeywell, they simultaneously add precision, context and foresight. In turn, distribution centers (DCs) and warehouses have greater visibility than ever before, enabling more accurate decision‑making.
“Predictive analytics detect microscopic shifts in vibration, temperature and electrical patterns long before failure symptoms appear,” Thakur said. “Meanwhile, digital twins extend this by simulating asset behavior under different loads and operating conditions.”
While reflecting on predictive analytics’ chief goals, Nathan Hibbs, material handling and intralogistics industry business development manager at MHI member Beckhoff Automation LLC, believes two especially stand out. First, it will detect any equipment degradation before a catastrophic failure ever occurs. And second, it will ensure DC and warehouse managers’ equipment components have the most usable life possible…
