Predictive Maintenance: The Asset Efficiency Testbed Keeps Aircraft Safe

During a recent return flight from a business meeting in Washington, DC, I endured a frustrating delay. After boarding and waiting at the gate for nearly an hour, the pilot announced that the aircraft would be grounded for at least two more hours because a critical component of the landing gear had malfunctioned and its replacement needed to be shipped in. While I sat with fellow passengers, I realized how predictive maintenance could have prevented this costly interruption.

The aircraft landing‑gear predictive‑maintenance use case is the first live demonstration of the Asset Efficiency Testbed, an Internet of Things initiative led by the Industrial Internet Consortium (IIC). Infosys is spearheading the development, with strategic partners Bosch, Intel, PTC, and HP providing essential technology and expertise.

Asset efficiency may sound like a financial buzzword, but it represents a powerful technology that can dramatically reduce downtime, save billions, and, most importantly, protect lives. This breakthrough is especially relevant for high‑tech manufacturers and any organization that relies on critical infrastructure.

"Asset efficiency isn’t a revolutionary new concept, but it is highly underleveraged." – Dr. Richard Mark Soley, Executive Director, Industrial Internet Consortium

Asset Efficiency: The Elephant in the Room

Modern equipment and systems generate vast amounts of data—every activity in an aircraft, factory, or oil field produces measurable signals. When that data is continuously monitored and converted into actionable insights, maintenance teams can accurately anticipate and address failures before they occur. The benefits are clear: higher performance, lower energy consumption, reduced waste, improved quality, increased profits, and even saved lives.

Yet, a recent joint study by Infosys and the Institute for Industrial Management (FIR) at Aachen University revealed that while 85% of industrial and process‑manufacturing companies in China, France, Germany, the UK, and the US recognize the need for asset efficiency, only 15% have actually implemented machine‑data technologies to achieve it. China leads the way, but the gap remains wide.

The study identified key obstacles: lack of asset instrumentation, absence of real‑time analytics, missing integration with related systems, and a narrow focus that ignores broader efficiency dimensions such as energy, utilization, operations, and serviceability.

Mind the Gap

The Asset Efficiency Testbed is engineered to bridge this divide by taking a holistic approach that covers operational, energy, maintenance, service, and informational aspects (see graphic). Its core capabilities include:

• Condition Monitoring: Continuously measures and tracks vital health parameters, ensuring they remain within safe limits.
• Diagnostic Analysis: A robust analytics engine compares live data against historical and contextual datasets to spot anomalies.
• Prognostics: Advanced algorithms forecast the remaining useful life of assets or specific components.

Collaborating partners:

• Infosys leads the initiative, designing the solution, developing the application, and providing the Infosys Information Platform (IIP) as the analytics engine.
• Bosch supplies sensor technology, edge data acquisition, device management, and scalability through the Bosch IoT Suite, with the Vorto code generator enabling M2M modeling.
• PTC offers the ThingWorx Application Enablement Platform (AEP) for building dashboards, widgets, and other UI components.
• Intel delivers the Moon Island Gateway for edge data aggregation and collaborates with HP to provide horizontal infrastructure.