Considering the aggressive time-to-market required for aviation products and services, it is crucial to identify the cause of potential faults or failures before they have an opportunity to occur. Emerging technologies like the Internet of Things, big data analytics, and cloud data storage are enabling more vehicles, industrial equipment, and assembly robots to send condition-based data to a centralized server, making fault detection easier, more practical, and more direct.
By proactively identifying potential issues, aerospace companies can deploy their maintenance services more effectively and improve equipment up-time. The critical features that help to predict faults or failures are often buried in structured data, such as year of production, make, model, warranty details, as well as unstructured data such as maintenance history and repair logs.
Due to higher spending by aviation companies looking to optimize operating costs and increase profitability, North America will continue to be the biggest market for predictive maintenance solutions. With an estimated market share of 31.6 percent, North America is expected to grow its predictive maintenance solutions at a CAGR of 24.5 percent, maintaining its lead from 2017 through 2022.