SparkCognition’s cognitive analytics generate early warnings of impending failure and forecast potential flight issues to minimize impact.
As A&D customers become more demanding in terms of delivery schedules and customization, industry players are expected to increasingly need highly agile production and predictive quality controls. By investing in digital technologies, the industry could be at the forefront of manufacturing, enhancing productivity and efficiency.
Deloitte
Our solution flags any values in critical aircraft subcomponents that deviate from the norm to pinpoint where, when, and how an equipment failure will take place. Get notice of pending asset failures up to weeks in advance.
Machine learning models proactively identify problematic behaviors up to months in advance, enabling more efficient operations, more agility in planning maintenance, and reducing turnaround times for aircraft availability.
Advanced behavior modeling flags underperformance of aircraft components and provides insights into conditions that cause parts to fail faster. Find optimal repair solutions through rich content analytics derived from asset maintenance logs and user manuals.
Advanced machine learning techniques automate retrieval of unstructured data —like aircraft maintenance logs and input from safety and mechanical SMEs—so decision makers can focus more time on high value business outcomes.
SparkCognition’s highly trusted, highly awarded AI-built cybersecurity solution protects against zero-day ransomware, viruses, malware, and more. Prevents 99.9% of never-before-seen attacks.
Machine learning models can be developed in hours, not weeks, and without data science expertise. Unlock insights in enterprise data with models that adapt themselves dynamically even as aircraft components or assets may change.
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