High production requirements combined with labor shortages and supply chain constraints are placing strong pressure on aerospace manufacturers to minimize or eliminate quality and nonconformance issues in their production processes. Automating quality control processes can improve yield, process efficiencies, and ensure businesses never ship defective products to customers. Computer Vision for Quality Insight solutions on AWS help aerospace manufacturers analyze data from disparate sources, including cameras from multiple vendors, which saves significant time compared to manual inspection. Automated image analysis enables root-cause analytics and the development of countermeasures, helping teams manage the entire process life cycle, and achieve near zero defects at scale.
Partner Solutions
Software, SaaS, or managed services from AWS Partners
Total results: 5
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Maximo Application Suite - SaaS
Maximo a single, integrated cloud-based platform that uses AI, IoT and analytics to optimize performance, extend asset lifecycles and reduce operational downtime and costs. With market-leading technology from IBM Maximo®, you’ll have access to configurable CMMS, EAM and APM applications, along with streamlined installation and administration, plus a better user experience with shared data and workflows. Key features of Maximo Application Suite: Leverage market-leading EAM, mobility, add-ons and industry models Enhance reliability with AI-powered monitoring, inspection and predictive maintenance Only pay for what you actually use with simplified licensing Use multicloud deployment for greater flexibility -
Tulip Frontline Operations Platform
Tulip’s Frontline Operations Platform is empowering organizations to digitally transform their operations and gain real-time visibility into the people, tools, machines, and processes involved — all in a matter of days. With Tulip’s IIoT-enabled, no-code platform, companies can give the engineers closest to operations the tools they need to improve the productivity of their frontline teams, the quality of their output, and the efficiency of their operations. -
APEx Quality Management at the Edge via Computer Vision
The computer vision-based quality analytics solution will automate the visual inspection process, then accurately identify, categorize, and label defect types. Data is used to determine the root cause of an issue by examining a timeline of rejected parts and the annotated image. Results are integrated with OEE calculations and Quality Management System to trigger corrective action. An MLOps framework was designed to facilitate the development, maintenance, and deployment of machine learning models. This framework is utilized to support the Quality Management use case. The solution can also be extended to other vision-based and AI/ML use cases. A gateway management tool was designed to support multi-site enterprise deployments. This tool will reduce the gateway deployment effort and provide a central location to monitor status and to manage functionality updates. -
Denali Analytics and Monitoring Application
Denali’s Analytics & Monitoring Application (AMA) is a browser-based interface for industrial customers to visualize and retain production line insights generated by complementary computer vision applications such as Denali Automated Quality Inspection, both powered by AWS. AMA runs locally and is used to capture images from multiple cameras then display anomalies detected by AWS machine learning models. This capability allows plant managers and staff to quickly identify defects and associated trends on their production lines over time. As a result, they can make data-driven decisions that reduce downtime and increase efficiency. -
Eigen Industrial Vision Platform
Eigen’s AI-enabled vision platform allows manufacturers to see inside their processes to avoid costly quality issues. It consolidates critical quality and process data to detect issues in-line – eliminating scrap and destructive, post-production testing and providing traceability on every-part.