Leonardo (formerly Selex Electronics Systems/Selex Galileo)
Advanced engineering company, committed to delivering winning, cost-effective solutions in the aerospace and defense sectors.
LEONARD needed to identify and minimize manufacturing/repair touch time and investigate yield and performance issues at multiple sites with Secure and Secret deployments.
They required the ability to analyze disparate data from complex test systems and
normalize analysis data from ATML, NI TestStand, LabVIEW TDMS, PDF and various Text, CSV and Excel formats.
Aggregation of manufacturing and field/return data from Integration, ESS Thermal, ESS Vibration, Pre-ATP, ATP.
Identify trends such as: measurement variation between test stations, test software impact on performance, and operator impact on performance and yield.
Continuously gathering of test data fin any format, NI TestStand, LabVIEW TDMS, PDF, and multiple variants of .txt, CSV, and Excel formats with hundreds of metadata points for performance characterization.
- Minimized manufacturing/repair touch time
- Faster production throughput
- Reduction in Defect Per Unit (DPU) for high value assemblies
- Measure and track Throughput Yield
- Single source of truth for as-built performance
- Multi-site cross functional collaboration
- Reduction in high value resource demand
Highly complex products with tight safety and reliability metrics. Need to analyze production data to quickly identify issues affecting yield and performance. Data aggregation from AOI,AXI,ICT,FCT, ESS, Failures, Rework and ATP performance test.
Apply Statistical Process Control ( SPC) across a wide number of process variables such as CpK.
“IntraStage core technologies has enabled the visibility needed to achieve a 90% reduction of our yield issues. This helped ultimately reduce our Cost of Goods Sold by £ 500,000 / year via achieving target improvements in Rolled Throughput Yield.”
General Atomics needed to analyze gigabytes of test data from ATEs producing LabVIEW and TestStand data outputs on the manufacturing floor to identify issues that affect manufacturing efficiency and product quality.
They also wanted to be able to digitize paper-based manufacturing data capture to facilitate data analysis and improve process integrity.
IntraStage was also tasked with enabling the processing of data from multiple manufacturing lines and systems.
