Siemens Gamesa Renewable Energy, S.A.
Co-creation of an Artificial Intelligence solution to quickly identify flaws during quality checks
Siemens must put each of the 5,000 blades it produces annually through a stringent quality assurance process. Any flaws when a blade is in operation could prove catastrophic and could inflict major damage to the company’s reputation. However, manually evaluating Ultrasonic Testing (UT) scanning of each blade takes up to 6 hours. Working with long-term partner Fujitsu, together they co-created an Artificial Intelligence (AI) solution that could automatically detect flaws through machine learning and deep learning capabilities; it achieved 100% coverage of all defects and evaluation of each Nondestructive Testing scanning reduced by 80%.
Fujitsu’s ground-breaking Artificial Intelligence technology dramatically cuts the time required for an inspection of turbine blades.
Kenneth Lee Kaser,
Head of Supply Chain Management,
|Company Name||Siemens Gamesa Renewable Energy, S.A. WebSite|
|Address||Parque Tecnologico de Bizkaia, Edificio 222, Zamudio, Spain|