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Session 7: Predictive Maintenance, Condition Monitoring and failure prediction

공유

Session 7: Predictive Maintenance, Condition Monitoring and failure prediction

Watch our final part of a 7 part series.

During this session, we explain how prognostic health management and failure prediction methodologies are applied to quantify the remaining useful lifetime (RUL) of components, subsystem and machines under its specific real-use conditions – instead of determining the ultimate lifetime on a statistical average.

Data analytics and virtual sensing technology are used to gather deeper system insight during condition monitoring. By connecting the real data with system simulation or CAE 3D simulation in a digital twin, we can take targeted preventive actions before a predicted failure occurs.

발표자 소개

Siemens Digital Industries Software

Ralf Leis

Service Project Manager for „Data Analytics & Durability“

Graduated from Kaiserslautern University with a degree in Civil Engineering in 2001 and worked for Simcenter Engineering Services team since then as project engineer first, nowadays as service program manager and business development manager for data analytics and durability. He has a long-standing experience in the planning and execution of different kind of durability projects from load measurements, data processing and analysis up to CAE based fatigue life analysis.

관련 자료

드론 소음 감소
Webinar

드론 소음 감소

eVTOL 에어택시 및 드론과 같은 도심항공교통 기술에 대한 지역사회 수용률을 개선하십시오. 시뮬레이션 및 테스트를 사용하여 소음을 줄이는 방법에 대해 알아보십시오.

Simcenter 3D 체험판
Trial

Simcenter 3D 체험판

Simcenter 3D는 오늘날 시장에서 가장 포괄적이고 완벽하게 통합된 CAE 솔루션으로, 시뮬레이션 효율성을 획기적으로 개선하여 복잡한 다분야 제품 엔지니어링 성능을 해결하기 위한 제품입니다.