Andreas Panayi joined Skoltech as the Professor of the Practice at the Center for Digital Engineering with extensive global experience in automotive and aerospace product development. His expertise focuses on leveraging computer aided engineering methodologies to enable the digital transformation of traditional analysis methods and expedite the product development cycle in order to develop efficient and reliable final products while reducing production and operating costs.
He holds a Ph.D. in Mechanical Engineering from Michigan State University where his research work was focused on the development of numerical models for the assessment of internal combustion engine performance. He worked with Ford Motor Company and Cummins to test and validate these models.
Dr. Panayi transitioned to the aerospace industry in 2011 by joining Boeing. He worked on the development of the methods of analysis for composite joints – the best modeling practices for interlaminar analysis using finite element methods and their validation through testing. He developed and implemented an automation framework that made these methodologies accessible with ease and straightforward human interaction, while ensuring consistency, accuracy, repeatability, and efficiency throughout the design cycle. He was instrumental in the certification of several new airplane programs and their derivatives. In more recent years, he was involved in the digital transformation where he led the Mechanical and Structural Engineering efforts for the Boeing Model Based-Engineering Global Center. He researched and developed prototypes for the infrastructure that would enable the seamless data exchange between cross-disciplinary teams so that well-informed engineering decisions are made early on in the design cycle to eliminate expensive rework, improve product quality and reduce in-service costs, while ensuring safety and reliability. He has presented multiple times on these topics over the years at the internal Boeing Technical Excellence Conference, and he won the Best Paper in Structures for his work on the automation framework for composite joint analysis. He holds one patent and four trade secrets. Recognized for his contributions, advancements and transformations in aerospace product development through modeling and simulation, he was inducted to the Boeing Technical Fellowship as an Associate Technical Fellow in Structures.
Dr. Panayi will continue his work in teaching, research and innovation at the Center for Digital Engineering with the Cyber-Physical Systems Laboratory and the Systems Thinking Group, to investigate and further advance the technologies for product lifecycle management ensuring that the next engineering leaders will have the right tools to innovate and thrive.
Overview:
At the Cyber-Physical Systems Laboratory, we blend cutting-edge research with practical engineering challenges to address real-world problems and shape the future. The projects span from active initiatives that need skilled collaborators to conceptual ideas awaiting inspired minds to bring them to life. Whether it is revolutionizing transportation, enhancing safety, pioneering sustainable practices, or developing groundbreaking technologies, there is a place for everyone to contribute. Join us to tackle meaningful challenges, collaborate with multidisciplinary teams, and be part of innovations that make a difference. Together, we will turn possibilities into reality by advancing and transforming engineering.
Research Projects:
Engineering Revolution at the Cyber-Physical Systems Laboratory
This initiative focuses on developing cutting-edge solutions within an integrated and applied engineering ecosystem. By leveraging digital and product lifecycle management (PLM) tools, the lab creates sustainable and innovative products using model-based systems engineering (MBSE) and digital twin technologies. The lab also emphasizes educational advancements, equipping students and professionals with the tools to address future engineering challenges.
Unmanned Trains: A Smarter Future on Rails
Aimed at revolutionizing rail transport, this project develops prescriptive analytics and digital twin solutions to enhance the operational reliability of unmanned trains on the Moscow Central Ring. By predicting critical system failures, the project reduces downtime, optimizes maintenance schedules, and ensures continuous operation. With 64 digital twin instances planned, the initiative promises smarter diagnostics for safer, cost-effective railway systems.
Smart-Rails: Ensuring Safety Across the Tracks
The Smart-Rails system applies ultrasonic guided waves to detect and predict rail damage in real-time, addressing the growing demand for safer rail infrastructure. This project develops a digital twin-driven approach to monitor rail integrity and prevent catastrophic failures. By leveraging advanced analytics and field testing, the system will offer a proactive solution for over 85,000 km of Russian railways under increasing stress from heavier and faster trains.
DroneSpect: Revolutionizing Aircraft Inspections
DroneSpect introduces advanced drone-based solutions for visual inspection of aircraft structures. This system will reduce inspection time by up to 85%, addressing the global shortage of aviation maintenance professionals and improving operational efficiency. By complementing human inspectors, DroneSpect will offer a practical approach to ensure safety and reliability in the rapidly expanding aviation industry.
STEM Digital Twins: Predicting the Future of Maintenance
This project establishes a standardized methodology for building Structured, Traceable, Efficient, and Manageable (STEM) digital twins to enhance predictive and prescriptive maintenance. By integrating these systems across use cases like train systems and aircraft, the project aims to transition from reactive to predictive strategies, reducing maintenance costs and improving operational efficiency.
Machine Learning Meets Structural Engineering
Focusing on engineering innovation, this project develops synthetic datasets for finite element analysis (FEA) combined with machine learning techniques. The goal is to automate stress analysis processes, streamline decision-making, and enhance structural reliability. This interdisciplinary effort equips participants with skills relevant to emerging fields in engineering and data science.
AI Engineering Agent: Bridging Intelligence and Innovation
This project integrates large language models (LLMs) to revolutionize engineering processes, from regulatory compliance to product certification. The agent generates simulation inputs, streamlining workflows and improving efficiency. It promises to bridge the gap between machine learning and complex engineering challenges.
Safeguarding Seal Habitats: Smart Water Systems
Focusing on water quality in zoo environments, this project develops a predictive maintenance system for pumps in the Moscow Zoo’s seal habitat. By monitoring parameters like vibration, pressure, and temperature, the system ensures the continuous operation of critical equipment, protecting animal welfare through early failure detection and timely maintenance.
The Flying Weed Terminator: Taking the Fight to Hogweed
Combating invasive hogweed, this project designs an autonomous drone system equipped with computer vision and herbicide sprayers. The system precisely targets hogweed clusters, reducing human effort and exposure to toxic sap. By automating weed control, the project offers an innovative solution to a growing ecological challenge.
The Smart Grill: Automating Culinary Perfection
This project introduces an automated kebab grill with sensors for temperature control, automatic skewer rotation, and height adjustments. By optimizing grilling processes, the Smart Grill ensures even cooking, reduces manual effort, and enhances user experience, blending convenience with culinary precision.
Digital Twins for Additive Manufacturing: Crafting Precision in 3D Printing
Aiming to improve the consistency and reliability of 3D-printed parts, this project integrates digital twins with machine learning algorithms for real-time monitoring of additive manufacturing processes. By minimizing physical tests and variability, the system streamlines production and certification, advancing industrial 3D printing.
Legacy to Cutting Edge: Simplifying Complex Systems
This project addresses challenges in managing complex systems through requirements traceability and standardized engineering workflows using PLM tools. By leveraging modern process orchestration software, the research demonstrates the feasibility of orchestrating and optimizing legacy analysis methods for modern engineering applications.
tPAD: Transforming Prescriptive Analytics into Reality
the Prescriptive Analytics Demonstrator (tPAD) test bed explores prescriptive analytics by simulating malfunction scenarios in a controlled environment. Using artificial vibrations in rotating shafts, the project develops accurate analytics solutions to predict and prevent failures. Recognized for its educational innovation, tPAD bridges theoretical concepts with real-world engineering applications.
Digital Twin Farming: Sustainable Solutions for Indoor Agriculture
This project develops a simulation-based digital twin for energy-efficient indoor agriculture systems, addressing high energy consumption challenges in vertical farms and greenhouses. By modeling HVAC systems, microclimates, and control systems, the research supports sustainable farming practices, enabling participation in energy efficiency initiatives and reducing operational costs. This will be a joined project with the Center for Agro Technologies.
Journal Publications
Conference Presentations and Proceedings
Internal (closed-door) Conference Presentations
* BTEC : Boeing Technical Excellence Conference
Андреас Панаи присоединился к Сколтеху в качестве Профессора в Центре Системного Проектирования с обширным мировым опытом в области разработки продукции для автомобильной и аэрокосмической промышленности. Эксперт в области использования методологий компьютерного проектирования для обеспечения цифровой трансформации традиционных методов анализа и ускорения цикла разработки продукта для создания эффективных и надежных конечных продуктов при одновременном снижении производственных и эксплуатационных затрат.
Он имеет докторскую степень в области машиностроения («PhD in Mechanical Engineering») от Университета Штата Мичиган, где его исследовательская работа была сосредоточена на разработке численных моделей для оценки характеристик двигателя внутреннего сгорания. Он работал с «Ford Motor Company» и «Cummins», чтобы протестировать, проверить и утвердить эти модели.
Д-р Панаи перешел в аэрокосмическую отрасль, перейдя в компанию «Boeing», и с 2011г. он работает в России. Он работал над разработкой методов анализа композитных соединений — лучших практик моделирования для межслойного анализа с использованием методов конечных элементов и их проверки посредством испытаний. Он разработал и внедрил структуру автоматизации, которая сделала эти методологии доступными с легкостью и простым взаимодействием с человеком, обеспечивая при этом согласованность, точность, воспроизводимость и эффективность на протяжении всего цикла проектирования. В последние годы он участвовал в цифровой трансформации, где руководил команду по машиностроению и проектированию конструкций в глобальном центре проектирования на основе моделей Боинга («Boeing MBE Global Center»). Он исследовал и разработал прототипы инфраструктуры в рамках «PLM», которая обеспечила бы беспрепятственный обмен данными между междисциплинарными командами, от концепции продукта до эксплуатации, чтобы хорошо обоснованные инженерные решения принимались на ранних этапах цикла проектирования, и для исключения дорогостоящих доработок, улучшения качества продукции и снижения эксплуатационных расходов, обеспечив при этом безопасность и надежность продукта. На протяжении многих лет он неоднократно выступал по этим темам на внутренней конференции «Boeing Technical Excellence Conference» и получил награду за лучший доклад по конструкциям за свою работу над структурой автоматизации для анализа составных соединений. Он владеет одним патентом и четырьмя коммерческими. Он сыграл важную роль в сертификации нескольких новых авиационных программ и их модификации. Его вклад, достижения и преобразования в области разработки продукции для аэрокосмической отрасли посредством моделирования и симуляции были признаны, и он стал членом «Boeing Technical Fellowship» в ранг «Associate Technical Fellow (ATF)», ранг который присваивается только 3%-ам лучших инженеров Боинга по всему миру.
Д-р Панаи продолжит свою работу по обучению, исследованиям и инновациям в Центре Системного Проектирования с Лабораторией Киберфизических Систем и Группой Системного Мышления, чтобы исследовать и развивать технологии для управления жизненным циклом продукта, гарантируя, что следующие инженеры-лидеры будут иметь правильные инструменты для инноваций и процветания.