In CAiRS, we have proposed a data-driven model using a transformer-based lightweight model for accurately prediction of the remaining useful life (RUL) of systems or products. The effectiveness of the proposed model is validated using the C-MAPSS dataset for aircraft engines provided by NASA. The proposed model achieves state-of-the-art performance on the C-MAPSS dataset, and outperforms previous state-of-the-art methods by at least 30% in RMSE and 50% in Score on the harder dataset in C-MAPSS
A physical-based model is often used when there is a good understanding of a less obfuscated system. However, since most interactions in the system are not well understood, the practicality of the physical-based model is greatly reduced.
As “New-industrialisation” has gained momentum in Hong Kong in recent years, the city’s new growth agenda now depends on the application of innovative technologies to streamline manufacturing process for the development of high value-added industries and industry supply chains locally. In addition to regenerate manufacturing that once played a major role in the economy.
Today, Hong Kong’s brands represent safe and reliable products and systems, and the Centre for Advances in Reliability and Safety (CAiRS) has been established to ensure and elevate “trust” in Hong Kong products using a top-down, problem-centric and collaborative approach. Through our collaborating research projects with industry, not only accelerate the "commercialization of scientific research results", but also expediting the transformation of "from 1 to N" results. CAiRS consolidates local and overseas’ talents to improve the innovative eco-system.