Industrial AI
Industrial AI represents a confluence of Domain and Data, connected through Discipline, focusing on Industry-inspired Research, Methodological Innovation and Education, and Fundamental Research with Systematic Thinking. By integrating these key aspects, Industrial AI facilitates a more coherent understanding and application of AI technologies in the industrial sector. This cohesive approach enables businesses to address complex challenges with innovative solutions, leveraging the synergy between domain knowledge, quality data, and disciplined methodologies. Through methodological innovation and fostering education, along with a commitment to fundamental research and systematic thinking, Industrial AI propels the field toward new heights, aligning the theoretical frameworks with practical industrial needs.
COMMON ISSUES IN INDUSTRIAL SYSTEMS
Many data in the industry currently suffer from issues related to either Usefulness or Usability, leading to complications in extracting valuable insights. Addressing and resolving these data quality problems is essential, as it paves the way for more effective utilization of data, transforming it into actionable information that can drive decision-making and foster growth.
DATA-CENTRIC APPROACH
A Data-Centric Approach focuses on considering the quantity and quality of data, ensuring that the right methods are selected for problem-solving. By prioritizing the integrity and relevance of the information, it enables more precise analysis and decision-making tailored to specific challenges.
APPLICATIONS
With a dedication to excellence in several key areas, Industrial AI identifies the unique intricacies of each domain and utilizes specialized knowledge and data to craft solutions tailored to specific needs, offering unparalleled precision and efficiency for a wide array of industrial applications.
PLATFORM INDEPENDENCE
The Center’s tools can be reconfigured for use on many platforms or software languages. Currently, the Center focuses on commercially available engineering platforms and cloud-based platforms.
Industrial AI Data Foundry
Industrial AI Data Foundry will serve as a data hub to host more than 100 different datasets from real-world industrial problems to train engineers to apply AI to solve problems systemically. These datasets cover a broad range of industries including automotive, aerospace, healthcare, semiconductors, energy, transportation, mining, construction, industrial automation, etc. The Industrial AI Data Foundry will be the critical mass investment that is expected to form connections to the wider AI community and research and innovation ecosystem. Its mission is to drive research and education activities and objectives in either AI for real data or AI for scientific and engineering research. Students will learn how to harness the power of Industrial AI to gain insights into the invisible relationship of the operation conditions and further use that insight to optimize the uptime, productivity, and efficiency of their operations. In terms of predictive maintenance, Industrial AI can detect incipient changes in the system and predict the remains useful life, and further optimize maintenance tasks to avoid disruption to operations.
The goal of industrial AI Data Foundry is to make data available to researchers, analysts, developers, and other interested parties (including industry and government agencies) for the purpose of facilitating research, innovation, and discovery. We are aimed to collect and share 100 datasets (i.e., four key AI domains: manufacturing, new energy, transportation, and healthcare) to help researchers understand different manufacturing industrial AI applications, such as virtual metrology, digital twin, cyber-physical systems, intelligent maintenance systems for mechanical components, and sensory systems. Also, the industrial AI center provides technical training materials to train engineers who can contribute to upgrading industry technology.
