(61b) Liberation of Digitalization and Modeling

The fundamental building block for AI, ML, Simulation, Ind 4.0, and other sophisticated approaches is the DATA and the importance of its quality and availability (i.e. accessibility, cleanness, correctness, comprehensiveness, context, ..). However, this fundamental aspect mostly ignored, either the data is in silos, trapped in dispersed types and ELNs and vendor licensed platform, messy, noisy, incomplete, and so on. Although there have been different efforts in harmonizing the format, connectivity, and accessibility, still a sharable and customizable database and a collaborative platform (either for data governance or running models and simulation) is a big challenge.

The next step in utilization of data is to drive information and develop models that yield to enterprise value. The model sharing and deployment (democratization of modeling and simulation) is another challenging aspect that limits the models’ benefit. Technical team members cannot have access to models and always rely to M&S SMEs to run models. These gaps highlights the importance of crunchable data repository and platforms and models deploying and sharing tools across the enterprise in affordable and manageable manner.

In this presentation we will discuss on the data management (equipment, material, process) in different industries from R&D to post manufacturing and demonstrate some work arounds and solutions for data curation and running models across organizations. The case studies will be from different types of applications and organization, including a Gen-AI tool for digesting information and assisting user for recipe and process development. Democratization of numerical models and sharing models across stakeholders will be demonstrated on Cloud based and user friendly interfaces.