Category: AI

In batch manufacturing, optimizing processes for consistent yields and quality standards remains a top priority. Yet, the intricacies of batch operations often pose challenges in......

Our paper titled SMPL: Simulated Industrial Manufacturing and Process Control Learning Environments has recently been accepted by NeurIPS 2022, Datasets and Benchmarks Track. In this......

Machine learning and first principle models are two widely discussed approaches for process optimization nowadays. First principle models, which are also referred as dynamic models, have long been one...

The ‘Golden Batch’ is your ideal batch, the one that came out perfectly, the way you intended: the recipe is followed perfectly, and the process stays on course. The expectation is that once such ...

Modern process control algorithms are the key to the success of industrial automation. The increased efficiency and quality create value that benefits everyone from the......

We showed that when you are early in your digitalization journey where you only have access to manipulated variables (e.g. sugar feed rate) and the outcome (e.g. yield), you......

For many batch processes (e.g. in Life Sciences, Food & Beverage), the Design of Experiments (DoE) is usually conducted before scaling up to production...

In Part 1, we discussed simple Bayesian optimization (BO), and now we further exam BO by taking into account uncontrollable contextual information and constraints. 1.......

Bayesian optimization (BO) is a sample-efficient optimization method focused on solving the problem when the objective function f_0 is unknown or expensive to evaluate. At......

For industries like Life Sciences, it is challenging to collect a large amount of data with high quality that is needed for machine learning and autonomous control applic...