ENBIS 2021 Spring Meeting

Session

AI applications

2.3.2

18 May 2021, 13:00

Online

Conveners

AI applications

• Shirley Coleman (Newcastle University)

71. Artificial Intelligence-based Autonomous Control for Process Industry Improvement: A Case Study for Chemistry Control for Tissue Mill

Kamran Paynabar (ProcessMiner)

18/05/2021, 13:00

Data Science in Process Industries

Problem/Challenge: The goal of this project was to autonomously control a part of a tissue mill’s continuous manufacturing process using artificial intelligence and predictive analytics to reduce raw material consumption while maintaining the product quality within the specification limit. The project objective was to overcome the challenge within the operator’s ability to act quickly with...

48. Modeling and forecasting fouling in multiproduct batch processes

Joel Sansana (University of Coimbra)

18/05/2021, 13:20

Data Science in Process Industries

In the chemical process industry (CPI), it is important to properly manage process and equipment degradation as it can lead to great economic losses. The degradation dynamics are seldom included in modeling frameworks due to their complexity, time resolution and measurement difficulty. However, tackling this problem can provide new process insights and contribute to better predictive...

57. Predictive Control Charts (PCC): A Bayesian Approach in Online Monitoring of Short Runs

Konstantinos Bourazas (Athens University of Economics and Business)

18/05/2021, 13:40

Data Science in Process Industries

Performing online monitoring for short horizon data is a challenging, though cost effective benefit. Self-starting methods attempt to address this issue adopting a hybrid scheme that executes calibration and monitoring simultaneously. In this work, we propose a Bayesian alternative that will utilize prior information and possible historical data (via power priors), offering a head-start in...