Currently, Industry 4.0 concepts are being applied to pharma industry to achieve Pharma 4.0 paradigm. Pharma 4.0 reduces the time and resources needed for continuous pharmaceutical manufacturing and also improves the product quality and production consistency. It has many advantages but also have bigger challenges on the applications of artificial intelligence (AI)/machine learning (ML), material traceability, optimization, advanced process control, cyber-physical security, and data management side because of the different levels of complexities involved. The predictive capabilities and the quality of the pharmaceutical products can be improved significantly via employing the artificial intelligence and the advanced model predictive control (MPC) system if an appropriate cyber-physical security defense is in place.
In this work, seven components of industry 4.0 namely artificial intelligence (AI)/machine learning (ML), modelling, material traceability, optimization, advanced control, cyber-physical security, and data science have been developed and implemented into the continuous pharmaceutical manufacturing process.
Learning Objectives:
Upon completion, participant will be able to develop the machine learning model, integrated flowsheet model, model predictive control system, cyber-physical security, and data management system.
Upon completion, participant will be able to understand Pharma 4.0 concepts.
Upon completion, participant will be able to develop and implement the control system in actual manufacturing pilot-plant.
Upon completion, participant will be able to optimize the feeder refill strategy.
Upon completion, participant will be able to understand RTD toolbox.