“Generic Digital Twin Development Framework for Enhancing Energy Efficiency and Flexibility in Industrial Production Processes”: PhD defense by Daniel Anthony Howard

In today's changing energy landscape, industries face challenges embracing energy-efficient and flexible practices. Many are unaware of potential savings, while complex production setups make predicting impacts challenging.

To tackle these hurdles, Daniel presented the “Generic Digital Twin Development Framework for Enhancing Energy Efficiency and Flexibility in Industrial Production Processes” based on his PhD research. The proposed framework consists of six layers that gather data, analyze it, and create digital twin solutions in alignment with business objectives and strategies.

A diverse set of real-world case studies, including horticulture, meat processing, brewing, and a foundry, proved the framework's adaptability across industries. Daniel showcased how the framework could effectively identify potential energy efficiency and flexibility impacts in the various case studies.

Through the case studies, Daniel verified the framework as a structured approach for digital twin development across industrial domains to examine the impacts of energy efficiency and flexibility. By employing the framework for digital twin development, Daniel showed how industries could make informed decisions when diving into energy efficiency and flexibility.