Open PhD Defense Daniel Guzman Vargas

Daniel's open PhD Defense

We are pleased to invite you to the public defense of Daniel Guzman Vargas' doctoral dissertation on “Towards a Digital Twin Framework for Integrated Production Planning and Scheduling in Reconfigurable Manufacturing Systems.”

🗓️ Date: Thursday 28th of August 2025.
🕔 Time: start at 13:50.
📍 Location: Auditorium 1, iGent, first floor, Technologiepark Zwijnaarde 126, 9052.
🗣️ Spoken language: English.

A reception will follow. For catering purposes, please confirm your attendance via this form by August 15, the latest.

We are looking forward to welcoming you there!

Towards a Digital Twin Framework for Integrated Production Planning and Scheduling in Reconfigurable Manufacturing Systems

Modern manufacturing companies are faced with increasing competition, market volatility, and a growing demand for customized products. Reconfigurable Manufacturing Systems (RMSs) have emerged to provide the necessary flexibility to meet these challenges. However, effectively managing these complex systems requires an integrated approach to production planning and scheduling, something traditional methods often fail to provide in the timely manner required by Industry 4.0.

Daniel's doctoral research addresses this critical gap by proposing a Digital Twin (DT) framework designed to enable responsive, integrated decision-making for RMSs. The core of his work is the development of a novel Responsive Decision-Making Support (RDMS) framework, which is designed to provide fast and efficient solutions to the Integrated Production Planning and Scheduling (IPPS) problem in real-world industrial settings.

Rather than relying on slow conventional optimization, the proposed method uses fast-to-evaluate surrogate models to predict the performance of optimal plans and schedules. This approach allows for the rapid evaluation of numerous scenarios, identifying high-quality, integrated solutions that enhance system agility and responsiveness.

Ultimately, his work provides a pathway toward more agile, efficient, and resilient manufacturing operations, bridging the gap between advanced optimization theory and the practical needs of smart factories in the Industry 4.0 era.