Research Seminar: Optimization and Data-Driven Methods for Intelligent Manufacturing

Content

Abstract: This talk demonstrates how optimization and data-driven methods enhance and transform intelligent manufacturing and logistics through three selected real-world cases.

(1) Additive Manufacturing: We show how in-situ process monitoring data can be leveraged to predict part quality and optimize machine parameter selection in additive manufacturing.

(2) Energy Orchestration: To support the integration of renewable energy in manufacturing, digital tools are developed for production scheduling while taking into consideration multi-source renewable capacity and time-of-use pricing.

(3) Resilient Transportation Networks: We explore how resilience can be built into transportation systems, particularly in highly congested environments, through timetabling optimization and the evaluation of critical hotspots and their impact on overall network performance.

These cases demonstrate the role that optimization and analytics play across various stages of manufacturing, including product development, operations planning, and system-wide management.