International Conference on Engineering Design and Simulation using Data Mining
(ICEDSDM-27)

This track focuses on the latest methodologies in predictive modeling that enhance engineering design processes. Participants will explore case studies demonstrating the integration of predictive analytics in design workflows.

This session will delve into innovative data mining techniques that facilitate the integration of Computer-Aided Design and Computer-Aided Engineering. Discussions will highlight the impact of these techniques on design efficiency and accuracy.

This track aims to showcase data-driven strategies for optimizing engineering processes. Presentations will cover various optimization algorithms and their applications in real-world engineering scenarios.

This session will explore the role of design analytics in extracting actionable insights from engineering data. Attendees will learn about tools and methodologies that enhance decision-making in design.

This track focuses on the use of virtual prototyping and simulation in the engineering design process. Participants will discuss advancements in simulation technologies that improve product development cycles.

This session will investigate the applications of machine learning in various aspects of engineering design. Case studies will illustrate how machine learning algorithms can enhance design accuracy and efficiency.