Session: 10-07-01: Problem Solving Techniques in Engineering and Technology Education, Research Methodologies, Practice, Workshops and Seminars

Paper Number: 173302

A Modular Courseware for Engineering Problem Solving 

We present a curriculum module on “Engineering Problem Solving”, a multidisciplinary and systematic framework for addressing complex, real-world engineering problems. Centered around dynamic systems and computational modeling, this module introduces students to core problem-solving strategies, including requirements analysis, systems decomposition, and iterative solution development. It fosters a mindset of structured inquiry by guiding learners through the process of translating real-world challenges into solvable engineering models using industry-relevant software tools.

 

At the heart of the module is the integration of programming, analysis, and model-based design, which enables students to visualize, simulate, and interrogate system behaviors in a virtual environment (MATLAB and Simulink). Learners derive system requirements (Requirement Toolbox), create system architecture (System Composer), and model physical systems (Simscape) within an integrated environment for better traceability and validation. These tools support a workflow where students evaluate design constraints, define system boundaries, and refine solutions using simulation-based feedback. The emphasis on virtual experimentation reduces physical risk while accelerating understanding of system-level dynamics such as transient responses, steady-state behavior, and component interdependencies.

 

The main project of this module focuses on solving a problem related to the development of a delivery drone, including activities like battery selection and automatic code generation for hardware integration. This project encourages students to apply their skills to diverse engineering contexts. These challenges not only demonstrate the versatility of dynamic system modeling but also reinforce iterative decision-making and trade-off analysis. With each project, learners practice defining objectives, constructing virtual models, running simulations, and interpreting results to improve performance and reliability.

 

Moreover, the module cultivates the ability to communicate technical findings effectively, promoting collaboration and engineering judgment. The modeling techniques presented serve as powerful tools for prototyping, diagnostics, and performance evaluation in complex systems. In doing so, students practice both domain-specific and cross-disciplinary problem-solving, preparing them for real-world engineering roles that demand agility and rigor. This module equips students with a holistic toolkit for solving complex problems, where dynamic modeling and simulation act as both a lens for understanding and a platform for innovation. Through this system-thinking approach, learners gain the confidence and capability to analyze, model, and optimize engineered systems in a virtual setting—bridging theory and application with precision and creativity.

 

Although the techniques and methods are mainly based on the standard industry practices of Model-Based Design (MBD) and Model-Based Systems Engineering (MBSE), they are accessible to first and second-year engineering students and can be used as a primer for any engineering design courses. The course materials are publicly available for educators to use and adopt for their courses.

 

Presenting Author: Mehdi Vahab MathWorks

Presenting Author Biography: Mehdi Vahab is the Academic Manager for Mechanical and Aerospace Engineering at MathWorks. He assists researchers, faculty, and students with their research and teaching challenges by collaborating and consulting to find more effective and accessible solutions. During his academic career, he has worked on modeling and simulation of multi-physics systems, especially fluid mechanics, heat transfer, and phase-change dynamics.

Authors:

Chad Allie MathWorks
Mehdi Vahab MathWorks