Course Highlights
- Gain insights into the principles and applications of engineering analysis and optimization.
- Learn how to collect, analyze, and interpret engineering data for decision-making.
- Understand the fundamentals of mathematical modeling and its relevance to engineering problems.
- Explore optimization techniques, including linear programming, nonlinear programming, and multi-objective optimization.
- Discover decision analysis methods and how to make decisions under uncertainty.
- Learn simulation and modeling techniques for understanding and improving system performance.
- Gain knowledge of design of experiments and its role in process improvement.
- Understand the principles of process improvement methodologies such as Lean Six Sigma.
- Explore reliability analysis and maintenance optimization to enhance system performance and minimize downtime.
- Get an introduction to Finite Element Analysis (FEA), Computational Fluid Dynamics (CFD), Boundary Element Method (BEM), and other analysis methods.
- Engage in real-world case studies and practical applications to reinforce learning.
Course Objectives
- Understand the significance of engineering analysis and optimization in managerial decision-making.
- Apply data analysis techniques to interpret and utilize engineering data effectively.
- Formulate and solve mathematical models to address engineering problems.
- Apply optimization techniques to improve system performance and resource utilization.
- Make informed decisions under uncertainty using decision analysis methods.
- Utilize simulation and modeling techniques for system analysis and improvement.
- Design and conduct experiments for process improvement and optimization.
- Apply process improvement methodologies, such as Lean Six Sigma, to enhance efficiency.
- Analyze and optimize system reliability and maintenance strategies.
- Gain an overview of analysis methods like FEA, CFD, BEM, and their applications in engineering.
Course Prerequisite
To derive maximum benefit from the “Engineering Analysis & Optimization for Managers” course, it is recommended that participants have a basic understanding of engineering principles and terminology. While no specific technical background is required, familiarity with concepts such as mathematics, statistics, and basic problem-solving methods will be advantageous. Additionally, a working knowledge of spreadsheet software and data analysis tools will be helpful for certain modules. The course is designed to cater to managers and professionals from diverse backgrounds who are involved in decision-making and process optimization in engineering or related fields.