Engineering Design Optimization

Typical Engineering Design Optimization Process

1. Defining Objectives: Identifying the goals and criteria that the design must achieve, such as maximizing strength, minimizing weight, or minimizing cost
2. Identifying Constraints: Considering limitations and requirements that must be adhered to, such as material properties, manufacturing capabilities, regulatory standards, or operational conditions
3. Formulating Mathematical Models: Developing mathematical representations of the design problem, including objective functions to be optimized and constraints to be satisfied
4. Exploring Design Space: Using algorithms to systematically search through the space of design variables to understand how varying the parameters affects the design’s performance
5. Evaluating Solutions: Assessing the performance of candidate designs against the specified objectives and constraints
6. Iterating and Refining: Iteratively refining the design based on the evaluation results, potentially revisiting and adjusting objectives, constraints, or design variables

Engineering design optimization can be applied to various stages of the design process, from conceptual to detailed design, and across different engineering disciplines, including mechanical, electrical, civil, aerospace, and others. It helps engineers make informed decisions, improve product performance, reduce development time and costs, and ultimately deliver better-engineered products or systems.

Benefits of Optimization

1. Improved Performance: Optimization enables engineers to enhance the performance of their designs by maximizing desired metrics such as efficiency, strength, or durability while minimizing undesirable factors like weight, cost, or energy consumption
2. Cost Reduction: Optimizing designs can lead to cost savings by reducing material use, minimizing manufacturing complexity, and streamlining production processes. This can result in lower manufacturing costs and overall project expenses.
3. Increased Reliability and Safety: Optimization can improve the reliability and safety of engineering systems by identifying and mitigating potential failure points and ensuring that designs meet or exceed relevant safety standards.
4. Faster Time to Market: By systematically exploring design alternatives and identifying optimal solutions, optimization can help accelerate the product development cycle bringing new products to market more quickly.
5. Informed Decision-Making: Optimization provides engineers with valuable insights into the design space, allowing them to understand trade-offs and make informed decisions based on quantitative data.
6. Customization and Tailoring: Optimization enables engineers to tailor designs to specific requirements or constraints, such as customer preferences or environmental conditions, resulting in more customized and tailored solutions.

Optimization Tools for Mechanical Simulation

• Ansys has tools for parametric optimization, shape optimization, and topology optimization.
• Parametric optimization is completed in Ansys optiSLang.
• Shape optimization and topology optimization are handled by the Structural Optimization tool in Ansys Mechanical.

Parametric Optimization in optiSLang

Ansys optiSLang is a tool specifically designed for multidisciplinary optimization and robustness evaluation. Ansys optiSLang integrates with simulation tools to automate the optimization process and enable engineers to efficiently explore design alternatives, identify optimal solutions, and evaluate design robustness under uncertainty.

A typical parametric optimization workflow in optiSLang includes:

1. Integration with Simulation Tools
2. Parameterization of Simulation Models
3. Definition of Objectives and Constraints
4. Sensitivity Study
5. Optimization
6. Robustness Evaluation
7. Optimization Results Visualization and Interpretation

By leveraging Ansys optiSLang, engineers can streamline the design optimization process, accelerate product development cycles, and ultimately deliver more robust and efficient engineering solutions.

Parametric, Shape, and Topology Optimization Examples and Case Studies