Automated Ideation in CAD: From Prior Art to Novel Concepts

Category: Modelling · Effect: Strong effect · Year: 2019

Leveraging TRIZ principles within a CAD framework can automate the generation and evaluation of design concepts from existing models.

Design Takeaway

Designers can explore integrating TRIZ principles and computational tools into their ideation workflows to systematically generate and evaluate novel design concepts from existing product data.

Why It Matters

This approach can significantly accelerate the early stages of the design process, moving beyond manual modification of existing designs to systematically explore novel solutions. By integrating ideation with CAD and decision-making tools, design teams can more efficiently identify and develop high-value concepts.

Key Finding

A new computational method has been developed that uses existing 3D CAD models and the Theory of Inventive Problem Solving (TRIZ) to automatically generate and evaluate new design ideas, presenting them as CAD models.

Key Findings

Research Evidence

Aim: Can TRIZ principles be integrated with CAD and Multi-Criteria Decision Making (MCDM) to automate the ideation and concept development stage, transforming existing 3D CAD models into novel design concepts?

Method: Computational Modelling and Algorithmic Design

Procedure: The method involves creating a function model from a prior art CAD design, simplifying it to generate new function models, and then using MCDM to quantitatively evaluate and select the most promising new designs. This is supported by an automated CAD model complexity reduction technique.

Context: Computer-Aided Design (CAD) software development and engineering design processes.

Design Principle

Systematic innovation can be achieved by applying structured problem-solving methodologies (like TRIZ) within digital modelling environments to generate and evaluate design alternatives.

How to Apply

Develop or utilize CAD plugins that incorporate TRIZ tools to suggest design modifications or generate variations based on an initial model. Implement MCDM frameworks to objectively compare generated concepts.

Limitations

The effectiveness of the automated ideation is dependent on the quality of the input model and the TRIZ principles applied. The MCDM process requires careful definition of criteria and weights.

Student Guide (IB Design Technology)

Simple Explanation: This research shows how computers can help designers come up with new ideas for products by looking at old designs and using clever problem-solving rules.

Why This Matters: It demonstrates how computational tools and structured methodologies can enhance creativity and efficiency in the early stages of design, leading to more innovative and potentially cost-effective solutions.

Critical Thinking: To what extent can automated ideation truly replicate or surpass human creativity and intuition in design?

IA-Ready Paragraph: The research by Efimov-Soini (2019) presents a novel approach to automating the ideation stage in computer-aided design by integrating TRIZ principles with CAD and Multi-Criteria Decision Making (MCDM). This methodology transforms existing 3D CAD models into new design concepts by analyzing their functional models and generating innovative variations, offering a systematic pathway to explore novel solutions and potentially reduce development time and costs.

Project Tips

How to Use in IA

Examiner Tips

Independent Variable: Integration of TRIZ principles, CAD modelling framework, and MCDM procedure.

Dependent Variable: Number and quality of generated design concepts, efficiency of the ideation process.

Controlled Variables: Input CAD model of prior art design, defined TRIZ principles, MCDM criteria.

Strengths

Critical Questions

Extended Essay Application

Source

Ideation Stage in Computer-Aided Design · LUTPub (LUT University) · 2019