March 2024

Mohammad Anas Wahaj | 19 mar 2024

Design of new part, component, or assembly requires consideration of fit, form and function and also innovation and aesthetic. Design reuse is an important aspect where existing designs are utilized. Computer aided design (CAD) and product data management (PDM) enabled use of existing similar designs available within the engineering organization, while engineering design search engines enabled finding them in broader internet ecosystem. Moreover, software driven engineering design optimization tools that proved optimal and efficient designs. One such tool was Topology Optimization in which the algorithm reduced the maerial in a design object. These processed and tools evolved into Generative Design that utilizes AI technologies like Deep Generative Models (DGMs) a form of Machine Learning and Neuro-Symbolic AI. The algorithms now create innovative designs with many options and possibilities that satisfy specified fit, form, and functional requirements including manufacturability. AI-Driven Generative Design develops, optimizes, and assesses design possibilities, and reduces repetitive tasks, multiple calculations, optimal design search etc for designers and helps them focus on problem-solving and innovation. Traditional design process includes ideation and conceptualization, creation, redefining and ehhancing the design, validating and building. This process is linear and even the use of CAD and CAE tools are not sufficient and require high level of expertise. AI-driven generative design improves on this process and significantly shortens the product design lifecycle. Generative design enables the designer to set performance and prioritize parameters and the algorithm generates a menu of alternatives to consider. In terms of the product development lifecycle, generative design is a combination of AI, CAD, simulation and test (CAE), and topology optimization, all working in conjunction, Additive manufacturing (AM) is an area where generative design is having an impact. In this process 3D printing is utilized to provide ouput parts that meets very specific functional requirements. The each phase of AM lifecycle process can be driven and enhanced by AI technology. Read on...

ARC Advisory Group: Understanding the Role of AI in Generative Engineering Design
Author: Dick Slansky