Handling Frequent Design Changes by Automatic Optimization-Constrained Updates of Parametric CAD Models

Abstract

A common difficulty in designing mechanical systems is in handling the effects that design changes in one subsystem have on another, or on the system as a whole. This is made more difficult in early engineering design, when frequent changes are required and design information is preliminary. Increased efforts have been made to capitalize on the benefits of numerical optimization methods (search methods) in early engineering design – because of the large impact early decisions have on subsequent development activities. An important step toward executing meaningful optimizations in early design is the development of a design optimization framework that can be used when objectives, constraints, variables, and other conditions are expected to change as the design progresses and new information is gained. This paper presents a design framework that considers such change by subjecting the parametric updating of CAD models to optimization criteria. Under the proposed framework, a part is generically and parametrically modeled in a CAD system; when changes are made to the design of subsystems that interact with the part, the part is then automatically updated subject to design objectives and constraints. In this way, the updated part or subassembly satisfies system and subsystem level optimization criteria. Thus reducing the need for the designer to react to design changes in one subsystem by manually correcting the affected design of another. The proposed framework carries practical implications that are demonstrated in the development of a suspension rocker for a formula SAE car designed and built at Brigham Young University, resulting in a rocker weight savings of 18%.