
WeldANA: Welding Decision Support Tool for Conceptual Design
An efficient engineering design process is crucial to the success of a product, whereas inefficiencies in the process can cripple the product’s profitability through increased design time, cost, and time-to-market. A significant source of inefficiency in the design process can be attributed to designs that are not sufficiently manufacturable [1]. With a greater emphasis on design for manufacturability, costs can be greatly reduced as the design-to-manufacturing transition within the engineering design process becomes more efficient. This paper describes a decision support software tool created to aid design engineers in the early phases of design for a new product. The tool analyzes a computer aided design (CAD) model and provides the design engineer feedback on how easily the design could be completed as a weldment. Four metrics (partability, setup/orientation, accessibility, and preparation) are defined and used as a basis for determining the weldability of a design. A rating is given for the design for each metric. In addition to a rating, 3D graphical output is used to point out the areas of the design that present manufacturability concerns for a given metric. The use of this tool can greatly enhance the likelihood that design engineers produce more manufacturable designs, reducing the need for redesign later in the process. This paper will show two use cases to demonstrate that the tool can be used to iteratively improve a weldment from poor weldability to high weldability, and redesign a casting as a weldment with high weldability. Additionally, with a series of example parts, it will show how each use case is iteratively progressed from a part with poor weldability to a part with high weldability.
Files
Penn State Only
Files are only accessible to users logged-in with a Penn State Access ID.
Metadata
Work Title | WeldANA: Welding Decision Support Tool for Conceptual Design |
---|---|
Access | |
Creators |
|
Keyword |
|
License | All rights reserved |
Work Type | Research Paper |
Deposited | November 16, 2017 |
Versions
Analytics
Collections
This resource is currently not in any collection.