Research Programs

Development of an Electronic Data Base for Rapid Selection of Aluminum Die Casting Alloys

Industrial Partners:

Kennedy Die Casting Inc.

Research Team:

Dr. Libo Wang
Prof. Diran Apelian
Prof. Makhlouf Makhlouf

The objective of this project is to create an electronic design tool by which the users can input the requirements for performance of die castings and get the needed alloy chemistry, and vice-versa. The electronic database is being created within an electronic design tool that limits variation in specifications and consequently variation in performance of die-casting alloys. The tool enables procurement agents to better procure a better product at the lowest cost and with the shortest possible lead-time. It will also help die casting designers and casters in selecting the appropriate alloys quickly and economically, as well as in tailoring and optimizing the alloys they select or use.

Implementing an electronic tool kit for the selection of aluminum die casting alloys will have a significant impact on the metal casting industry. This will be realized by reducing scrap due to non compliance of metal quality resulting in components not meeting performance requirements, and thus reducing scrap, reducing lead time, reducing quoting risk and reducing total costs.

There are three major phases to this project:

Phase 1 - Development of the electronic design tool kit

The tasks in Phase 1 are:

Build chemistry/properties database for aluminum die casting alloys
Develop trend equations between chemistry and performance
Construct the electronic design tool
Alpha test the initial design tool at Kennedy Die casting and subsequently expand to ACRC member companies

Phase 2 - Enhancement of the tool kit and development of a robust design tool

The tasks in Phase 2 are:

Enhance the design tool kit
Perform Beta site tests
Expand the data set

Phase 3 - Establishment of a standardized set of alloy chemistry/performance indices

The North American Die Casting Association (NADCA) will market the electronic design tool and the accompanying database once they are completed and tested.

Prediction: Properties to Chemistry based on Trend Equations

Selection: "Chemistry to Properties" from NADCA Data