Process parameter optimization for metal additive manufacturing: experimentation

Metal additive manufacturing is a promising manufacturing technique that has attracted attentions in the recent years due to the ability to manufacture complex parts. During the process, metal goes through complex thermal treatment, which causes defects such as porosity and lack of fusion in the final part. Understanding the relationship between process parameters and parts’ final quality is the key to achieve consistent zero-defect parts. This can be done by performing experiments and deriving the mathematical relationship between the process parameters and parts’ final quality. After finding the relationship, optimization can be done to find the optimized process parameters that lead to zero-defect parts. Being able to optimize the process will help designers and manufacturers to have parts that have not only complex geometries but consistent and superior quality.

Faculty Supervisor:

Gary Wang

Student:

Partner:

University of Tampere

Discipline:

Engineering

Sector:

Advanced Manufacturing; Artificial Intelligence; Other

University:

Simon Fraser University

Program: