Date of Award


Degree Name

MS in Industrial Engineering


Industrial and Manufacturing Engineering


College of Engineering


Xuan Wang

Advisor Department

Industrial and Manufacturing Engineering

Advisor College

College of Engineering


The world of additive manufacturing revolves around speed and repeatability. Inherently, the process of 3D printing is plagued with variability that fluctuates with every material and parameter modification. Without proper qualification standards, processes can never become stable enough to produce parts that may be used in aerospace, medical, and construction industries. These industries rely on high quality metrics in order to protect the lives of those who may benefit from them. To establish trust in a process, all points of variation must be controlled and accounted for every part produced. In instances where even the best process controls are enacted, there still may be situational unknowns that can cause detrimental defects, often on micron scales.

Through in-situ monitoring techniques, such as visual or acoustic monitoring, a secondary level of quality assessment can be performed. This type of real time monitoring solution can be used in a variety of ways to help reduce scrap rate, increase overall quality, and improve the mechanical characteristics of a newly developing material. In this proposal, a goal was set to develop a system that can be a low-cost alternative to a comparable acoustic monitoring system. This design is meant to be a low fidelity concept that can alert a user of any potential anomalies within a build by detecting spikes in acoustic emissions.

The overall success of this experiment is set on two conditions. First, the new low-cost system should be mountable on various types of machines. Second, this system should demonstrate some level of equivalency to a similar system. These two situations were successfully met as the system was able to provide indications of anomalies present within a build. The system was calibrated and tuned to be able to measure signals on a SLM 125 running 316L powder. Minor modifications to the code and system can make it adaptable to different types of equipment such as CNC’s, bandsaws, casting processes, and other advanced manufacturing equipment. The model can be attenuated to support higher or lower frequencies as well as different types of acoustic sensors, which demonstrates the vast potential that this system can provide for detecting different types of defects.