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Additive Manufacturing Sensor Fusion Technologies for Process Monitoring and Control.

Award Information
Agency: Department of Defense
Branch: Defense Logistics Agency
Contract: SP4701-18-P-0116
Agency Tracking Number: L18A-001-0010
Amount: $100,000.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: DLA18A-001
Solicitation Number: 2018.0
Solicitation Year: 2018
Award Year: 2018
Award Start Date (Proposal Award Date): 2018-09-19
Award End Date (Contract End Date): 2019-03-18
Small Business Information
555 Quince Orchard Road
Gaithersburg, MD 20878
United States
DUNS: 960861958
HUBZone Owned: No
Woman Owned: Yes
Socially and Economically Disadvantaged: No
Principal Investigator
 Arnab Gupta
 (301) 355-0488
Business Contact
 Jennifer Duan
Phone: (301) 200-8368
Research Institution
 University of Dayton Research Institute
 Claudette Groeber
300 College Park Ave
Dayton, OH 45469
United States

 (937) 229-2919
 Domestic Nonprofit Research Organization

Additive Manufacturing (AM) is a modern and increasingly popular manufacturing process for metallic components, but suffers from well known problems of inconsistent quality of the finished product. Process monitoring and feedback control are therefore crucial research areas with a goal of solving this problem. To address this concern, X-wave Innovations, Inc. (XII) and the University of Dayton Research Institute (UDRI) propose to develop an advanced sensor fusion system for monitoring and feedback control of AM processes. The project will be supported by extensive experiments where test components of varying quality will be created using an AM setup by varying different process variables. Process parameter data, along with quality rating of the final product, will be acquired using several different third party sensors. The input data will be used for latent class analysis (LCA) and logistic regression modeling, for classification and feedback regarding the manufacturing quality. A feedback control system will also be developed using the sensor fusion technology to update process variables during manufacture. Upon completion, this technology is expected to be applicable to a wide variety of AM processes for improved efficiency and reduced rejected components due to inferior quality.

* Information listed above is at the time of submission. *

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