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Direct Performance Evaluation of Additive Manufacturing Process Plans

Award Information
Agency: Department of Commerce
Branch: National Institute of Standards and Technology
Contract: 70NANB20H115
Agency Tracking Number: 038-FY19-73 (PII)
Amount: $400,000.00
Phase: Phase II
Program: SBIR
Solicitation Topic Code: 9.0
Solicitation Number: 2020-NIST-SBIR-02
Timeline
Solicitation Year: 2020
Award Year: 2020
Award Start Date (Proposal Award Date): 2020-09-15
Award End Date (Contract End Date): 2022-09-01
Small Business Information
211 S Paterson St., Ste 350, Madison, WI, 53703
DUNS: 849711880
HUBZone Owned: N
Woman Owned: N
Socially and Economically Disadvantaged: N
Principal Investigator
 Goldy Kumar
 (608) 334-9646
 gkumar@intact-solutions.com
Business Contact
 Goldy Kumar
Phone: (608) 334-9646
Email: gkumar@intact-solutions.com
Research Institution
N/A
Abstract
Additive manufacturing is steadily advancing towards fulfilling its promise of customized and on-demand production of functional parts. However, performance of as-manufactured parts can differ significantly from the as-designed parts because the as-manufactured geometry differs from the as-designed geometry and the as-manufactured material properties are unknown. Attempts to predict performance of as-manufactured parts are hampered by the complexity of the as-planned geometry and the unknown material properties. In Phase I, Intact Solutions successfully demonstrated the feasibility of performing accurate structural simulation directly from AM plans while querying material information directly from NIST’s AMMD. This was achieved by extending our moment-based interoperable simulation technology that incorporates material properties through a combination of analytical, experimental, and data-driven methods.In Phase II, we will develop a novel Part-Scale Process–Structure–Property–Performance (PSPP) architecture and implement a robust commercial grade system for performance prediction of AM parts. The developed system will support adaptive exploration of process and design spaces through direct integration with AM material databases, as well as simulated data. In addition to rigorous validation and testing, we will demonstrate how our system can be used to evaluate, compare, and optimize AM process plans, leading to significant savings and improved performance.

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

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