Effects of Defects within Metal Additive Manufacturing Systems
Navy STTR 2018.A - Topic N18A-T013
NAVSEA - Mr. Dean Putnam - dean.r.putnam@navy.mil
Opens: January 8, 2018 - Closes: February 7, 2018 (8:00 PM ET)


TITLE: Effects of Defects within Metal Additive Manufacturing Systems


TECHNOLOGY AREA(S): Materials/Processes

ACQUISITION PROGRAM: Cross Platform Systems Development (CPSD) Research & Development (R&D) Program

OBJECTIVE: Develop and demonstrate an empirical database of allowable process defects and variations to aid quality control and nondestructive evaluation of additively manufactured metal components.

DESCRIPTION: Additive manufacturing (AM) systems, especially metal AM, bring revolutionary capabilities, but suffer from a lack of understanding of the defects that exist within the components.  Developing a database of the effects of defects, such as mechanical performance and material properties within an additively manufactured component, will provide a means of certifying these components at a more rapid rate without having to perform traditional “brute force” type methods of destructively testing large numbers of components.  Current commercial efforts to quantify the effects of defects on additively manufactured components focus on this sort of brute force testing, with an emphasis on expensive micro computed-tomography imaging and extensive destructive testing in order to qualify a printed component.  The database developed during this project will provide a faster response manufacturing capability to the Navy with increased flexibility.

The Naval fleet suffers from long lead times to obtain replacements for broken, worn, or otherwise failed parts. AM technology has the potential to reduce supply chain issues and enable new designs through unique layer-by-layer fabrication capabilities.  The significant advance in AM technology recently has been demonstrated in the private sector – the most visible recent example being General Electric’s LEAP Turbine Engine fuel nozzle, where an assembly of dozens of components was reduced to a single printed part and qualified by extensive destructive testing, but no existing commercial database is available as a product.

To enable the Navy to harness metallic AM capabilities for end-use items, the ability to identify the effects of defects within additively manufactured components is critical.  Parts manufactured by metal AM typically suffer from a combination of several defect types that can inhibit the functional performance of a part, and reduce confidence in designing parts for this manufacturing method.  A system for quantifying the effect of defects on printed parts is desired.  As defined by MIL-STD 2035A, such defects can be porosity, inclusions, large-scale voids, and chemical inconsistencies, and all of these can affect the mechanical performance and material properties of a printed component.

The desired system would quantify the effect of these various defects, establish an allowable defect frequency for printed parts, and be applicable across multiple material types and AM systems, especially laser and electron beam powder bed fusion as well as directed energy deposition.

The desired system’s performance goals would be to:
(1) Provide a method for nondestructively locating and classifying defects within a printed part quickly, with minimum technician support required, and with a minimum of specialized equipment (without having to test every component using microcomputer tomography (Micro CT);
(2) Quantify the effects of multiple defect types on the mechanical performance and material properties of printed parts. Defect types of interest are Small voids (particularly due to lack of fusion or vector spacing/path direction); Inclusions (powder contamination or powder size inconsistency leading to unfused material); Large voids (powder short-feeds, powder collapse, or other print errors); Chemical inconsistencies (powder contamination, carbide formation, grain structure);
(3) Provide a database of permissible defect sizes, distributions, densities, or other allowable metrics for quality control (QC) pass/fail testing in multiple materials: 316SS, Commercially Pure (Grade 2) Titanium, IN625, IN718, and 17-4PH;
(4) Provide an end-to-end system demonstration, including a NAVSEA-selected part printed in one of the above materials, to demonstrate successful application of the developed testing method and material database.

Emphasis should be placed on a solution(s) that successfully achieve(s) the listed objectives, while minimizing cost/complexity (not relying solely on processes like microcomputer tomography (CT), etc.), especially those that do not require extensive mechanical test specimens to be printed alongside the final part, and those that do not require highly specialized testing for the final part.  Advanced test methods are welcome, but attention should be paid to testing and calibration costs.  Development of the material database is expected to include complex and highly specialized testing – the goal of the project should be to build a database so that those same tests are not required on every part after the database is developed.

By providing a database to reduce cost and time to qualify an additively manufactured metal component, maintenance costs can be substantially reduced. Increased confidence and understanding of mechanical performance from parts produced by metal additive manufacturing, candidate parts can be more quickly selected.  Improved quality control means that replacement parts and tools can reach the fleet sooner, increasing system availability, reducing maintenance and downtime costs, and improving mission and warfighter flexibility by 20%.

PHASE I: Develop a concept method to determine the effect of defects on printed mechanical test specimens in one material, and use the data collected by executing their planned experiments to develop the framework for the larger material database.  Develop a program plan and structure to conduct print testing using their method on multiple materials in Phase II.  The Phase I Option, if awarded, will include the initial design specifications and capabilities description to build a prototype in Phase II.  Develop a Phase II plan.

PHASE II: Based on the Phase I results and the Phase II Statement of Work (SOW), design, develop, and deliver a prototype framework database.  In Phase II, testing to collect the necessary data to develop the final mechanical database in multiple materials will be performed, and the database and set of design allowable for each material will be assembled.  The project team will also develop a plan to demonstrate the complete system on a NAVSEA-provided part in Phase III.

PHASE III DUAL USE APPLICATIONS: Support the Navy in transitioning the technology to Navy use, especially in the regional maintenance centers and warfare centers.  Phase III serves as a complete, end-to-end systems demonstration for the method developed in Phases I and II.  Using a part(s) provided by NAVSEA, the team will print and qualify the part(s) using their process, and provide a report on the results of their testing.

A reliable, fast, and low-cost empirical database for QC in additively manufactured metal components is applicable in multiple industries, especially the aerospace and automotive sectors, where qualification efforts to date have been primarily brute force efforts.  By providing a database by which printed parts can be quickly confirmed as meeting some minimum set of operational criteria, significant cost reduction in metal AM is possible.  Part cost reduction is always a goal of manufacturers, and would make the system developed under this SBIR/STTR attractive to private-sector organizations.


1. “NONDESTRUCTIVE TESTING ACCEPTANCE CRITERIA,” MIL-STD-2035A (SH) 15 MAY 1995, http://everyspec.com/MIL-STD/MIL-STD-2000-2999/MIL-STD-2035A_6636/

2. Bauereiß, A., Scharowsky, T., & Körner, C.  “Defect generation and propagation mechanism during additive manufacturing by selective beam melting.” Journal of Materials Processing Technology, 2014, 214(11), 2522-2528. http://www.sciencedirect.com/science/article/pii/S0924013614001691

3. Gong, H., Rafi, K., Gu, H., Starr, T., & Stucker, B.  “Analysis of defect generation in Ti–6Al–4V parts made using powder bed fusion additive manufacturing processes.” Additive Manufacturing, 2014, 1, 87-98. http://www.sciencedirect.com/science/article/pii/S2214860414000074

KEYWORDS: Metal Additive Manufacturing; Quality Control for Additive Manufacturing; Effect of Defects in Additive Manufacturing; Material Database; Material Performance in Additive Manufacturing; Part Qualification in Additive Manufacturing


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