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A novel approach to obviousness: An algorithm for identifying prior art concerning 3-D printing materials

Paper ID Volume ID Publish Year Pages File Format Full-Text
37803 45634 2015 6 PDF Available
Title
A novel approach to obviousness: An algorithm for identifying prior art concerning 3-D printing materials
Abstract

•Rapid expansion of 3D-printing materials for consumers producing 3-D printed articles.•Open-source algorithm proposed for identifying prior art concerning 3-D printing materials.•Proposed algorithm narrows the search for 3-D printable materials with specific properties.•Prior art identified by proposed algorithm can invalidate innovation-restricting patents.•Potential ramifications on innovation and patent law in the 3-D printing discussed.

With the development and commercialization of the recyclebot (plastic extruders that fabricate 3-D printing filament from recycled or virgin materials) and various syringe pump designs for self-replicating rapid prototypers (RepRaps), the material selection available for consumers who produce products using 3-D printers is expanding rapidly. This paper provides an open-source algorithm for identifying prior art for 3-D printing materials. Specifically this paper provides a new approach for determining obviousness in this technology area. The potential ramifications on both innovation and patent law in the 3-D printing technological space are discussed.

Keywords
3-D printing; Additive manufacturing; Materials; 3-D printer filament; 3-D ink; Intellectual property; Prior art; Intellectual monopoly; Public domain; Open source; Open source materials; Libre
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A novel approach to obviousness: An algorithm for identifying prior art concerning 3-D printing materials
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Publisher
Database: Elsevier - ScienceDirect
Journal: World Patent Information - Volume 42, September 2015, Pages 13–18
Authors
,
Subjects
Physical Sciences and Engineering Chemical Engineering Bioengineering
Get Full-Text Now
Don't Miss Today's Special Offer
Price was $35.95
You save - $31
Price after discount Only $4.95
100% Money Back Guarantee
Full-text PDF Download
Online Support
Any Questions? feel free to contact us