| Title: | Metallurgical and geometric properties controlling of additively manufactured products using artificial intelligence |
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| Authors: | ID Pal, Snehashis (Author)
ID Drstvenšek, Igor (Author) |
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| Files: |  ams_ams-202102-0001.pdf (1,46 MB)
MD5: CABAA35E310BB821A9B2D2BBCACEFA70
 https://www.actamechanica.sk/artkey/ams-202102-0001_metallurgical-and-geometric-properties-controlling-of-additively-manufactured-products-using-artificial-intelli.php
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| Language: | English |
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| Work type: | Article |
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| Typology: | 1.01 - Original Scientific Article |
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| Organization: | FS - Faculty of Mechanical Engineering
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| Abstract: | This article has presented a technical concept for producing precisely desired Additive
Manufactured (AM) metallic products using Artificial Intelligence (AI). Due to the stochastic
nature of the metallic AM process, which causes a greater variance in product properties
compared to traditional manufacturing processes, significant inaccuracies in metallurgical
properties, as well as geometry, occur. The physics behind these phenomena are related to
the melting process, bonding, cooling rate, shrinkage, support condition, part orientation.
However, by controlling these phenomena, a wide range of product features can be achieved
using the fabricating parameters. A variety of fabricating parameters are involved in the
metal AM process, but an appropriate combination of these parameters for a given material
is required to obtain an accurate and desired product. Zero defect product can be achieved
by controlling these parameters by implementing Knowledge-Based System (KBS). A suitable
combination of manufacturing parameters can be determined using mathematical tools with
AI, considering the manufacturing time and cost. The knowledge required to integrate AM
manufacturing characteristics and constraints into the design and fabricating process is beyond
the capabilities of any single engineer. Concurrent Engineering enables the integration of design
and manufacturing to enable trades based not only on product performance, but also on other
criteria that are not easily evaluated, such as production capability and support. A decision
support system or KBS that can guide manufacturing issues during the preliminary design
process would be an invaluable tool for system designers. The main objective of this paper is to
clearly describe the metal AM manufacturing process problem and show how to develop a KBS
for manufacturing process determination. |
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| Keywords: | metallurgical properties, geometry, additive manufacturing, artificial intelligence, knowledge-based system |
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| Publication status: | Published |
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| Publication version: | Version of Record |
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| Submitted for review: | 06.04.2021 |
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| Article acceptance date: | 11.04.2021 |
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| Publication date: | 25.06.2021 |
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| Publisher: | Acta Mechanica Slovaca |
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| Year of publishing: | 2021 |
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| Number of pages: | str. 6-13 |
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| Numbering: | Ročnik 25, 2 |
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| PID: | 20.500.12556/DKUM-90821  |
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| UDC: | 669:004.8 |
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| ISSN on article: | 1335-2393 |
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| COBISS.SI-ID: | 208773891 |
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| DOI: | 10.21496/ams.2021.015 |
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| Publication date in DKUM: | 25.09.2024 |
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| Views: | 137 |
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| Downloads: | 12 |
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| Metadata: |    |
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| Categories: | Misc.
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