Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
Impact Factor & Key Scientometrics

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
Overview

Impact Factor

1.671

H Index

58

Impact Factor

2.039

I. Basic Journal Info

Country

United Kingdom
Journal ISSN: 08900604, 14691760
Publisher: Cambridge University Press
History: 1987-ongoing
Journal Hompage: Link
How to Get Published:
Find out more

Research Categories

Scope/Description:

The journal publishes original articles about significant AI theory and applications based on the most up-to-date research in all branches and phases of engineering. Suitable topics include: analysis and evaluation; selection; configuration and design; manufacturing and assembly; and concurrent engineering. Specifically, the journal is interested in the use of AI in planning, design, analysis, simulation, qualitative reasoning, spatial reasoning and graphics, manufacturing, assembly, process planning, scheduling, numerical analysis, optimization, distributed systems, multi-agent applications, cooperation, cognitive modeling, learning and creativity. AI EDAM is also interested in original, major applications of state-of-the-art knowledge-based techniques to important engineering problems.

II. Science Citation Report (SCR)



Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
SCR Impact Factor

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
SCR Journal Ranking

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
SCImago SJR Rank

SCImago Journal Rank (SJR indicator) is a measure of scientific influence of scholarly journals that accounts for both the number of citations received by a journal and the importance or prestige of the journals where such citations come from.

0.413

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
Scopus 2-Year Impact Factor Trend

Note: impact factor data for reference only

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
Scopus 3-Year Impact Factor Trend

Note: impact factor data for reference only

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
Scopus 4-Year Impact Factor Trend

Note: impact factor data for reference only

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
Impact Factor History

2-year 3-year 4-year
  • 2023 Impact Factor
    2.359 2.382 2.411
  • 2022 Impact Factor
    2.343 2.472 2.546
  • 2021 Impact Factor
    2.039 1.92 1.872
  • 2020 Impact Factor
    2.108 2.063 1.921
  • 2019 Impact Factor
    1.625 1.634 1.7
  • 2018 Impact Factor
    1.182 1.221 1.426
  • 2017 Impact Factor
    1.19 1.423 1.664
  • 2016 Impact Factor
    1.253 1.472 1.428
  • 2015 Impact Factor
    1.266 1.319 1.361
  • 2014 Impact Factor
    1.243 NA NA
  • 2013 Impact Factor
    0.985 NA NA
  • 2012 Impact Factor
    1.476 NA NA
  • 2011 Impact Factor
    2.094 NA NA
  • 2010 Impact Factor
    1.714 NA NA
  • 2009 Impact Factor
    1.639 NA NA
  • 2008 Impact Factor
    1.288 NA NA
  • 2007 Impact Factor
    1.042 NA NA
  • 2006 Impact Factor
    1.132 NA NA
  • 2005 Impact Factor
    1.067 NA NA
  • 2004 Impact Factor
    0.776 NA NA
  • 2003 Impact Factor
    0.914 NA NA
  • 2002 Impact Factor
    0.65 NA NA
  • 2001 Impact Factor
    0.421 NA NA
  • 2000 Impact Factor
    0.569 NA NA
Note: impact factor data for reference only

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Impact Factor

Impact factor (IF) is a scientometric factor based on the yearly average number of citations on articles published by a particular journal in the last two years. A journal impact factor is frequently used as a proxy for the relative importance of a journal within its field. Find out more: What is a good impact factor?

III. Other Science Influence Indicators

Any impact factor or scientometric indicator alone will not give you the full picture of a science journal. There are also other factors such as H-Index, Self-Citation Ratio, SJR, SNIP, etc. Researchers may also consider the practical aspect of a journal such as publication fees, acceptance rate, review speed. (Learn More)

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
H-Index

The h-index is an author-level metric that attempts to measure both the productivity and citation impact of the publications of a scientist or scholar. The index is based on the set of the scientist's most cited papers and the number of citations that they have received in other publications

58

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM
H-Index History

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