Home›Search›Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM

Cambridge University Press · United Kingdom

ISSN0890-0604eISSN1469-1760
SJR Q2✓ WOS SCIE✓ Scopus / SJR
90
/ 100
High Trust
PubScope credibility score from verifiable indexing & ethics signals
Score Breakdown
◆ WoS flagship (SCIE/SSCI/AHCI)78
✓ Corroboration (2 more)+12
Total90
Level data: Norwegian Register (HK-dir), NLOD 2.0. · Third-party records · how this is calculated · Report an error →
⚡ Speed vs Prestige
How does this journal balance review speed with impact level?
Publication speed: not measurable
publisher doesn’t disclose per-article submission dates — we never estimate
Q2
SJR Rank
Top 50% in field
Impact Factor & Quartile · Web of Science (JCR)

✓ Indexed in the Web of Science Core Collection (SCIE) — Clarivate publishes an official Journal Impact Factor and JCR quartile for this journal.

See the official Impact Factor & quartile on the journal’s page ↗

The Impact Factor & JCR quartile are licensed by Clarivate — we link you to the official source instead of reprinting a number that can go out of date. Open metrics below: SCImago Q2. Source: Clarivate Journal Citation Reports.

SJR Scorei
0.447
H-Indexi
69
CiteScore
View ↗
Scopus metric · on the journal’s page
SNIPi
0.942
Total Worksi
1,392
Total Citationsi
23,634
2yr Mean Citednessi
2.24
Open Impact Factor alternative

Aims & Scope

Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AI EDAM) is a journal that publishes original research papers on the application of artificial intelligence techniques to engineering design, analysis, and manufacturing. The journal covers a wide range of topics, including knowledge-based systems, expert systems, machine learning, neural networks, fuzzy logic, genetic algorithms, and other AI methodologies applied to engineering problems. AI EDAM aims to bridge the gap between AI research and its practical implementation in engineering industries.

General Information

Country / RegionUnited Kingdom
Primary LanguageEnglish
1st Year Published—
FrequencyQuarterly
StatusActive
Total Publications1,392
Publisher OrgCambridge University Press
Visit Journal Website

Submission Info

Publishing ModelSubscription
Peer ReviewSingle-blind peer review
Review Time—
Acceptance Rate—
OA License—
OA Rate—

Ethics & Quality

COPE Member✗ No
OASPA Member✗ No
Not on Predatory Lists✓ Yes

Think.Check.Submit Compliance

7/12 · 58%
✅
Do you know the journal / publisher?
Cambridge University Press
✅
Does the journal have a website?
✓ Linked
✅
Is the ISSN verified?
0890-0604 / 1469-1760
✅
Indexed in a trusted database?
WoS, Scopus
✅
Peer review process documented?
Single-blind peer review
❌
Follows ethical publishing standards (COPE)?
N/A
❌
APC fees clearly disclosed?
N/A
✅
Not on predatory/blacklists?
✓ Clean
❌
Long-term digital preservation?
N/A
❌
Plagiarism detection in place?
N/A
❌
Listed in DOAJ (verified OA)?
N/A
✅
Primary language documented?
English

Based on the Think.Check.Submit framework by DOAJ, COPE & OASPA. All data from verified open sources.

Publication & Citation Trend

Articles published
Citations received
42
545
2019
51
511
2020
28
235
2021
35
303
2022
26
238
2023
25
98
2024
31
94
2025
6
1
2026

Source: OpenAlex · Each year’s green bar = citations earned by that year’s papers, counted to date — so recent years look lower simply because their papers haven’t had time to be cited yet.

SJR Quartile by Discipline

Scimago ranks this journal separately in each subject category — its quartile can differ by discipline.

Industrial and Manufacturing EngineeringQ2
Artificial IntelligenceQ3

Subject Classification

Web of Science Categories

Computer Science, Artificial IntelligenceComputer Science, Interdisciplinary ApplicationsEngineering, ManufacturingEngineering, Multidisciplinary

Scopus Categories

Industrial and Manufacturing EngineeringArtificial Intelligence

Research Topics (OpenAlex)

Design Education and PracticeManufacturing Process and OptimizationProduct Development and CustomizationDiverse Scientific and Economic StudiesBIM and Construction Integration

Frequently asked questions about Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM

Is Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM a predatory journal?

PubScope has no integrity flags on record for Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM: it is indexed in Web of Science, Scopus, and is not on DOAJ's withdrawn list. Its PubScope Trust Score is 90/100. Indexing is a transparency signal, not a guarantee — always confirm fit and policies before submitting.

What is the impact factor of Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM?

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM is indexed in the Web of Science Core Collection, so Clarivate publishes an official Journal Impact Factor for it (since the 2023 Journal Citation Reports, every Core Collection journal — including Arts & Humanities and Emerging Sources titles — receives one). PubScope links to Clarivate's official source rather than reprinting the number, which can be out of date. Its open 2-year mean citedness is 2.24.

Is Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM indexed in Scopus and Web of Science?

Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM is indexed in Web of Science, Scopus.

What is the aims and scope of Artificial Intelligence for Engineering Design, Analysis and Manufacturing: AIEDAM?

Artificial Intelligence for Engineering Design, Analysis and Manufacturing (AI EDAM) is a journal that publishes original research papers on the application of artificial intelligence techniques to engineering design, analysis, and manufacturing. The journal covers a wide range of topics, including knowledge-based systems, expert systems, machine learning, neural networks, fuzzy logic, genetic algorithms, and other AI methodologies applied to engineering problems. AI EDAM aims to bridge the gap between AI research and its practical implementation in engineering industries.

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Data updated: 2026-05-22 · Sources: SJR, DOAJ, OpenAlex, WoS, Crossref