International Journal of Automation Technology

Top Research Topics at International journal of automation technology?

The journal primarily focuses on research topics in Mechanical engineering, Composite material, Manufacturing engineering, Engineering drawing and Control engineering. Machining is a major topic of Mechanical engineering research. Engineering drawing and Machine tool are closely related fields of research discussed in International journal of automation technology.

The journal focuses on Control engineering research which is adjacent to topics in Control theory.

• Mechanical engineering (14.12%)
• Composite material (10.32%)
• Manufacturing engineering (9.75%)

What are the most cited papers published in the journal?

• “Industrie 4.0” and Smart Manufacturing - A Review of Research Issues and Application Examples (417 citations)
• Indirect Measurement of Volumetric Accuracy for Three-Axis and Five-Axis Machine Tools: A Review (150 citations)
• Muscle Suit Development and Factory Application (90 citations)

Research areas of the most cited articles at International journal of automation technology:

The main points discussed in the published articles deal with Manufacturing engineering, Machine tool, Engineering drawing, Control engineering and Mechanical engineering. While the journal papers focused on Manufacturing engineering, they were also able to explore topics like Factory (object-oriented programming) and Computer-aided process planning, Process (engineering), Machining. The works on Engineering drawing tackled in the most cited papers bring together disciplines like Industry 4.0, Composite material, End milling and Geometric error.

What topics the last edition of the journal is best known for?

• Mechanical engineering
• Artificial intelligence
• Composite material

The previous edition focused in particular on these issues:

The primary areas of discussion in International journal of automation technology are Composite material, Mechanical engineering, Robot, Machining and Artificial intelligence. Magnetic levitation studies in the realm of Mechanical engineering interact with fields like Free form. The journal holds forums on Robot that merges themes from other disciplines such as Type (model theory) and Machine tool.

The Machining study featured falls within the larger field of Metallurgy. The research on Artificial intelligence featured in the journal combines topics in other fields like Extraction (chemistry) and Computer vision. The journal focuses on Industrial robot but the discussions also offer insight into other areas such as Control engineering and Robot calibration.

The most cited articles from the last journal are:

• Predicting Positioning Error and Finding Features for Large Industrial Robots Based on Deep Learning (2 citations)
• Quasi-Static Compliance Calibration of Serial Articulated Industrial Manipulators (1 citations)
• Kinematic Modeling of Six-Axis Industrial Robot and its Parameter Identification: A Tutorial (1 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing in International journal of automation technology (based on the number of publications) are:

• Keiichi Shirase (33 papers) published 2 papers at the last edition, 2 less than at the previous edition,
• Yoshimi Takeuchi (27 papers) absent at the last edition,
• Tsunemoto Kuriyagawa (26 papers) published 1 paper at the last edition, 4 less than at the previous edition,
• Masayoshi Mizutani (22 papers) published 1 paper at the last edition, 4 less than at the previous edition,
• Keita Shimada (21 papers) published 1 paper at the last edition, 3 less than at the previous edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in International journal of automation technology (based on the number of publications) are:

• University of Tokyo (20 papers) absent at the last edition,
• Osaka University (17 papers) published 2 papers at the last edition, 1 less than at the previous edition,
• Okayama University (16 papers) absent at the last edition,
• Tohoku University (10 papers) published 1 paper at the last edition, 3 less than at the previous edition,
• Keio University (9 papers) absent at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 73.08% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 23.81% were posted by at least one author from the top 10 institutions publishing in the journal. Another 38.10% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 19.05% of all publications and 19.05% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.