Robotics and Computer-Integrated Manufacturing

Robotics and Computer-Integrated Manufacturing - ISSN 0736-5845
Source Normalized Impact per Paper (SNIP): 2.994 Source Normalized Impact per Paper (SNIP):
SNIP measures contextual citation impact by weighting citations based on the total number of citations in a subject field.
SCImago Journal Rank (SJR): 1.795 SCImago Journal Rank (SJR):
SJR is a prestige metric based on the idea that not all citations are the same. SJR uses a similar algorithm as the Google page rank; it provides a quantitative and a qualitative measure of the journal’s impact.
Impact Factor: 5.057 (2019) Impact Factor:
The Impact Factor measures the average number of citations received in a particular year by papers published in the journal during the two preceding years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
5 Year Impact Factor: 4.851 (2019) Five-Year Impact Factor:
To calculate the five year Impact Factor, citations are counted in 2016 to the previous five years and divided by the source items published in the previous five years.
© 2017 Journal Citation Reports ® (Clarivate Analytics, 2017)
Volumes: Volumes 61-66
Issues: 6 issues
ISSN: 07365845
Editor-in-Chief: Wang

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The emphasis of the journal Robotics and Computer-Integrated Manufacturing is on disseminating the application of research to the development of new or improved industrially-relevant robotics, manufacturing technologies, and innovative manufacturing strategies. Preference is given to papers describing original research that includes both theory and experimental validation. Comprehensive review papers on topical issues related to robotics and manufacturing will also be considered. Papers on conventional machining processes, modelling and simulation, supply chain management, and resource optimisation, will generally be considered out of scope, as there are other more appropriate journals in these areas. Overly theoretical or mathematical papers will be directed to other more appropriate journals as well. Original papers are welcomed in the areas of industrial robotics, human-robot collaborative manufacturing, cloud-based manufacturing, cyber-physical production systems, big data analytics in manufacturing, smart mechatronics, machine learning, adaptive and sustainable manufacturing, and other fields involving unique manufacturing technologies.