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International Journal of Computer Aided Manufacturing

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The International Journal of Computer-Aided Manufacturing (IJCAM) is a peer-reviewed hybrid open-access journal dedicated to publishing high-quality research in computer-aided manufacturing, automation of machining processes, and CAD/CAM technologies. Ideal for researchers, engineers, and scholars in mechanical engineering and manufacturing automation.

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International Journal of Computer-Aided Manufacturing

The International Journal of Computer-Aided Manufacturing (IJCAM) is a peer-reviewed journal focused on advancing research, innovation, and technological development in the field of computer-aided manufacturing (CAM). It offers a comprehensive platform for researchers, engineers, and academics to explore cutting-edge technologies, methodologies, and practices aimed at improving manufacturing processes and systems.

What This Journal Covers: Key Focus Areas

The IJCAM covers a wide range of emerging and critical topics in the CAM and manufacturing industries, ensuring that its content is applicable to both academic research and practical industry needs:

  • Automated Manufacturing Systems: Studies on robotic automation, machine learning, and artificial intelligence (AI) for improving the efficiency and flexibility of production systems in modern manufacturing.
  • Advanced Machining Techniques: Research on innovative machining technologies, such as laser cutting, ultrasonic machining, precision grinding, and micro-manufacturing for high-performance components.
  • Smart Manufacturing & IoT: The role of the Internet of Things (IoT) in smart manufacturing, where intelligent machines, data analytics, and real-time monitoring systems drive automation, productivity, and quality control.
  • Manufacturing Process Optimization: Insights into optimization algorithms, supply chain management, and lean manufacturing techniques that enhance operational efficiency and sustainability in production environments.
  • Sustainability in Manufacturing: Focus on green manufacturing, waste reduction, energy efficiency, and the use of sustainable materials in manufacturing processes to reduce the environmental impact.

Who Should Read the Journal

IJCAM is ideal for:

  • Manufacturing engineers and technologists working with CAD/CAM systems, additive manufacturing, and advanced machining.
  • Researchers and academics studying computer-aided manufacturing, industrial automation, and smart manufacturing technologies.
  • Students pursuing mechanical engineering, manufacturing engineering, or industrial design degrees.
  • Industry professionals and consultants involved in automated production systems, industrial design, and process optimization.
  • Policymakers and regulatory bodies focused on sustainable manufacturing practices and industry standards.

Why It Matters

The International Journal of Computer-Aided Manufacturing is crucial in:

  • Disseminating the latest research that drives technological advances in automated manufacturing and computer-aided systems.
  • Promoting innovative manufacturing solutions that improve productivity, precision, and flexibility in production systems.
  • Providing insights into emerging manufacturing trends, such as additive manufacturing, intelligent manufacturing, and IoT integration.
  • Supporting sustainability and energy-efficient practices that help industries meet global environmental goals.
  • Advancing education and knowledge sharing in the realm of manufacturing automation and smart manufacturing systems.

Submission & Peer-Review

IJCAM is published in both online and print formats, providing flexible access for global readers:

  • Online Subscription: Access to the full journal archives and research articles through the STM Journals digital platform.
  • Print Subscription: Physical copies available for delivery to academic institutions, libraries, or personal use.

Why Choose STM Journals

STM Journals ensures high-quality research publication with:

  • Rigorous peer-review standards to maintain academic integrity and credibility.
  • Global reach, offering access to researchers, students, and professionals worldwide.
  • Multiple access options, including online and print, for broader dissemination.
  • A focus on advancing industrial practices, manufacturing automation, and sustainable manufacturing technologies.

About Journal

International Journal of Computer Aided Manufacturing International Journal of Computer-Aided Manufacturing [2456-642X(e)] is a peer-reviewed hybrid open-access journal launched in 2015 that reports new research as well, as a new application of the technology that could be of use in the ongoing research and in framing an educational ground for the students. The journal aims to cover computer-aided manufacturing software and the automation of machining processes.

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Journal Information

Title: International Journal of Computer Aided Manufacturing Abbreviation: IJCAM
Issues Per Year: 2 Issues E-ISSN: 2456-642X
Publisher: JournalsPub, An imprint of Dhruv Infosystems Pvt. Ltd.
DOI: 10.37591/IJCAM Starting Year: 2015
Language: English Publication Format: Hybrid Open Access
Subject: Engineering Type: Peer-reviewed Journal (Refereed Journal)
Copyright Policy: CC BY-NC-ND

Indexing & Metrics

Indexing: Index Copernicus, Scientific Literature (SCILIT), SJIF, Google Scholar

ICV Value: 2024: 59.92, 2023: 60.92

Impact Factor (SJIF): 2024: 6.000, 2023: 5.993, 2022: 5.986, 2021: 5.984, 2020: 5.949

Focus & Scope

Focus & Scope

A next-generation manufacturing framework—unifying high-speed CNC machining and laser additive processes with electric vehicle dynamics, computational intelligence, and seamless PLM data integration.

Advanced CNC Dynamics

Optimization of 5-axis machining via configuration space search and optimal tool orientation. Research targets systematic deviation identification in tilting rotary tables and sculptured surface tool paths.

EV & Power Systems

Investigation of permanent magnet motors, stator windings, and magnetic flux in induction motors. Covers Vehicle-to-Everything (V2X) taxonomy and Vehicular Ad Hoc Networks (VANETs).

Feature & Image Analysis

Applying neural networks and volume decomposition for automated feature recognition in CAD models. Includes edge detection algorithms for laser additive manufacturing and geometric measurement.

Evolutionary Computing

Utilizing Particle Swarm Optimization and evolutionary computation for power system dynamics. Focus on computational intelligence for streamlining manufacturing processes and software usability.

Digital Thread (PLM/DNC)

Seamless data integration across the CAM-NC process chain. Research covers Direct Numerical Control (DNC), Product Lifecycle Management (PLM), and supervisory control via PLCs.

Modern Enterprise Management

Strategic management information systems focusing on data security and investment costs. Integration of business communication with modern software systems for reconfigurable manufacturing.

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