Smart and Sustainable Manufacturing Systems

Scope & Guideline

Empowering the evolution of smart manufacturing solutions.

Introduction

Explore the comprehensive scope of Smart and Sustainable Manufacturing Systems through our detailed guidelines, including its aims and scope. Stay updated with trending and emerging topics, and delve into declining areas to understand shifts in academic interest. Our guidelines also showcase highly cited topics, featuring influential research making a significant impact. Additionally, discover the latest published papers and those with high citation counts, offering a snapshot of current scholarly conversations. Use these guidelines to explore Smart and Sustainable Manufacturing Systems in depth and align your research initiatives with current academic trends.
LanguageEnglish
ISSN2520-6478
PublisherAMER SOC TESTING MATERIALS
Support Open AccessNo
CountryUnited States
TypeJournal
Convergefrom 2017 to 2024
AbbreviationSMART SUSTAIN MANUF / Smart Sustain. Manuf. Syst.
Frequency1 issue/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address100 BARR HARBOR DR, W CONSHOHOCKEN, PA 19428-2959

Aims and Scopes

The journal 'Smart and Sustainable Manufacturing Systems' focuses on the intersection of advanced manufacturing technologies, sustainability practices, and smart systems, aiming to provide a platform for innovative research that enhances manufacturing efficiency while addressing environmental and operational challenges.
  1. Smart Manufacturing Technologies:
    Exploration of advanced manufacturing technologies such as machine learning, digital twins, and automation systems that enhance production efficiency and adaptability.
  2. Sustainability in Manufacturing:
    Research on sustainable practices within manufacturing processes, including energy efficiency, waste reduction, and eco-friendly materials, to promote a greener industry.
  3. Integration of Digital Solutions:
    Focus on integrating digital solutions like IoT, cloud computing, and AI into manufacturing systems to enable real-time monitoring, predictive maintenance, and improved decision-making.
  4. Data-Driven Approaches:
    Utilization of data analytics and machine learning techniques to optimize manufacturing processes, enhance quality control, and improve operational performance.
  5. Collaborative and Adaptive Systems:
    Development of collaborative frameworks and adaptive manufacturing systems that respond to dynamic market demands and facilitate human-robot collaboration.
Recent publications in 'Smart and Sustainable Manufacturing Systems' highlight several emerging themes that are gaining traction, reflecting the journal's responsiveness to current industry needs and technological advancements.
  1. Machine Learning and AI Applications:
    There is a significant increase in research focused on the application of machine learning and AI in manufacturing processes, particularly in predictive maintenance, quality control, and process optimization.
  2. Digital Twins and Virtual Simulation:
    The use of digital twins and virtual simulation technologies is rapidly emerging, allowing for real-time monitoring and optimization of manufacturing systems.
  3. Sustainable Manufacturing Practices:
    Research on specific sustainable manufacturing practices, such as decarbonization pathways and eco-efficient processes, is on the rise, reflecting a global push towards sustainability.
  4. Cyber-Physical Systems and IoT Integration:
    The integration of cyber-physical systems and IoT in manufacturing is trending, facilitating enhanced connectivity and data exchange across manufacturing environments.
  5. Collaborative Robotics and Human-Robot Interaction:
    Emerging studies are increasingly focusing on collaborative robotics and the optimization of human-robot interactions, highlighting the importance of workforce adaptation in smart manufacturing.

Declining or Waning

As the field evolves, certain themes within 'Smart and Sustainable Manufacturing Systems' appear to be declining in prominence. This reflects a shift in focus towards more innovative and pressing issues in manufacturing.
  1. Traditional Manufacturing Techniques:
    There has been a noticeable decrease in research focused solely on traditional manufacturing techniques, as the emphasis shifts towards smart and automated processes that leverage modern technology.
  2. Generalized Sustainability Concepts:
    While sustainability remains a core theme, the exploration of generalized sustainability concepts without specific application to manufacturing contexts is becoming less frequent.
  3. Manual Quality Control Methods:
    The focus on manual quality control methods is waning as automated and machine learning-based quality assurance systems are increasingly prioritized.
  4. Conventional Supply Chain Management Solutions:
    Research on conventional supply chain management practices is declining as the integration of digital and smart technologies transforms traditional approaches.
  5. Static Educational Frameworks:
    The previous emphasis on static educational frameworks in manufacturing is diminishing, with a growing interest in adaptive, interdisciplinary curricula that better prepare students for modern manufacturing challenges.

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