International Journal of System Assurance Engineering and Management

Scope & Guideline

Elevating Standards in Safety and Engineering Management

Introduction

Welcome to your portal for understanding International Journal of System Assurance Engineering and Management, featuring guidelines for its aims and scope. Our guidelines cover trending and emerging topics, identifying the forefront of research. Additionally, we track declining topics, offering insights into areas experiencing reduced scholarly attention. Key highlights include highly cited topics and recently published papers, curated within these guidelines to assist you in navigating influential academic dialogues.
LanguageEnglish
ISSN0975-6809
PublisherSPRINGER INDIA
Support Open AccessNo
CountryIndia
TypeJournal
Convergefrom 2010 to 2024
AbbreviationINT J SYST ASSUR ENG / Int. J. Syst. Assur. Eng. Manag.
Frequency6 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
Address7TH FLOOR, VIJAYA BUILDING, 17, BARAKHAMBA ROAD, NEW DELHI 110 001, INDIA

Aims and Scopes

The International Journal of System Assurance Engineering and Management focuses on the intersection of engineering, management, and technology, aiming to advance the understanding and application of system assurance methods. It serves as a platform for innovative research that addresses contemporary challenges in engineering and management disciplines through the integration of advanced technologies.
  1. System Assurance Engineering:
    The journal emphasizes methodologies and frameworks that ensure the reliability, safety, and performance of engineering systems across various fields, including manufacturing, transportation, and healthcare.
  2. Data-Driven Decision Making:
    Research published in the journal often employs data analytics, machine learning, and artificial intelligence to enhance decision-making processes in complex systems.
  3. Sustainable Engineering Practices:
    A significant focus is placed on sustainability, exploring how engineering and management practices can be optimized to meet environmental and economic goals.
  4. Interdisciplinary Approaches:
    The journal encourages interdisciplinary research that combines insights from engineering, management, information technology, and social sciences to address multifaceted issues.
  5. Emerging Technologies:
    It covers the application of emerging technologies such as IoT, AI, blockchain, and big data analytics in enhancing system assurance and management practices.
The International Journal of System Assurance Engineering and Management is currently witnessing a surge in research themes that reflect the latest trends in technology and societal needs. These emerging scopes indicate a proactive approach to addressing contemporary challenges in engineering and management.
  1. Artificial Intelligence and Machine Learning:
    There is a growing body of research applying AI and machine learning techniques to enhance system assurance, predictive maintenance, and decision-making processes.
  2. Internet of Things (IoT) Integration:
    The integration of IoT technologies in various systems is a trending topic, focusing on how interconnected devices can improve operational efficiency and data collection.
  3. Sustainability and Green Engineering:
    Research dedicated to sustainable engineering practices, including waste reduction, energy efficiency, and the circular economy, is increasingly prominent.
  4. Cybersecurity in Engineering Systems:
    With the rise of digitalization, there is an increasing emphasis on cybersecurity measures in engineering systems to safeguard against vulnerabilities.
  5. Big Data Analytics:
    The use of big data analytics for real-time monitoring and predictive analytics in system assurance is gaining traction, indicating a shift towards more data-centric methodologies.

Declining or Waning

As the International Journal of System Assurance Engineering and Management evolves, certain themes appear to be declining in prominence. This can be attributed to shifts in research priorities and advancements in technology that render some previously popular topics less relevant.
  1. Traditional Manufacturing Techniques:
    Research focusing solely on conventional manufacturing methods is becoming less prevalent as the emphasis shifts towards automation and smart manufacturing technologies.
  2. Basic Statistical Analysis:
    There is a noticeable decline in studies that rely solely on basic statistical methods without integrating advanced computational techniques or machine learning approaches.
  3. Single-Discipline Studies:
    The journal is witnessing a decrease in publications that focus narrowly on a single discipline, moving instead towards more integrative and multidisciplinary research.
  4. Outdated Risk Assessment Models:
    Traditional risk assessment models that do not incorporate modern data analytics or machine learning techniques are becoming less common in favor of more robust, data-driven approaches.

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