Computers & Industrial Engineering

Scope & Guideline

Fostering Collaboration for a Smarter Industrial Landscape

Introduction

Delve into the academic richness of Computers & Industrial Engineering with our guidelines, detailing its aims and scope. Our resource identifies emerging and trending topics paving the way for new academic progress. We also provide insights into declining or waning topics, helping you stay informed about changing research landscapes. Evaluate highly cited topics and recent publications within these guidelines to align your work with influential scholarly trends.
LanguageMulti-Language
ISSN0360-8352
PublisherPERGAMON-ELSEVIER SCIENCE LTD
Support Open AccessNo
CountryUnited Kingdom
TypeJournal
Convergefrom 1976 to 2024
AbbreviationCOMPUT IND ENG / Comput. Ind. Eng.
Frequency12 issues/year
Time To First Decision-
Time To Acceptance-
Acceptance Rate-
Home Page-
AddressTHE BOULEVARD, LANGFORD LANE, KIDLINGTON, OXFORD OX5 1GB, ENGLAND

Aims and Scopes

The journal 'Computers & Industrial Engineering' focuses on the intersection of computer science and industrial engineering, emphasizing the application of computational methods to solve complex industrial problems. It aims to foster innovation in manufacturing and operational processes through advanced technologies and methodologies.
  1. Supply Chain Management and Logistics:
    Research in this area includes optimization of supply chain networks, inventory management, and logistics operations, often integrating advanced technologies such as IoT and blockchain for enhanced efficiency and transparency.
  2. Manufacturing Systems and Operations Management:
    The journal covers methodologies for improving manufacturing processes, including scheduling, production planning, and quality control, with a focus on Industry 4.0 and automation.
  3. Sustainability and Green Practices:
    A significant emphasis is placed on sustainable practices in manufacturing and supply chains, exploring the integration of environmental considerations into operational decisions and the development of circular economy models.
  4. Data Analytics and Predictive Modeling:
    The use of data-driven approaches, including machine learning and statistical modeling, to enhance decision-making processes in various industrial applications is a core focus.
  5. Maintenance and Reliability Engineering:
    Research related to maintenance strategies, reliability analysis, and predictive maintenance methodologies is prevalent, aiming to optimize equipment performance and minimize downtime.
  6. Human Factors and Ergonomics:
    The journal also addresses the human aspects of industrial engineering, including worker safety, ergonomics, and the integration of human-robot collaboration in manufacturing environments.
Recent publications in 'Computers & Industrial Engineering' indicate a strong trend towards integrating advanced technologies and methodologies in various industrial applications. The following emerging scopes highlight the journal's current research trajectory.
  1. AI and Machine Learning Applications:
    There is a significant increase in studies applying AI and machine learning to optimize processes, enhance decision-making, and predict outcomes in manufacturing and supply chain management.
  2. Blockchain Technology in Supply Chains:
    Research exploring the use of blockchain for supply chain transparency, traceability, and efficiency is on the rise, reflecting the growing interest in decentralized and secure transaction models.
  3. Circular Economy and Sustainability Initiatives:
    The focus on circular economy principles, sustainable supply chain practices, and environmental impact assessments is gaining momentum, indicating a shift towards more responsible industrial practices.
  4. Smart Manufacturing and Industry 4.0:
    Emerging themes related to smart manufacturing, including IoT integration, digital twins, and automation technologies, are increasingly prevalent in recent publications.
  5. Resilience and Risk Management:
    There is a growing emphasis on resilience in supply chains, particularly in the context of disruptions such as pandemics, highlighting the need for robust risk management strategies.
  6. Human-Robot Collaboration:
    Research on human-robot collaboration in manufacturing environments is emerging, focusing on optimizing workflows and enhancing worker safety and efficiency.

Declining or Waning

While the journal continues to expand in many areas, certain themes have shown a decline in prominence in recent years. These waning scopes suggest a shift in focus and research priorities within the field.
  1. Traditional Manufacturing Techniques:
    Research focusing solely on traditional manufacturing techniques without the integration of modern technologies has decreased, as the field shifts towards more innovative and technology-driven approaches.
  2. Basic Statistical Methods:
    The application of basic statistical methods in industrial engineering is becoming less common as more advanced data analytics and machine learning techniques take precedence.
  3. Conventional Supply Chain Models:
    There is a noticeable reduction in research centered around conventional supply chain models that do not incorporate sustainability or technological advancements, reflecting a broader trend towards more integrated and innovative models.
  4. Single-Objective Optimization Problems:
    The journal has seen fewer publications focused on single-objective optimization problems, as multi-objective and complex optimization scenarios gain more attention.
  5. Industry-Specific Studies Without Technological Integration:
    Research that focuses on specific industries without considering the integration of new technologies or methodologies is becoming less prevalent, signaling a shift towards more interdisciplinary approaches.

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