Journal Information
Computers & Industrial Engineering
https://www.journals.elsevier.com/computers-and-industrial-engineering/
Impact Factor:
4.135
Publisher:
Elsevier
ISSN:
0360-8352
Viewed:
3480
Tracked:
4
Call For Papers
Industrial engineering is one of the earliest fields to utilize computers in research, education, and practice. Over the years, computers and electronic communication have become an integral part of industrial engineering. Computers & Industrial Engineering (CAIE) is aimed at an audience of researchers, educators and practitioners of industrial engineering and associated fields.

It publishes original contributions on the development of new computerized methodologies for solving industrial engineering problems, as well as the applications of those methodologies to problems of interest in the broad industrial engineering and associated communities. The journal encourages submissions that expand the frontiers of the fundamental theories and concepts underlying industrial engineering techniques.

CAIE also serves as a venue for articles evaluating the state-of-the-art of computer applications in various industrial engineering and related topics, and research in the utilization of computers in industrial engineering education. Papers reporting on applications of industrial engineering techniques to real life problems are welcome, as long as they satisfy the criteria of originality in the choice of the problem and the tools utilized to solve it, generality of the approach for applicability to other problems, and significance of the results produced.

A major aim of the journal is to foster international exchange of ideas and experiences among scholars and practitioners with shared interests all over the world.
Last updated by Dou Sun in 2021-03-09
Special Issues
Special Issue on Digital technologies for sustainability and risk in post-pandemic supply chains
Submission Date: 2021-10-31

Background: The COVID-19 pandemic has brought severe challenges to the global supply chain. Many manufacturers and retailers have closed their businesses during the epidemic. To cope with production delays and the slowdown in distribution due to disruptions in labor and material supply chains, many organizations have used digital technologies related to the Industrial Internet or Industry 4.0, such as the Internet of Things (IoT), blockchain, and machine learning to enhance the sustainability of the supply chain. Since logistics and supply chain management include a wide range of activities, successfully controlling resources related to logistics and supply chain management is essential for organizations to maintain self-sustainment of business activities in a severe market environment. With the rapid development of digital technologies such as blockchain technology, artificial intelligence, virtual reality, and big data analysis, the existing organizational processes and results continue to form and influence each other, which is necessary to deal with the sustainability of the supply chain in the pandemic. In addition, in supply chain management, data-led leadership and targeted decision-making have basically replaced experience and best practices. Traditional management systems are facing ever-changing volatility and strong competitiveness, while artificial intelligence and blockchain technology are completely changing the way of supply chain process management from all levels. This special issue aims to explore new technologies such as blockchain, the Internet of Things (IoT), and machine learning in supply chain management. The SI encourages submissions of original analytical or empirical studies that report significant research contributions, covering topics including, but not limited to: The role of digital technology (e.g. Artificial Intelligence, machine learning, blockchain) adoption in predicting and coping with supply chain disruptions (E.g. caused by COVID-19 pandemic) New business models/concepts, methods, technologies promoting supply chain sustainability under Industrial Internet Blockchain-supported closed-loop supply chain systems Data safety and security to improve supply chain sustainability with the use of blockchain Quantitative case studies of using digital technology in multi-tier supply-demand coordination in sustainability Digitalized documentation for effective take-back and closed-loop supply chains using smart contracts Smart contracting, risk sensitivity assessment, information sharing, and updating within supply chain sustainability Policy, education, finance, governance in the implementation of supply chain sustainability through digital technologies Supply chains risks and vulnerabilities in the light of scenarios of manufacturing and service trade development worldwide Submission and review process Manuscripts should be submitted through the publisher’s online system, Elsevier Editorial System (EES) at www.editorialmanager.com/caie. Please follow the instructions described in the “Guide for Authors”, given on the main page of the EES website. Please make sure you select “Special Issue” as Article Type and “Digital technologies for sustainability and risk in post-pandemic supply chains” as Section/Category. Authors should choose the article type VSI: Digital technologies. In preparing their manuscript, the authors are asked to closely follow the “Instructions to Authors”. Submissions will be reviewed according to C&IE’s rigorous standards and procedures through a double-blind peer review by at least two qualified reviewers. Publication Schedule Manuscript Submission Deadline: 31 October 2021 Revised Manuscript Submission: 31 December 2022 Final Decision Date: 28 February 2022 Expected Publication (Tentative): Middle of 2022 Guest Editors Prof. Desheng Dash Wu, University of Chinese Academy of Sciences, China; dwu@ucas.ac.cn; desheng.wu@sbs.su.se. Managing Guest Editor Prof. James H. Lambert, University of Virginia, United States; lambert@virginia.edu Prof. David L. Olson, University of Nebraska, United States; dolson3@unl.edu
Last updated by Dou Sun in 2021-03-09
Special Issue on Optimizing IoT and Big data Embedded Smart Supply Chains for Sustainable Performance
Submission Date: 2021-12-31

Topics of interest include, but not limited to: - Impact of IoT & big data on sustainable supply chain projects - Recent advances for sustainable supply chain & logistics - Green supply chain and logistics management to reduce environmental risk. - Optimize ABCD technologies in the company’s production, logistics, and supply chain process. - Application of IoT and big data in all aspects of production and supply chain network with the aim of sustainability - Block-chain based IoT for secured supply chain - Smart contract for rapid and sustainable supply chain - Smart transformation of the supply chain through digital technologies - Block-chain based IoT and big data embedded sustainable supply chain for industry 4.0 - Application of Artificial intelligence in supply chain management - Assessing the impact of IoT and Big data on sustainable operations and supply chain management (OSCM) model
Last updated by Dou Sun in 2021-07-25
Special Issue on Blockchain-based applications for enhancing cybersecurity in manufacturing and building supply chain resilience
Submission Date: 2022-03-31

Topics of interest include, but are not limited to: - Role of blockchain technology in increasing SCRes and sustainability in the context of the COVID-19 pandemic - Use of BT-based cryptocurrencies and smart contract applications to enhance SCRes and operations sustainability - Theory-based assessment of blockchain prospects for SCRes and operations sustainability - Blockchain-based solutions for specific industries or business areas - Barriers and enablers of blockchain adoption for SCRes and sustainable supply chain performance - The role of emerging technologies adoption in predicting supply chain disruptions - Evaluation and governance of BT for developing SCRes. - The impact of BT on organizational governance - Risk management and incident response frameworks for manufacturing context - Security and privacy of BT based smart applications using Machine Learning techniques - Cybersecurity vulnerabilities detection and prevention to foster SCRes - Transparency, anonymity, information, and privacy control in next-generation BT - Blockchain based authentication, authorization, and accounting mechanisms for SCRes and sustainability - Blockchains in software-defined networking (SDN) and network functions virtualization (NFV) for SCRes applications - Performance Optimization for Blockchain using machine learning techniques - Resources allocation in BT-based systems - Optimization BT-based strategies for investment in Industry 4.0
Last updated by Dou Sun in 2021-07-25
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