Journal Information
Computers & Industrial Engineering
https://www.journals.elsevier.com/computers-and-industrial-engineering/
Impact Factor:
4.135
Publisher:
Elsevier
ISSN:
0360-8352
Viewed:
2329
Tracked:
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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 Human-technology integration in smart manufacturing and logistics
Submission Date: 2021-04-30

Aims of the Special Issue: Advances in automation, digitalisation, and robotics have ushered a new age in which machines can substitute and/or complement human operators in an increasingly wider range of work activities, paving the way to the concepts of Operator 4.0 and Logistics Operator 4.0 (Cimini et al., 2020a; Romero et al., 2020). Among the plethora of technologies, which are mentioned under the umbrella of Industry 4.0, different impacts can be observed, in relation to the different technological capabilities. The operators of the future will be immersed in intelligent environments, with the possibility to share and receive real-time information from many smart objects (e.g., machines, robots, products) and they will be involved in new collaboration mechanisms and social interactions, which will highly affect the performance of the industrial system. The management and decision-making processes will become increasingly shared between humans and machines, requiring new models to govern the management and control of the manufacturing and logistics processes. New scenarios of Social Human-in-the-Loop Cyber-Physical Production Systems (Cimini et al., 2020b) and Human-Machine Cooperation (Pacaux-Lemoine et al., 2017) have been envisioned, suggesting that re-thinking manufacturing and logistics systems from a human-centred perspective makes it possible to use digital technologies to enhance the unique and irreplaceable capabilities of man, who will continue to play a fundamental role in the factories of the future. Indeed, in smart manufacturing and logistics systems, the available amount of information will not be manageable for the normal operator - just because of the variety and quantity. For this reason, new methods will be required to allow the operator to handle this amount and variety of information and make the right decision out of the chain "signal-data-information", since it can be assumed that Artificial Intelligence cannot solve every data-related issue. Some related relevant contributions have been already published on Computers & Industrial Engineering, demonstrating a high interest from the readers of the journal about these topics; in particular, the Special Issue entitled “The Operator 4.0: Towards socially sustainable factories of the future”, edited by David Romero, Johan Stahre and Marco Taisch, has been published in 2019. With this Special Issue, we aim at deepening further these researches, but enlarging the perspective with a more socio-technical systems approach, exploring more in detail the social interactions that occur in smart manufacturing systems. Moreover, currently, the manufacturing landscape has been heavily broken out by the emergence of the COVID-19 pandemic, which is changing promptly and profoundly the industrial work, requiring urgent investigation about new practices of smart industrial work, able to allow social distancing without performance losses. This special issue aims at attracting contribution from scholars and practitioners in the emerging research streams about Human-Technology integration in the next-generation manufacturing and logistics systems. Integrating humans in the smart manufacturing and logistics systems includes both technological aspects, such as the human-centred development of technological applications, workplaces and human-machine interfaces (Longo et al., 2017), and operational aspects, including multidisciplinary approaches to depict the role of humans in the loop of manufacturing and logistics process planning and control (Fantini et al., 2020). Along with this, deeply exploring human aspects, such as new competences and skillsets required to the human workforce to be efficient in Industry 4.0, the evolution of roles and the Human Factors affecting successful implementations of new technologies, will be of high relevance both from the academic and industrial communities. Scope of the Special Issue: Alongside the development of new technologies, developments in the human-related aspects (such as human factors concerning the technologies design and application as well as the impacts on operators’ capabilities) must be carried out. This analysis should be done both at theoretical level, highlighting the interdependences between technological implementation and the human capabilities, and at a practical level, providing industrial companies with effective tools to drive their workforce toward the new paradigm of Industry 4.0, aligning the technological innovations with a human-centred perspective of the smart manufacturing and logistics. We invite authors to submit scientific papers that approach the human-technology integration in manufacturing and logistics systems. Submissions involving case studies and innovative applications in the field of smart manufacturing and logistics systems that affect the human work are welcomed. Both empirical and conceptual, quantitative and qualitative original research studies are welcomed. Case studies and practical applications are encouraged. To that end, we seek submissions with an original perspective and advanced thinking on the development of the smart manufacturing and logistics field, instead of theoretical studies and frameworks on human-technologies integration. Although they can contain some review of the literature, we look for submissions that go beyond systematic reviews, and propose and discuss fresh conceptual and methodological avenues for further development of the field. The topics of interest include, but are not limited to: Multidisciplinary approaches in Human-centred smart technologies development in Manufacturing and Logistics Human-centred development of assisting and augmenting technologies 5G and advanced technologies supporting Human-technology integration Artificial Intelligence supporting Human-technology integration Human Factors affecting implementations of smart technologies New skills and competences for the workforce 4.0 Human-technology integration/collaboration in decision-making and decision support systems for Smart Manufacturing and Logistics Human-machine interactions and human-technologies collaboration in process control for Manufacturing and Logistics Use of simulation models and digital twins for human-technology collaboration in Smart Manufacturing and Logistics References Cimini, C., Lagorio, A., Romero, D., Cavalieri, S., Stahre, J., 2020a. Smart Logistics and The Logistics Operator 4.0. Presented at the 21st IFAC World Congress | Berlin, Germany. Cimini, C., Pirola, F., Pinto, R., Cavalieri, S., 2020b. A human-in-the-loop manufacturing control architecture for the next generation of production systems. Journal of Manufacturing Systems 54, 258–271. https://doi.org/10.1016/j.jmsy.2020.01.002 Fantini, P., Pinzone, M., Taisch, M., 2020. Placing the operator at the centre of Industry 4.0 design: Modelling and assessing human activities within cyber-physical systems. Computers & Industrial Engineering 139, 105058. https://doi.org/10.1016/j.cie.2018.01.025 Longo, F., Nicoletti, L., Padovano, A., 2017. Smart operators in industry 4.0: A human-centered approach to enhance operators’ capabilities and competencies within the new smart factory context. Computers & Industrial Engineering 113, 144–159. https://doi.org/10.1016/j.cie.2017.09.016 Pacaux-Lemoine, M.-P., Trentesaux, D., Zambrano Rey, G., Millot, P., 2017. Designing intelligent manufacturing systems through Human-Machine Cooperation principles: A human-centered approach. Computers & Industrial Engineering 111, 581–595. https://doi.org/10.1016/j.cie.2017.05.014 Romero, D., Stahre, J., Taisch, M., 2020. The Operator 4.0: Towards socially sustainable factories of the future. Computers & Industrial Engineering 139, 106128. https://doi.org/10.1016/j.cie.2019.106128 Submission Guidelines: Manuscripts should be submitted through the publisher’s online system, Elsevier Editorial System (EES) at http://ees.elsevier.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 “Human-technology integration in smart manufacturing and logistics” as Section/Category. 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: Deadline for manuscript submission: 30th April 2021 Review report: 30th June 2021 Revised paper submission deadline: 31st July 2021 Notification of final acceptance: 30th September 2021 Expected Publication (Tentative): End of 2021 Guest Editors: Prof. Sergio Cavalieri, Department of Management, Information and Production Engineering, University of Bergamo, Italy; sergio.cavalieri@unibg.it Dr. Chiara Cimini, Department of Management, Information and Production Engineering, University of Bergamo, Italy; chiara.cimini@unibg.it Prof. Carlos E. Pereira, Electrical Engineering Department, Federal University of Rio Grande do Sul, Porto Alegre, Brazil; cpereira@eletro.ufrgs.br Prof. Oliver Riedel, Institute for Control Engineering of Machine Tools and Manufacturing Units, University of Stuttgart, Germany; oliver.riedel@isw.uni-stuttgart.de Mr. Jason Wang, China Sci-Tech Automation Alliance, jason.wang@sachina.org Managing Guest Editor: Dr. Alexandra Lagorio, Department of Management, Information and Production Engineering, University of Bergamo, Italy; alexandra.lagorio@unibg.it
Last updated by Dou Sun in 2021-03-09
Special Issue on Emerging Artificial Intelligent Technologies for Industry 5.0 and Smart Cities
Submission Date: 2021-07-30

Future personalization services in industry is one of term recently used as an enhancement on Industry 4.0. Industry 5.0 is also known as fifth industrial revolution using artificial intelligence and cognitive based services that focuses cooperation between man and machine with intelligence. Artificial intelligence (AI) technologies (such as IoT, blockchain, virtual reality, fuzzy inference system, deep learning-based neural networks (DNNs), convolutional neural networks, stacked autoencoders, deep reinforcement learning, meta-learning, life-long learning, and graph neural networks, and meta-heuristic algorithms) have played an important role in enhancing the quality of manufacturing which combines people, processes, and machines, to impact the overall economical productions, i.e., the age of Industry 5.0. Industry 5.0 is the technical enhancements over the services offered in addition to Industry 4.0, especially in context to future personalization services. In the meanwhile, these emerging AI technologies also provide enough supports for the connectivity of buildings, data, energy, transport, and governance, which is leading toward many innovations across industrial applications. Hence, there is a demand to further explore the abundant applications of these AI technologies to improve/enhance the quality of manufacturing, supply chain management, Industry 5.0 and smart cities. Thus, the special issue is to provide a platform for discussions on novel, scientific, technological insights, principles, algorithms, and experiences in such papers (as below) but not limited; Significant cuts in unplanned downtime to better-designed products; Novel AI-based analytics on data to improve efficiency, product quality and the safety of employees; Data-driven innovations for demand planning and logistics management; AI-based and green-based supply chains; Applications of IoT for tracking production across entire processes and supply chain; Advances AI technologies in enhancing Industry 5.0 and the connectivity of any components for smart cities; Hybrid meta-heuristic algorithms with AI technologies in enhancing Industry 5.0 and the connectivity of any components for smart cities; Intelligent solutions for future smart industries; Internet of things (IoT) in industry 5.0; Cloud and data analytics in industry 5.0 for effective analysis of industrial data; Novel or improved nature-inspired optimization algorithms in enhancing Industry 5.0 and the connectivity of any components for smart cities. Submission Deadline: 30 July 2021 Notification of Acceptance: 30 October 2021 Publication: Late 2021 Guest Editors Prof. Dr. Wei-Chiang Hong, Department of Information Management, Oriental Institute of Technology, New Taipei, Taiwan; samuelsonhong@gmail.com Prof. Dr. Wei-Chang Yeh, Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Taiwan; wcyeh@ie.nthu.edu.tw Prof. Dr. Pradeep Kumar Singh, Department of Computer Science & Engineering, ABES Engineering College. Ghaziabad, Uttar Pradesh, India; pradeep_84cs@yahoo.com Assoc. Prof. Dr. Paulo J. Sequeira Gonçalves, Electrotechnical and Industrial Engineering, School of Technology, Polytechnic Institute of Castelo Branco, Portugal; paulo.goncalves@ipcb.pt Managing Guest Editor: Prof. Dr. Pradeep Kumar Singh, Department of Computer Science & Engineering, ABES Engineering College. Ghaziabad, Uttar Pradesh, India; pradeep_84cs@yahoo.com
Last updated by Dou Sun in 2021-03-09
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
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