Impact Score 4.62
Special Issue in
Computers & Industrial Engineering:
Human-technology integration in smart manufacturing and logistics
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:
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
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.
Professor Carlos E. Pereira, Electrical Engineering Department, Federal University of Rio Grande do Sul, Porto Alegre, Brazil; [email protected]
Professor Sergio Cavalieri, Department of Management, Information and Production Engineering, University of Bergamo, Italy; [email protected]
Professor Oliver Riedel, Institute for Control Engineering of Machine Tools and Manufacturing Units, University of Stuttgart, Germany; [email protected]
Dr Alexandra Lagorio, Department of Management, Information and Production Engineering, University of Bergamo, Italy; [email protected]
Managing Guest Editor:
Dr Chiara Cimini, Department of Management, Information and Production Engineering,
University of Bergamo, Italy; [email protected]