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Systems
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Design Methods for Human–Machine Teams
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Design Methods for Human–Machine Teams

A special issue of Systems (ISSN 2079-8954). This special issue belongs to the section "Systems Engineering".

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 9676

Special Issue Editors

Dr. Christina Rusnock

E-Mail Website
Guest Editor
Systems Engineering and Management, Air Force Institute of Technology, Dayton, OH 45433, USA
Interests: human factors; human performance modeling; human workload
Special Issues, Collections and Topics in MDPI journals
Dr. Michael E. Miller

E-Mail Website
Guest Editor
Systems Engineering and Management, Air Force Institute of Technology, Dayton, OH 45433, USA
Interests: human factors; modeling the human element; human systems integration
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The explosion of automation, artificial intelligence, and autonomous systems is transforming interaction and work across a wide range of applications, including manufacturing, defense, transportation, healthcare, and finance. The design of human–machine teams that include humans and machines with embedded algorithms has the potential to combine the relative advantages, while compensating for the disadvantages of each. However, teams are much more than a sum or their individual parts, and to be effective, these entities must be designed to support effective communication, collaboration, and trust. Deliberate systems engineering methods and tools for designing and evaluating these systems, as well as appropriate system architectures, are required to support these vital teaming characteristics. You are cordially invited to contribute to this Special Issue to expand the shared understanding and advances in the use of systems engineering to support the design of human–machine teams. We welcome both original research and review articles.

Dr. Christina Rusnock
Dr. Michael E. Miller
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Systems is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

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Published Papers (4 papers)

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Research

29 pages, 4071 KiB  
Article
Analysis and Requirement Generation for Defense Intelligence Search: Addressing Data Overload through Human–AI Agent System Design for Ambient Awareness
by Mark C. Duncan, Michael E. Miller and Brett J. Borghetti
Systems 2023, 11(12), 561; https://doi.org/10.3390/systems11120561 - 29 Nov 2023
Cited by 1 | Viewed by 2087
Abstract
This research addresses the data overload faced by intelligence searchers in government and defense agencies. The study leverages methods from the Cognitive Systems Engineering (CSE) literature to generate insights into the intelligence search work domain. These insights are applied to a supporting concept [...] Read more.
This research addresses the data overload faced by intelligence searchers in government and defense agencies. The study leverages methods from the Cognitive Systems Engineering (CSE) literature to generate insights into the intelligence search work domain. These insights are applied to a supporting concept and requirements for designing and evaluating a human-AI agent team specifically for intelligence search tasks. Domain analysis reveals the dynamic nature of the ‘value structure’, a term that describes the evolving set of criteria governing the intelligence search process. Additionally, domain insight provides details for search aggregation and conceptual spaces from which the value structure could be efficiently applied for intelligence search. Support system designs that leverage these findings may enable an intelligence searcher to interact with and understand data at more abstract levels to improve task efficiency. Additionally, new system designs can support the searcher by facilitating an ‘Ambient Awareness’ of non-selected objects in a large data field through relevant system cues. Ambient Awareness achieved through the supporting concept and AI teaming has the potential to address the data overload problem while increasing the breadth and depth of search coverage. Full article
(This article belongs to the Special Issue Design Methods for Human–Machine Teams)
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19 pages, 7646 KiB  
Article
Manufacturing System Design in Industry 5.0: Incorporating Sociotechnical Systems and Social Metabolism for Human-Centered, Sustainable, and Resilient Production
by Alejandro Agote-Garrido, Alejandro M. Martín-Gómez and Juan Ramón Lama-Ruiz
Systems 2023, 11(11), 537; https://doi.org/10.3390/systems11110537 - 4 Nov 2023
Cited by 11 | Viewed by 3104
Abstract
This paper delves into the concept of social metabolism as a foundation for the development of sociotechnical systems in Industry 5.0. The study conducts an analysis of the existing methods and approaches for designing sociotechnical systems, and reviews publications that utilize such systems [...] Read more.
This paper delves into the concept of social metabolism as a foundation for the development of sociotechnical systems in Industry 5.0. The study conducts an analysis of the existing methods and approaches for designing sociotechnical systems, and reviews publications that utilize such systems to incorporate Industry 4.0 technologies into manufacturing processes. Additionally, it examines the three key factors of Industry 5.0 and the enabling framework of Industry 4.0 technologies. Based on these investigations, a theoretical model is proposed for manufacturing system design, employing sociotechnical systems to integrate Industry 4.0 enabling technologies, while considering the essential aspects of Industry 5.0. The model emphasizes the early consideration of sociotechnical systems to design manufacturing systems that prioritize human-centricity, sustainability, and resilience. By embracing this comprehensive approach, the proposed model contributes to the realization of a production environment aligned with societal needs, fostering a more conscious and adaptable industry. Full article
(This article belongs to the Special Issue Design Methods for Human–Machine Teams)
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19 pages, 2866 KiB  
Article
Biases in Stakeholder Elicitation as a Precursor to the Systems Architecting Process
by Taylor Yeazitzis, Kristin Weger, Bryan Mesmer, Joseph Clerkin and Douglas Van Bossuyt
Systems 2023, 11(10), 499; https://doi.org/10.3390/systems11100499 - 28 Sep 2023
Viewed by 1887
Abstract
Many systems engineering projects begin with the involvement of stakeholders to aid in decision-making processes. As an application of systems engineering, systems architecture involves the documentation of stakeholder needs gathered via elicitation and the transformation of these needs into requirements for a system. [...] Read more.
Many systems engineering projects begin with the involvement of stakeholders to aid in decision-making processes. As an application of systems engineering, systems architecture involves the documentation of stakeholder needs gathered via elicitation and the transformation of these needs into requirements for a system. Within human–machine teaming, systems architecture allows for the creation of a system with desired characteristics elicited from stakeholders involved with the project or system. Though stakeholders can be excellent sources for expert opinion, vested interests in a project may potentially bias stakeholders and impact decision-making processes. These biases may influence the design of the system architecture, potentially resulting in a system that is developed with unbalanced and misrepresented stakeholder preferences. This paper presents an activity analysis of the Stakeholder Needs and Requirements Process as described in the Systems Engineering Body of Knowledge (SEBoK) to identify potential biases associated with this elicitation process. As part of the research presented in this paper, a workshop was conducted where currently practicing systems architects provided feedback regarding perceptions of biases encountered during the elicitation process. The findings of this research will aid systems architects, developers, and users in understanding how biases may impact stakeholder elicitation within the architecting process. Full article
(This article belongs to the Special Issue Design Methods for Human–Machine Teams)
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17 pages, 529 KiB  
Article
RAD-XP: Tabletop Exercises for Eliciting Resilience Requirements for Sociotechnical Systems
by Stephen L. Dorton, Emily Barrett, Theresa Fersch, Andrew Langone and Kelly J. Neville
Systems 2023, 11(10), 487; https://doi.org/10.3390/systems11100487 - 23 Sep 2023
Cited by 2 | Viewed by 1361
Abstract
Despite noble intentions, new technologies may have adverse effects on the resilience of the sociotechnical systems into which they are integrated. Our objective was to develop a lightweight method to elicit requirements that, if implemented, would support sociotechnical system resilience. We developed and [...] Read more.
Despite noble intentions, new technologies may have adverse effects on the resilience of the sociotechnical systems into which they are integrated. Our objective was to develop a lightweight method to elicit requirements that, if implemented, would support sociotechnical system resilience. We developed and piloted the Resilience-Aware Development Exercise Protocol (RAD-XP), a method to generate tabletop exercises (TTXs) to elicit resilience requirements. In the pilot study, this approach generated 15 requirements from a one-hour TTX, where the majority of requirements were found to support resilience. Participants indicated via survey that RAD-XP was effective and efficient, and that they would want to use RAD-XP regularly throughout the agile development process. We discuss future research and development to refine this approach to eliciting resilience requirements. Full article
(This article belongs to the Special Issue Design Methods for Human–Machine Teams)
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