A connective framework to minimize the anxiety of collaborative Cyber-Physical System

Islam, SOB, Lughmani, WA, Qureshi, WS and Khalid, A ORCID: https://orcid.org/0000-0001-5270-6599, 2023. A connective framework to minimize the anxiety of collaborative Cyber-Physical System. International Journal of Computer Integrated Manufacturing. ISSN 0951-192X

Preview

Text 1630608_Khalid.pdf - Post-print Download (1MB) | Preview

Abstract

The role of Cyber-Physical systems (CPS) is well recognized in the context of Industry 4.0, which consists of human operators working with machines/robots. The interactions among them can be quite demanding in terms of cognitive resources. Existing systems do not yet consider the psychological aspects of safety in the domain. This lack can lead to hazardous situations, thus compromising the performance of the working system. This work proposes a connective decision-making framework for a flexible CPS, which can quickly respond to dynamic changes and be resilient to emergent hazards. First, Anxiety is defined and categorized for expected/unforeseen situations that a CPS could encounter through historical data using the Ishikawa method. Second, visual cues are used to gather the CPS's current state (such as human pose and object identification). Third, a mathematical model is developed using Mixed-integer programming (MIP) to allocate optimal resources, to tackle high-impact situations generating Anxiety. Finally, the logic is designed for an effective counter-mechanism to mitigate Anxiety. The proposed method was tested on a realistic industrial scenario incorporating a collaborative CPS. The results demonstrated that the proposed method improves the decision-making of a CPS facing a complex scenario, ensures physical safety, and effectively enhances the human-machine team's productivity.

Item Type:	Journal article
Publication Title:	International Journal of Computer Integrated Manufacturing
Creators:	Islam, S.O.B., Lughmani, W.A., Qureshi, W.S. and Khalid, A.
Publisher:	Informa UK Limited
Date:	1 January 2023
ISSN:	0951-192X
Identifiers:	Number Type 10.1080/0951192x.2022.2163294 DOI 1630608 Other
Rights:	This is an Accepted Manuscript of an article published by Taylor & Francis in International Journal of Computer Integrated Manufacturing on 01.01.2023, available online: http://www.tandfonline.com/10.1080/0951192X.2022.2163294
Divisions:	Schools > School of Science and Technology
Record created by:	Jeremy Silvester
Date Added:	05 Jan 2023 14:15
Last Modified:	01 Jan 2024 03:00
URI:	https://irep.ntu.ac.uk/id/eprint/47751

Actions (login required)

Edit View

Statistics

Views

Downloads