TY - JOUR
T1 - Selection of alarm displays for time- and error-critical tasks
T2 - A multi-hierarchy decision framework integrating network structure and multi-criteria decision analysis
AU - Cun, Wenzhe
AU - Fan, Hao
AU - Wang, Long
AU - Huang, Zhe
AU - Shi, Jinlei
AU - Gan, Yihan
AU - Chu, Jianjie
AU - Chen, Dengkai
N1 - Publisher Copyright:
© 2026 Elsevier B.V. All rights are reserved, including those for text and data mining, AI training, and similar technologies.
PY - 2026/7
Y1 - 2026/7
N2 - Effective alarm design and evaluation are crucial for time- and error-critical tasks. This study introduces a hierarchical network-synthesized multi-criteria decision analysis (HNS-MCDA) framework that balances multi-dimensional, conflicting criteria and reconcile the divergent optimal alarm displays identified by various indices. By decomposing the evaluation into three layers (primary metric, attribute-synthesized, and cross-task synthesis), the framework enables hierarchical decision-making for alarm display selection within specific task types and across task types. It also identifies the most robust alarm under dynamic task types and provides full traceability and interpretability of the decision process. The framework was validated on the OpenMATB platform with six alarm displays and six types of tasks. Results showed that the optimal alarm display differed across the three decision hierarchical layers, with the auditory-tactile alarm exhibiting the highest robustness in the cross-task synthesis layer. The findings demonstrated that the HNS-MCDA framework could enable comprehensive evaluation and optimal selection of alarm displays, thereby enhancing the safety, reliability, and efficiency of alarm systems.
AB - Effective alarm design and evaluation are crucial for time- and error-critical tasks. This study introduces a hierarchical network-synthesized multi-criteria decision analysis (HNS-MCDA) framework that balances multi-dimensional, conflicting criteria and reconcile the divergent optimal alarm displays identified by various indices. By decomposing the evaluation into three layers (primary metric, attribute-synthesized, and cross-task synthesis), the framework enables hierarchical decision-making for alarm display selection within specific task types and across task types. It also identifies the most robust alarm under dynamic task types and provides full traceability and interpretability of the decision process. The framework was validated on the OpenMATB platform with six alarm displays and six types of tasks. Results showed that the optimal alarm display differed across the three decision hierarchical layers, with the auditory-tactile alarm exhibiting the highest robustness in the cross-task synthesis layer. The findings demonstrated that the HNS-MCDA framework could enable comprehensive evaluation and optimal selection of alarm displays, thereby enhancing the safety, reliability, and efficiency of alarm systems.
KW - Alarm display
KW - Decision framework
KW - Multi-criteria decision analysis
KW - Multimodal alarm
UR - https://www.scopus.com/pages/publications/105034620732
U2 - 10.1016/j.displa.2026.103431
DO - 10.1016/j.displa.2026.103431
M3 - 文章
AN - SCOPUS:105034620732
SN - 0141-9382
VL - 93
JO - Displays
JF - Displays
M1 - 103431
ER -