An analysis of factors influencing ice management performance in an experimental marine simulator and their application to decision support system design
Ice management is essential for maintaining the safety of offshore operations in Arctic regions. We present the combined results of three experiments conducted in a full-mission bridge simulator specially designed for ice management. From a quantitative analysis of the results, we infer the effect o...
| Published in: | Journal of Offshore Mechanics and Arctic Engineering |
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| Main Authors: | , , , , |
| Format: | Article in Journal/Newspaper |
| Language: | English |
| Published: |
American Society of Mechanical Engineers
2023
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| Subjects: | |
| Online Access: | https://doi.org/10.1115/1.4063617 https://nrc-publications.canada.ca/eng/view/ft/?id=57af9b31-b604-4c6f-b2ac-2cef2328a8a9 https://nrc-publications.canada.ca/eng/view/object/?id=57af9b31-b604-4c6f-b2ac-2cef2328a8a9 https://nrc-publications.canada.ca/fra/voir/objet/?id=57af9b31-b604-4c6f-b2ac-2cef2328a8a9 |
| Summary: | Ice management is essential for maintaining the safety of offshore operations in Arctic regions. We present the combined results of three experiments conducted in a full-mission bridge simulator specially designed for ice management. From a quantitative analysis of the results, we infer the effect of three variables on performance: (1) experience, (2) training, and (3) Decision Support System (DSS). The results confirm that experience and training improve performance for untrained and inexperienced simulator participants. The DSS also improves performance, but with a smaller effect. Qualitative observations using vessel position heat-map diagrams and exit interviews suggested that novice participants using the DSS adopted expert strategies but carried out their tasks more slowly and with less precision. This has important consequences for the design of a future DSS used in training simulators or onboard ships. Potential improvements to the DSS design might include real-time feedback to the user, a redesign of the human–machine interface (HMI), and increasing user input and customization with a human factors focus. Peer reviewed: Yes NRC publication: No |
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