Enhancing human performance in ship operations by modifying global design factors at the design stage

Montewka, Jakub and Goerlandt, Floris and Innes-Jones, Gemma and Owen, Douglas and Hifi, Yasmine and Puisa, Romanas (2017) Enhancing human performance in ship operations by modifying global design factors at the design stage. Reliability Engineering and System Safety, 159. pp. 283-300. ISSN 0951-8320

[img]
Preview
Text (Montewka-etal-RESS-2017-Enhancing-human-performance-in-ship-operations-by-modifying-global-design-factors)
Montewka_etal_RESS_2017_Enhancing_human_performance_in_ship_operations_by_modifying_global_design_factors.pdf
Final Published Version
License: Creative Commons Attribution 4.0 logo

Download (1MB)| Preview

    Abstract

    Usually the improvements of human performance in the course of ship design process is carried out by modifying local ergonomics, like electronic visualisation and information display systems on the bridge or in the engine control room, stair or hatch covers design. However, the effect of global design factors (GDFs), such as ship motion, whole body vibration and noise, on human performance has not been given attention before. Such knowledge would allow the improvements of human performance by effective design modification on very early stage of ship design process. Therefore, in this paper we introduce probabilistic models linking the effect of GDFs with the human performance suitable for ship design process. As a theoretical basis for modelling human performance the concept of Attention Management is utilized, which combines the theories described by Dynamic Adaptability Model, Cognitive Control Model and Malleable Attentional Resources Theory. Since the analysed field is characterised by a high degree of uncertainty, we adopt a specific modelling technique along with a validation framework that allows uncertainty treatment and helps the potential end-users to gain confidence in the models and the results that they yield. The proposed models are developed with the use Bayesian Belief Networks, which allows systematic translation of the available background knowledge into a coherent network and the uncertainty assessment and treatment. The obtained results are promising as the models are responsive to changes in the GDF nodes as expected. The models may be used as intended by naval architects and vessel designers, to facilitate risk-based ship design.