Trans RINA, Vol 156, Part C1, Intl J Marine Design, Jan - Dec 2014
obtained are used as the primary input to an EAST analysis.
Co-ordination demands analysis (CDA) – involves defining the
involved during the scenario, and then rating each teamwork task step against the CDA taxonomy of; communication;
situational awareness; decision
making; mission analysis; leadership; adaptability; and assertiveness.
Comms Usage Diagram (CUD) - is used to describe collaborative activity between distributed agents. The output
communications between a team occur, the technology
disadvantages of the technology medium used.
Social Network Analysis – involves defining and analysing the relationships between agents within a network. A matrix of association and a social network diagram
Operation Sequence Diagram (OSD) – represents the tasks, actors, communications, social organisation, sequence and time in which a scenario takes
are constructed, and agent
centrality, sociometric status and network density figures are calculated.
place. It captures the flow of information
between actors and shows how this is mediated through technology and team work.
Critical Decision Method (CDM) – involves the use of interview probes to elicit information regarding the agent decision making strategies adopted during the scenario under analysis.
Propositional Networks – The CDM output is used to construct propositional networks for each phase. Propositional networks are comprised of nodes that represent sources of information, agents, and objects that are linked through specific causal paths. The propositional network thus represents the potentially ‘ideal’ collection of knowledge for an incident.
EAST is a comprehensive technique offering a multi- faceted assessment of the C4i network in question providing an assessment of
agent roles within the
network, a description of the activity including the flow of information, the component tasks, communication between agents and the operational loading of each agent. The methodology has been applied in a number of domains, including the fire service (Baber et al [66] [67]), naval
warfare (Stanton et al, [68]), military
aviation command and control (Stewart et al, [69]), air traffic control and rail domains (Walker et al, [70]). EAST provides a dynamic view of the DSA held by both human and non-human components in a system, and illustrates how this can vary with task requirements (Stanton, Baber and Harris, [71]).
3.4 DIGITAL HUMAN MODELING (DHM) AND BIOMECHANICAL ANALYSIS
There is a need to support the maritime sector to facilitate anthropometric and biomechanical aspects of
©2014: The Royal Institution of Naval Architects the advantages and
of CUD describes how and why involved, and
task-work and team-work tasks Human Factors Integration in the design process.
Traditionally, this has been supported through the use of mock-ups, with their effective use for anthropometric assessment often not being fully realised due to time constraints or uninformed practices. Physical mock-ups are typically constructed to assess the interaction between the user and their working environment, but this is still the exception rather than the norm. There are three recognised classes of
mock-up fidelity, which designers/manufacturers may use:
Class 1 - Low fidelity: used to evaluate approximate work/accommodation shape, space, external vision and new ideas.
Class 2 - Good fidelity: produced to be close to the craft drawing dimensions, used for the assessment of detail design, crew stations configuration, passenger space, maintenance access, ability to undertake emergency procedures, etc.
Class 3 - High fidelity: constructed with production materials and to production tolerances, interrogate Man-Machine Interface lighting, layouts of wiring, plumbing, etc.
used details, task
An issue with the production of Class 2 and Class 3 mock-ups is the resource required, both in terms of cost and development time, however 3D Computer Aided Design (CAD) has become the norm throughout the marine design industry. The ability of CAD to optimise human factor design considerations as an integral part of the design process is an effective solution both in terms of cost and development time (Dobbins, Hill, McCartan and Thompson, [72]).
In the early 90s the German car industry developed a CAD tool for early integration of ergonomics in the vehicle design process. This CAD tool for ergonomics and occupant packaging, was called RAMSIS (Realistic Anthropometric Mathematical Simulation in Situation). Its goal was to overcome the limitations of conventional automotive industry practices of using two-dimensional human templates, as well as to provide methods for predicting driver postures and comfort. RAMSIS is based on a highly accurate DHM (Digital Human Model) that can simulate occupants with a large variety of body dimensions from global
anthropometry databases. A
probability-based posture prediction model was developed through research on driver postures and comfort. The assessment of comfort allows designers to optimize packages with respect to driver comfort early in the design process. Analysis tools include: reach and vision;
force-based posture and comfort to
prediction
model; simulation of ingress and egress. This DHM has resulted in a reduction in development costs of more than 50% for the automotive industry through a reduction in vehicle development timeframes by a factor of 3 to 5 (van der Meulen and Seidl, [73]). RAMSIS is now used in the aerospace sector by companies such as Airbus, EADS, Embraer and Eurocopter to address customer
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