Trans RINA, Vol 156, Part C1, Intl J Marine Design, Jan -Dec2014 specifications regarding operability of aircraft.


Commercial vessels are similar to aircraft in that they are very often sold at the digital model stage. As with the automotive industry,


using DHM, the development


timeframe can be reduced and optimized at the same time because different design options can be easily compared with one another. Posture in the cockpit, comfort and ease of operation in the


passenger cabins and the


feasibility of maintenance tasks can all be simulated. It also facilitates the testing and optimization of the feasibility of performing assembly, maintenance and repair work. van der Meulen and DiClemente


[74]


describe the use of the DHM in a proposed flight deck design for the Eclipse 500 jet. The results were used to detect accommodation problems, as well as to establish further guidelines and requirements for design of the cockpit and interior components.


RAMSIS Cognitive is a module for analysing and optimizing the perception and management


of


information in the vehicle. As the number of instruments in drivers’ cockpits increases it is vital to know how well they can be perceived, and to ensure all the displays fall well within the field of vision. This concerns all technical information of a vehicle such as instruments, control displays, and optical indicators. The additional functionality allows simulation of viewing conditions in the car, including methods for the analysis of sight shadows, limits of visibility of liquid crystal displays, estimating the time of focus shifts of the driver and the modelling of the optical parameters of head-up displays. This offers optimized instrument visibility resulting in greater operational safety and increased comfort. It also results in lower costs for modifications during the development phase (Remlinger, Bubb and Wirsching, [75]).


The work undertaken within the European Boat Design Innovation Group (www.ebdig.eu) found that tools such as RAMSIS are effective human factor design tools in the majority of marine applications, (Dobbins, Hill, McCartan and Thompson, [72]).


3.4 OPEN INNOVATION


In order to facilitate transfer of technology into the Maritime sector we propose the use of ‘Open innovation’ (OI). OI is a new paradigm for the management of innovation. It is defined as ‘the use of purposive inflows and outflows of knowledge to accelerate internal innovation, and to expand the markets for external use of innovation, respectively.’ It thus comprises both outside- in and inside-out movements of technologies and ideas, also referred


to as ‘technology exploration’ and


‘technology exploitation’. As a result, a growing number of MNEs have moved to an OI model in which they employ both internal and external pathways to exploit technologies and, concurrently, to acquire knowledge


the comfort, safety and


from external sources. In order to better profit from internal knowledge, enterprises may engage in three activities related to technology exploitation: venturing, outward licensing of intellectual property (IP), and the involvement of non-R&D workers in innovation initiatives (Figure 18). Venturing is defined as starting up new organisations drawing on internal knowledge, i.e. it implies spin-off and spin-out processes. The third practice to benefit from internal knowledge is to capitalize on the initiatives and knowledge of current employees, including those who are not employed in the internal R&D department. Several case studies illustrate that informal ties of employees with employees of other organizations are crucial to understand how new products are created and commercialized. Many practitioners and scientists, also outside the field of OI, endorse the view that innovation by individual employees is a means to foster organizational success. Work has become more knowledge-based and less rigidly defined. In this context, employees can be involved in innovation processes in multiple ways, for example by


taking up their


suggestions, exempting them to take initiatives beyond organizational boundaries, or introducing suggestion schemes such as idea boxes and internal competitions (van de Vrandea et al., [76]).


However, innovation in SMEs is hampered by lack of financial resources, scant opportunities to recruit specialized workers, and small innovation portfolios, so that risks associated with innovation cannot be spread. SMEs need to heavily draw on their networks to find missing innovation resources. External networking to acquire new or missing knowledge is therefore vital for European Maritime SMEs to remain competitive. OI is therefore highly relevant for both


service and


manufacturing organisations and is described in the following collaborative model (Figure 19).


Figure 18: Open innovation model for SMEs


As the Maritime Sector is heavily populated by SMEs but other transport sectors are less so, the use of this model to efficiently transfer


knowledge while


engendering trust in a mutually beneficial relationship is both novel and ideal.


C-20 ©2014: The Royal Institution of Naval Architects


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