Abstract:
Unmanned surface vehicles (USVs) are remotely operated ships/boats without a crew and have
applications in rescue operations, exploring deep-sea regions, coastal monitoring and defence systems.
In this thesis, the focus is to identify an efficient design of unmanned surface vehicles using a
system engineering process. The approach involves the identification of stakeholders and their
operational needs, the development of operational scenarios highlighting system characteristics,
functional architecture with detailed system characteristics, physical architecture and lastly imple-
mentation/integration of system components. This systematic approach allows us to identification
of multiple design alternatives with no unwanted/redundant subsystems and each ensuring user
requirements. Thus a set of design alternatives can be identified that are utilizing subsystems as
per user requirements. The decision of selecting a specific the design is based on some economic and
other non-economic criteria. The economic criterion is the total cost of the project including initial
cost, maintenance cost, and salvage value and it is computed in terms of the present equivalent,
future equivalent or annual equivalent of the project. The non-economic criteria may include flexi-
bility, complexity and ease of integration. To utilize these non-economic criteria together with the
economic criterion for multi-criteria decision-making, it is important to rank all the non-economic
criteria on a scale by using past experience. The concept of decision evaluation display is used
to select a better choice based on the given economic and non-economic criteria. The results are
shown for an industrial-funded project where an efficient design of an unmanned surface vehicle is
to be identified under economic and non-economic constraints. It is observed that for the given
scenario, the system engineering process and evaluation leads to 27.7% improvement in terms of the
total project cost, in addition to better ranking in other non-economic criteria. The improvement in
non-economic criteria is qualitative and can be observed in comparison to other design alternatives.
