Design and Development of Unmanned Surface Vehicle Using System Engineering Principles

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.