Full Customisation, Quick Performance Estimation and Optimisation of Parametric Snowboard Design

Current snowboard design relies heavily on riding experience and personal riding style of the board designers along with feedback from professional snowboard riders. Snowboard companies are spending huge amounts of money and time on this unproductive trial and error method of design. As a result, consumers ’ choices are limited to the fixed sizes, shapes and structural designs offered by snowboard companies. At the same time, choosing a suitable snowboard by reading feedback and reviews from different sources can also be very time consuming. Snowboard enthusiasts seek an optimal board design that will suit them as best as possible. Due to the limited off-the-shelf designs provided by snowboard companies, the “Do-It-Yourself ” approach is the only solution for an optimal design. Sophisticated snowboard design requires a certain level of engineering Computer Aided Design (CAD) drawing and mathematical skill, including complex structural analysis of fabric composites and core materials; and bending and torsional stiffness distribution estimation. Therefore, an advanced design platform is desirable to enable users without engineering backgrounds to design and fully customise their own snowboard. This research is aimed at providing snowboard riders and designers an optimisation and customisation tool for snowboard design. Rather than maximising the performance parameters of a board in every aspect, the optimisation tool provides a solution to optimise the feel of the board to best fit individual use. This greatly reduces the time and cost for riders and even snowboard manufacturers to design a new board and avoid the inefficient trial and error method. Current research employed Sequential Quadratic Programming (SQP) method and Multiple Objective Simulated Annealing (MOSA) to perform the optimisation tasks and to verify the solutions with each other. The optimisation tasks were implemented throug