Multi-objective optimization and scenario-based robustness analysis of the MoneyMaker Hip Pump

Abstract Water-lifting technologies for irrigation have significant potential to increase agricultural yields and stimulate economic growth in rural areas of the developing world. Human-powered water pumps have been used with great success in this rapidly developing market. KickStart's MoneyMaker Hip Pump is a human-powered water pump with additional design features that make it lightweight and portable for use in remote fields in several countries throughout Africa. This work first applied numerical optimization techniques to the design of the MoneyMaker Hip Pump and offers further improvements to its design. Deterministic multi-objective optimization methods were employed to maximize the flow rate of the pump, maximize the pumping height of water, and minimize cost. Following optimization, the robustness of the optimized pump design was analyzed under several modified scenarios, including fouling of the hoses and a decrease in operator power due to fatigue or aging. The set of cost-optimized pump designs was then compared to a second set of optimal designs that was found using material volume as a simplified proxy for the cost objective function. Findings indicate that several technical improvements can be made to the current MoneyMaker Hip Pump design to reduce cost by up to 37% without affecting water flow rate, or increase water flow rate by up to 88% without increasing cost. The numerical model was validated through physical experimentation of the MoneyMaker Hip Pump, and design alterations to reduce cost were experimentally shown to maintain pump performance.