Meistaravörn við verkfræðideild: Ignas Urbonas
MSc í hátækniverkfræði
Föstudaginn 26.maí kl. 10:00 mun Ignas Urbonas verja 30 ECTS verkefni sitt til meistaragráðu í hátækniverkfræði „Design of a Robotic Storage Node: An Efficiency Analysis Using Axiomatic Design„. Fyrirlesturinn fer fram í M208 og eru öll velkomin.
Nemandi: Ignas Urbonas
Leiðbeinandi: Joseph Timothy Foley
Prófdómari: Indriði Sævar Ríkharðsson
Útdráttur
Robotic arms have the capabilities of storing objects within their reach, both in designated storage areas such as shelves or simply on the floor around themselves. To enhance the storage capabilities of the robotic arm one common approach is to incorporate custom-designed storage areas and attach the robotic arms to a rail system, thereby introducing an additional axis of movement. This configuration effectively expands the arm’s reach and facilitates increased storage capacity. Custom-made designated storage areas and rails are expensive to manufacture and install. The objective of the project is to design a storage node utilizing a robotic arm to maximize the efficient utilization of its designated space, through mathematical calculations and optimized shelving arrangements to ensure optimal use of available storage capacity. This storage node shall be designed with the goal of storing wine bottles. The design of the storage node was specifically tailored to meet the requirements of red wine bottle storage. Axiomatic Design theory was employed during the design of the storage node. The Customer Needs were acquired and defined through meetings with the representatives of companies involved in this project. The design specifics of the storage node were threefold. Firstly, the dedicated storage area was designed to maximize the number of bottles in the storage node. Secondly, the designated storage area was designed to account for different bottle shapes and sizes while maximizing the number of possible SKUs in the storage node. Finally, the design of the storage node is designed to minimize the cost of the node. The project findings demonstrate that implementing optimized wine bottle storage methods enables the Storage Node to efficiently accommodate up to 2160 bottles, while simultaneously maintaining a selection of a minimum of 45 distinct SKUs.
