Changeability Planning Of Modular Fixtures In A Robotic Assembly System To Manage Product Variety

Abstract

Changeability in Manufacturing Systems has been implemented in various industries over the last forty years to meet the challenge of change in product demand and design. Changeability is an umbrella paradigm and consists of different manufacturing system characteristics, such as changeover-ability, reconfigurability, flexibility, transformability and agility. On the system level, flexibility is enabled particularly by implementing modular equipment designs such as modular fixtures that can hold a variety of product geometries. On the operational level, optimizing the changeability plan of those modular fixtures improves the performance of the manufacturing system. This thesis considers a hole-pattern modular fixture to increase the changeability of an automated assembly system. In this assembly setting, a robot that is located on top of a conveyor belt loop places different parts on the modular fixture and secure them by inserting four pegs around each part. The more peg replacements are occurred, the longer fixture setup time is required. Hence, the researchers of this study have developed five different mathematical models to effectively determine the best parts and pegs locations on the fixture to minimize the number of pegs replacements considering different conditions and constraints. At this point, researchers presented a new fixture design that improves the fixture modularity to hold more products with different geometries. By making a few modifications, the five previous models have been extended to be used for this new fixture design. Subsequently, researchers proposed three case studies with different parameters sizes to investigate the models’ efficiency. The results show that the different models are able to significantly reduce fixture setup time.