This thesis deals with the operation problems of automated guided vehicle(AGV) in assembly production system. It is assumed that AGV delivers assembly parts to each workstation from a miniload automated storage/retrieval system(AS/RS) and a conveyor line transports subassemblies between workstations. The miniload AS/RS consists of an aisle of storage rack, a storage/retrieval (S/R) machine operating in the aisle, storage containers for housing electronic parts and load stands at the end of each aisle to facilitate order picking.
Since the parts needed at each workstation may not be a single component, it is assumed that kits are produced at a kitting station located in front of the load stands of the miniload AS/RS. The number of kits contained in the unit load affects the S/R machine operating cost, the AGV operating cost and the inventory holding cost. While a large unit load means a higher work-in process in each workstation, a small unit load needs frequent travels of the AGV from the kitting station to workstations. It also needs an increase in throughput requirements of the S/R machine. In addition to the unit load size, the system operating cost may be affected by the way kits are delivered from the kitting station to each workstation. In this regard, this thesis proposes three types of operating policies of AGV in delivering kits from the kitting station to each workstation of the production system. The effectiveness of these policies are examined under three different configurations of the system.
In the first part of this thesis, we consider a system which has only one assembly line served by a single AGV. For each policy, a nonlinear mathematical model is formulated. Based on the characteristics of the objective function and feasible region, a solution algorithm is developed which finds an optimum unit load size. To illustrate the validity of the models, numerical example problems are chosen and solved.
The assembly production system with multiple assembly lines served by a single AGV is treated in the second part. The cycle time of each assembly line can be different. All three operating policies are examined through analytical models.
The third part deals with the same system configuration as the second part except the number of AGV which becomes the decision variable. A heuristic procedure is proposed which finds the unit load size and AGV fleet size as well as the group of lines served by each vehicle.