Cyclic Production of Flexible Manufacturing Cells

This thesis deals with two different flexible manufacturing cells. Both cells contain m identical computer numerical control (CNC) machines that are able to perform all the processes to produce a final product. The CNC machines are set up in a line layout. In the both cases, one input station and one output station exists at the beginning and at the end of the line, respectively. The items to be processed are kept in the input station, and the finished items are kept in the output station. In the second case, in addition to the input station, there is an individual input buffers attached to each machine. Using these buffers, each machine can be consecutively loaded twice in a cycle. In the both cells, a robot serves the machines and transports parts from the input station to a machine, loads the machine, and unloads the machine, after finishing its process, and puts the processed part in the output station. In these cells, m different parts will be processed in every cycle. Each part is processed completely by one machine. If the system is at a specific state at the beginning of a cycle, it reaches the same state at the end of the cycle, and then repeats the same actions in the same order in the subsequent cycles. To show all of the possible cycles in such cells, a sequential part production matrix is presented considering a general case. The duration of a cycle is called cycle time. The objective function of both cell types is to find the order of robot operations that minimizes the cycle time which maximizes the long-run average throughput rate of each cell. For the first case, a new mathematical model is presented to optimize the system. A reduced version of the new model is also provided. The reduced version is still an exact model of the minimization of the cycle time, however it does not determine the waiting times of the robot directly. These two models are more effective than the previous existed exact models in the literature. The solution of the reduced model requires significantly less CPU time comparing to the other models. A metaheuristic algorithm based on simulated annealing algorithm is proposed. In order to compute the minimum cycle time in each iteration of the algorithm, a linear programming model is needed to be solved which is the first case in the literature to the best of our knowledge. A new proof is provided for the lower bound of cycle time. This new proof facilitates the optimality analysis of several sequences of the robot movements. For the second case, a mathematical model is presented to optimize the cyclic production. A two-machine cell is discussed in details. In addition to some lower bounds of the cycle time for different orders of robot movements, the optimal cycles and upper bounds for the cases with different activities are also investigated.