Simulation and optimization of a crossdocking operation in a just-in-time environment

In an ideal Just-in-Time (JIT) production environment, parts should be delivered to the work-stations at the exact time they are needed and in the exact quantity required. In reality, for most components/subassemblies this is neither practical nor economical. In this study, the material flow of the crossdocking operation at the Toyota Motor Manufacturing plant in Georgetown, KY (TMMK) is simulated and analyzed.; At the Georgetown plant between 80 and 120 trucks are unloaded every day, with approximately 1300 different parts being handled in the crossdocking area. The crossdocking area consists of 12 lanes, each lane corresponding to one section of the assembly line. Whereas some pallets contain parts designated for only one lane, other parts are delivered in such small quantities that they arrive as mixed pallets. These pallets have to be sorted/crossdocked into the proper lanes before they can be delivered to the workstations at the assembly line. This procedure is both time consuming and costly.; In this study, the present layout of the crossdocking area at Toyota and a layout proposed by Toyota are compared via simulation with three newly designed layouts. The simulation models will test the influence of two different volumes of incoming quantities, the actual volume as it is now and one of 50% reduced volume. The models will also examine the effects of crossdocking on the performance of the system, simulating three different percentage levels of pallets that have to be crossdocked.; The objectives of the initial study are twofold. First, simulations of the current system, based on data provided by Toyota, will give insight into the dynamic behavior and the material flow of the existing arrangement. These simulations will simultaneously serve to validate our modeling techniques. The second objective is to reduce the travel distances in the crossdocking area; this will reduce the workload of the team members and decrease the lead time from unloading of the truck to delivery to the assembly line. In the second phase of the project, the design will be further optimized. Starting with the best layouts from the simulation results, the lanes will be rearranged using a genetic algorithm to allow the lanes with the most crossdocking traffic to be closest together.; The different crossdocking quantities and percentages of crossdocking pallets in the simulations allow a generalization of the study and the development of guidelines for layouts of other types of crossdocking operations. The simulation and optimization can be used as a basis for further studies of material flow in JIT and/or crossdocking environments.