Optimization of an agv based assembly line feeding system by analytical simulation approach and taguchi design of experiments

Abstract

Automated guided vehicles (AGV) are unmanned transport systems for the transport of materials in various production environments. AGVs used to provide an efficient parts supply to the line on time and at minimum cost. In this paper we focus on minimizing the number of AGVs (AGV fleet size) and improving the utilization, which are used to feed the mixed-model assembly line at one of the major automobile assembly plants in Turkey. An analytical simulation approach is presented to optimize the AGV fleet size for the production system and AGVs utilization rates. A simulation model is presented for the production environment and validated through analytical approach from literature. Position and design of the kitting area and number of AGV trolleys are optimized using design of experiments considering the changes in different system parameters like AGV velocity, traffic interactions and battery-charging schemes. A L4 (32) orthogonal array is implemented to evaluate the optimal factor settings to optimize the number and average utilization of AGVs. The results show that presented model is an effective tool for determining the number of AGV required while maximizing the utilization rates.