Dynamic takt time decisions for paced assembly lines balancing and sequencing considering highly mixed-model production: An improved artificial bee colony optimization approach

Abstract

Balancing and sequencing are two important problems in paced assembly lines planning. Many studies use a precedence graph to solve the problems. Fixed takt time (fTT) is used as the paced value of assembly lines, which ignores the real-time status of assembly lines. By analyzing the position of each product on the assembly lines and the working time of the current assembly, this paper proposes to use the maximum value of the working time of each product in the current status as the value of the dynamic takt time (dTT). This method utilizes the assembly line capacity more effectively. An improved artificial bee colony (iABC) algorithm is developed to optimize balancing and sequencing simultaneously. Compared with multi-objective particle swarm optimization and non-dominated sorting genetic algorithms II, the effectiveness of the iABC algorithm is evaluated according to three performance evaluation indexes including the inverted generational distance, the spacing metric, and the set coverage metric. Case studies of different scales and the effects of fTT and dTT on idle time are analyzed, verifying the rationality of the proposed dTT method.