A Mathematical Model for an Integrated Assembly Line Regarding Learning and Fatigue Effects

In this paper, an integrated mathematical model for the balancing and sequencing problems of a mixed-model assembly line (MMAL) is developed. The proposed model minimizes the total overload and idleness times. For the sake of reality, the impact of operator's learning and fatigue issues on the optimization of the assembly line balancing and sequencing problems is considered. Furthermore, it is assumed that the Japanese mechanism is used in this assembly line to deal with the overload issue. With respect to the complexity level of the proposed model, a genetic algorithm is developed to solve the model. In order to set the parameters of the developed genetic algorithm, the well-known Taguchi method is used and the efficiency of this solution method is compared with the GAMS software using several test problems with different sizes. Finally, the sensitivity of the balancing and sequencing problems to the parameters such as station length, learning rate, and fatigue rate are analyzed and the impact of changing these parameters on the model is studied.

Automated summary

This paper proposes an integrated mathematical model for balancing and sequencing problems of a mixed-model assembly line, taking into consideration operator's learning and fatigue, as well as the use of Japanese mechanism. A genetic algorithm is developed to solve the complex model, with parameters set using the Taguchi method. Sensitivity analysis is conducted on parameters such as station length, learning rate, and fatigue rate.