Abstract
Footwear is the necessaries of life. With increasing population in the world, the footwear market value is considerable and expected to grow rapidly. In a fast growing footwear industry with increasing variety of product designs, the manufacturing process gain its difficulties. The redesign of lines is required frequently because of changes of production process. Moreover, stitching line is highly dependent on operators due to its requirements of numerous manual operations. Thus, with constrained operators and equipments, deciding the optimal assignment to workstations and design the assembly line configuration become more important. In this research, a Genetic Algorithm (GA) is proposed to solve type-E Assembly Line Balancing Problem (ALBP-E) which aims to maximize line efficiency. And based on the number of tasks, manufacturing data of two different specification are collected from a footwear manufacturing company in south China for comparison between simple and complex models. An approach of design of experiments is applied to evaluate performance of different parameters combinations. The output is analyzed and evaluated by using analysis of variance (ANOVA) and Duncan test. The proposed approach can provide applicable configuration in real environment with constrained labors and machines and is capable of increasing the production efficiency and decreasing idle time.