Optimization of Intra-Cell Operator Allocation and Product Sequencing using GA and PSO in Cellular Manufacturing

In cellular manufacturing, Scheduling and allocation of resource are the most critical decisions making process under labour-intensive manufacturing cells. Labour-intensive cells consist of smaller and simpler Equipment and machines that can be easily moved from one place to other, but require continuous monitoring and operator involvement. Hence assigning operators to each machine for various operations becomes a significant task. As the number of operations and machines increase, allocating operators to each operation becomes indigenous and adding more product varieties for production would lead to additional complications in transferring the operators between operations. Subsequently, when different products are released for production at random, the number of operator transfers increase, leading to excess time and production loss. Thus the products need to be sequenced in order to minimize operator transfers. In this paper, the operator allocation decisions are arrived in sequence using Genetic Algorithm for operator allocation and particle swarm optimization for product sequencing. This proposed algorithm is a novel approach to calculate operator allocation, product sequencing and results are found significant.