Abstract :

Authors:  Gursel Suer, Najat Al-masarwah, Omar Alhawari, C Davis   Publication date: 2017   Conference: ACMSA Conference Abstract: Cell loading and scheduling in a cellular manufacturing environment have remained subjects of intensive research over several years. A decision maker in any manufacturing company takes customer satisfaction as an essential priority where due date for customer demand should be met appropriately. This paper considers different performance measure such as number manufacturing cells, average flow time and number of tardy jobs. In cellular manufacturing context, a cell consists of machines and labors in which the number of cells is of a tremendous importance to be invested in. That is, unneeded open cells will incur extra cost for a manufacturer; therefore, the decision to avoid them is prudent. In this paper, the authors tackled the problem by using a two-phase approach. In the first phase, a mathematical model is utilized to minimize number of cells opened in the manufacturing system such that no job is tardy (i.e. number of tardy jobs ( =0)). In the second phase, another mathematical model is proposed to minimize the average flow time in the system considering the minimum number of cells ( ) obtained by the first mathematical model without violating due dates. An example problem is provided to show the proposed approach and then experimentation is run on two sets of data. The results show that the proposed 2-phase approach lowers the average flowtime while maintaining the same number of cells and with no tardy jobs as in the original 1-phase solution.