An enhanced Tabu search Cell formation Algorithm for Cellular Manufacturing System

The major benefit of using Cellular manufacturing systems (CMS) is the improvement in efficiency and reduction in the production time. In a CMS the part families and machine parts are identified to minimise the inter and intracellular movement and maximise the utilisation of machines within each cell. Many scholars have proposed methods for the evaluation of machine cell part layouts with single routes; this paper introduces a modified Hybrid Tabu Search Algorithm (HTSA) referred to as Hybrid Algorithm in this study for machine cell part layouts having multiple routes as well. The primary objective of this paper is to minimise the inter and intracellular movement using a hybrid algorithm. The paper presents a comparative analysis of the existing and the proposed algorithms, proving that the proposed hybrid algorithm is simple, easy to understand, and has a remarkable efficiency with a runtime of 5.6 seconds.

Calibration of GA Parameters for Layout Design Optimization Problems Using Design of Experiments

In manufacturing-cell-formation research, a major concern is to make groups of machines into machine cells and parts into part families. Extensive work has been carried out in this area using various models and techniques. Regarding these ideas, in this paper, experiments with varying parameters of the popular metaheuristic algorithm known as the genetic algorithm have been carried out with a bi-criteria objective function: the minimization of intercell moves and cell load variation. The probability of crossover (A), probability of mutation (B), and balance weight factor (C) are considered parameters for this study. The data sets used in this paper are taken from benchmarked literature in this field. The results are promising regarding determining the optimal combination of the genetic parameters for the machine-cell-formation problems considered in this study.

CELLULAR MANUFACTURING LAYOUT DESIGN USING HEURISTIC CLUSTERING ALGORITHM AND LPP MODEL

This mathematical model forms machine cells, optimises the costs of unassigned machines and components, and designs the shop floor cell layout to have minimal movement of materials. The complete similarity measure algorithm forms machine cells and part families in a refined form. Later, exceptional elements are eliminated in the optimisation model by using machine duplication and sub-contracting of parts. Then the shop floor layout is designed to have optimised material movements between and within cells. An evaluation of the cell formation algorithm’ performance is done on the benchmark problems of various batch sizes to reveal the process’s capability compared with other similar methods. The data of machining times are acquired and tabulated in a part incidence matrix, which is used as input for the algorithm. The results from the linear programming optimisation model are that costs are saved, machines are duplicated, parts are sub-contracted, and there are inter- and intra- cellular movements. Finally, the output of the inbound facility design is the floor layout, which has machine cell clusters within the optimised floor area.

Machine Cell Designing for Machinaries of Leather Shoes Production Unit

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