Back close

A Simulated Annealing Algorithm for Machine Cell Formation Under Uncertain Production Requirements

Publication Type : Journal Article

Publisher : Arabian Journal for Science and Engineering

Source : Arabian Journal for Science and Engineering, Volume 39, Issue 10, p.7345-7354 (2014)

Url :

Campus : Chennai

School : School of Engineering

Center : Research & Projects

Department : Mechanical Engineering

Year : 2014

Abstract : Due to customized products, shorter product life cycles, and unpredictable patterns of demand, the manufacturing industries are faced with stochastic production requirements. The production requirements (product mix and demand) may not be known exactly at the time of designing the manufacturing cell. It is likely that a set of possible production requirements (scenarios) with certain probabilities may be given at the design stage. Though a large number of research works on manufacturing cell have been reported, very few of them have considered random product mix constraint at the design stage. This paper presents a nonlinear mixed-integer mathematical model for the cell formation problem with the uncertainty of the product mix for a single period. The model incorporates real-life parameters such as alternate routing, operation sequence, duplicate machines, uncertain product mix, uncertain product demand, batch size, processing time, machine capacity, and various cost factors. The cost factors considered are machine amortization costs, operating costs, inter-cellular material handling costs, and intra-cellular material handling costs. A consultancy work is carried out for the proposed auto-components manufacturing industry to be located in the suburb of Chennai. In this paper, a solution methodology for best possible cell formation using simulated annealing algorithm is presented and the computational procedure has been illustrated for the case study undertaken.

Cite this Research Publication : Jayakumar V. and Raju, R., “A Simulated Annealing Algorithm for Machine Cell Formation Under Uncertain Production Requirements”, Arabian Journal for Science and Engineering, vol. 39, no. 10, pp. 7345-7354, 2014.

Admissions Apply Now