Indian Journal of Fundamental and Applied Life Sciences ISSN: 2231– 6345 (Online) An Open Access, Online International Journal Available at www.cibtech.org/sp.ed/jls/2015/02/jls.htm 2015 Vol. 5 (S2), pp. 1891-1902/Ansari and Arghish Research Article © Copyright 2014 | Centre for Info Bio Technology (CIBTech) 1891 A BI-OBJECTIVE MODELING FOR A CELLULAR MANUFACTURING SYSTEM DESIGN USING FUZZY GOAL PROGRAMMING UNDER UNCERTAINTY Meysam Ansari 1 and *Omid Arghish 2 1 Department of Management, Yasouj Branch, Islamic Azad University, Yasouj, Iran Department of Management, Kohkiluyeh and Boyerahmad Science and Research Branch, Islamic Azad University, Yasouj , Iran 2 Department of Industrial Engineering, Gachsaran Branch, Islamic Azad University, Gachsaran, Iran *Author for Correspondence ABSTRACT Cell formation problem is an important issue in designing cellular manufacturing systems. Most studies in this field in have been done in two-dimensional piece-machine matrix. Since the worker has an important role in getting things done, worker assigned to the cell is important for designing cellular manufacturing system to be more consistent with a competitive market environment. A mathematical a bi-objective model is presented for the problem of cell formation under conditions of uncertainty with regard to the worker in this thesis which involves aims to analyze the effectiveness of system measures to form optimize cell line production with minimal costs and exceptional elements in the cubic space of the worker-piece-machinery matrix. To demonstrate the performance and a better understanding of the proposed model, an illustrative example based on literature of Branch and Bound Method using Lingo software package through fuzzy goal programming technique has been resolved and the results are proposed. Keywords: Cellular Manufacturing System, Cell Formation, Queuing Theory, Exceptional Elements in Cell Formation, Uncertainty and Fuzzy Goal Programming INTRODUCTION In competitive environments, markets are heterogeneous and constantly changing. Production is appropriate based on a lie just under changing demand. Ability to design and operation of manufacturing firms that can rapidly and effectively adapt to technological change and market needs is very important in the success of any manufacturing organization. The manufacturing firms should be able to provide very high levels of elongation. In order to maintain profitability, industry executives recognized cellular manufacturing system as an efficient production system. Therefore, many companies increasingly changed their production of plant production systems to cellular manufacturing system. This system has the advantages of workshop, flexibility and higher efficiency and lower production costs. Cellular manufacturing system is an application of group technology in production and includes a series of processes on the same components (family components) by a set of machines or cell work and these series increase the competitiveness of the production system and decreases product life cycles and increases the ability to combine volume and average variety of product. Cellular manufacturing system design is called Cell Forming. Uncertainty exists about the time of the process and period between pieces entry. Random parameters can be described as continuous or discrete in unrealistic environments. If the information is specified, the uncertainty in the parameters will be used by discrete or continuous probability distribution. The scope of procedures for modeling is in a state of uncertainty such as: possible planning, queuing theory and etc (Saedi-Mehrabi and Ghezavati, 2009). The continuous probability distribution used to determine the uncertainty for the random parameters and queuing theory can be used in order to achieve the desired result. Process of the probability distribution represents that the time gap between inputs are successful and output process (servicing process) is probability distribution, which represents the customer's service