Advanced Production Systems

coherency point of the 3XX series of Al alloys. In: Proceedings of ICAA\_11; vol. 1. September, Aachen, Germany. 2008.

[42] Arnberg L, Dahle A, Paradies C, Syvertsen F. AFS Transactions. 1995;115:

[43] Flemings MC. Solidification Processing. New York: McGraw-Hill

[44] Ohta S, Asai K. Transactions of the Japan Welding Society. 1993;24(2):

[45] Saunders N. Materials Science Forum. 1996;217(2):667-672

[47] Kantekar CS, Stefanescu DM. AFS

[48] Huang H, Suri VK, Hill JL, Berry JT. AFS Transactions. 1991;54:685-689

[49] Rapaz M. International Materials

[46] Chen JH, Tsai HL. AFS Transactions. 1990;98:539-546

Transactions. 1988;60:591-598

Reviews. 1989;34(3):93-123

2:997-1005

36

[50] Stefanescu DM, Upadhya G, Bandyopaadhyay D. Metallurgical and Materials Transactions A: Physical Metallurgy and Materials Science. 1990;

[51] Jeng S, Chai S. Materials Science

Forum. 1996;217:283-288

[52] Emadi D, Whiting L, Djurdjevic MB, Kierkus W, Sokolowski J. Metallurgical and Materials Engineering. 2004;10:91-106

Inc.; 1974. pp. 60-166

Mass Production Processes

pp. 1-12

753-759

131-139

Chapter 4

Abstract

1. Introduction

39

A Methodology to Design

and Balance Multiple Cell

Manufacturing cell formation and its balance in just-in-time (JIT) type production environments have usually been studied separately in the literature. This practice is unrealistic since both problems interact and affect each other when the cells are operating. This chapter proposes a methodology to design multiple manufacturing cells and simultaneously balance their workload. The cells considered are U-shaped and process mixed models of product families. A nonlinear integer programming mathematical model is proposed, which integrates cell formation and their balancing, considering various production factors. For

illustration, the method is applied to the redesign of a rack manufacturing process.

Group technology (GT) can be defined as a manufacturing philosophy identifying similar parts and grouping them together to take advantage of their similarities in manufacturing and design [1, 2]. Cellular manufacturing (CM) is an application of GT and has emerged as a promising alternative manufacturing system [3]. When a productive system is changed to make it cellular, it implies solving the manufacturing cell formation problem (MCFP), which means identifying groups of machines and associating them with product families so that the intercellular traffic that the products can have within the productive system is minimized. This problem has been approached historically by analyzing the machine-product incidence matrix (A), where each row represents a machine and each column represents a product, with each element aij equal to one if machine i processes product j, and equal to zero otherwise. When this matrix is partitioned arbitrarily, it is usual to have products that remain outside the diagonal blocks (cells), which are called exceptional elements, since they carry out intercellular movements. Papaioannou and Wilson [3] reviewed the approaches between 1997 and 2008 to solve the above problem, proposing taxonomy based on the solution methodologies. It must be kept in mind that the latter approaches have started taking into account production factors other than the incidence matrix, like processing time, demanded production volumes, and operation sequences. Most recent works [4–7] are oriented mainly to the heuristic and metaheuristic approach to solve the problem, without considering

Keywords: manufacturing cells, assembly line balancing, N U-lines,

mathematical programming, mixed model production

Manufacturing Systems

Luis Valdivia and Pedro Palominos
