22nd International Congress of Mechanical Engineering (COBEM 2013)
November 3-7, 2013, Ribeirão Preto, SP, Brazil
Copyright © 2013 by ABCM
COMPARATIVE ANALYSIS ON MANUFACTURING CELL FORMATION
USING GENETIC ALGORITHMS
Rafael Crespo Izquierdo
1
Flávio Jose Lorini
2
Herbert Martins Gomes
3
Federal University of Rio Grande do Sul (UFRGS) - Departament of Mechanical Engineering (DEMEC), Sarmento Leite St., 425,
–Downtown , 90050-170 – Porto Alegre, RS – Brazil.
1
rcrespo9@hotmail.com ,
2
lorini@ufrgs.br,
3
herbert@mecanica.ufrgs.br
Abstract. In modern production systems it requires increasing the overall efficiency, which results in the optimization
process steps. In this context, the arrangement of an industrial layout is a fundamental concept to the effectiveness of a
system that must be considered in its design. An industrial environment can be designed with layouts of several types,
according to the diversity of items, adopted production mode and market demand. This paper discusses the design
layout of the cellular type, an arrangement used in industrial engineering that allows diversity to meet production
compatible with operational flexibility. Among the various techniques and approaches applied to the formation of
manufacturing cells, specifically here it is adopted an application of genetic algorithm, implemented using an interface
in Matlab, where several topics are covered, namely: the generation of the initial population, the chromosome coding,
operators of crossover and mutation and reliability of the proposed algorithm. The obtained results show that the
Genetic Algorithms are reliable tools for the optimization of manufacturing systems, obtaining responses that meet the
basic requirements of a cell design, and presenting convergence values in the generation of machine groups and family
of parts.
Keywords: Genetic Algorithms, Manufacturing Cells, Industrial Layout
1. INTRODUCTION
Production systems' increasing productivity demands cause the analysis of the layout to be fundamental, because
the physical arrangement of the machines in a manufacturing environment may influence the flow of production and
consequently the efficiency and cost of a production process. Nowadays, most production systems´ production is
focused on the needs of the customers "just in time" (JIT), because it is a way of avoiding stocks. This leads to the use
of cellular layouts, which are more suitable to meet this type of demand. Cellular layouts are widely applied
arrangements in engineering industry, for they enable good levels of production with desirable flexibility. In this
context various methods can be applied to form cells using specific techniques. This work aims at studying a heuristic
method related to the optimization of manufacturing systems through iterative processes, using specific functions and
convergence criteria. This paper makes use of information on production flow, with information tabulated in a matrix of
incidence part-machine.
This information is treated heuristically, associated with certain restriction conditions, aiming at the diagonalization
of incidence part-machine matrices, which consists of the formation of cells by a random combination of machines and
parts. The application is intended to define the formation of manufacturing cells, using genetic algorithms. Matlab’s
toolbox called gatool is used for the simulations. In addition, we intend to compare the results for different types of
production flow analysis (incidence part-machine matrices), verifying the efficiency of the proposed application with
respect to some examples in the literature.
1.1 Designing and Planning of an Industrial Layout
According to Slack et al.(1999), the physical arrangement or layout of a production process is related to the
physical layout of all the elements needed for the transformation of a specific product.
The importance of planning and decision making in relation to a layout is fundamental to the strategy of a company,
because a well prepared project enables a desirable performance with physical arrangements that favor the flexibility of
operations and efficiency of flows and use of the resources. Thus, it is necessary to adjust the decision of physical
arrangements in accordance with a more competitive strategy of operation. (Corrêa and Corrêa, 2006).
ISSN 2176-5480
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