Flexible Manufacturing Cell Formation Using Genetic Algorithms:

Industries are embracing the concepts of agile manufacturing, flexible manufacturing and group technology, which favor nimble principles over the aging techniques of mass production. Cellular manufacturing is the implementation of group technology (GT) to the manufacturing process.

The major contributions of this thesis may be stated as:

1. This cell formation methodology offers improved flexibility since it allows the cell designer to use the grouping efficacy or the travelling salesman problem formulation as objective functions and to incorporate design constraints during cell formation. These capabilities allow alternative cell configuration to be generated and reviewed easily.

2. Using metalevel GA where the control parameters i.e. population size, target standard deviation, mutation rate and crossover rates are determined by the first level GA and used to solve the second level GA, which gives the cell formation problem solutions.

3. A MATLAB software is constructed to handle the whole process of solving the cell formation problem, by controlling and monitoring each step in generating near-optimal solution.

4. A comparative study has been conducted between the GA solutions and the benchmark solutions to the problems adopted from the literature. This comparison is done using grouping measures such as grouping efficiency, grouping efficacy and cell index. The results obtained are at least equal to any previously reported results.