Machine group selection in a flexible manufacturing cell using digraph and matrix methods

Flexible Manufacturing Cells (FMCs) represent a class of highly automated systems. The increased importance of these highly automated manufacturing systems to the survival of modern industries has resulted in increasing research efforts that address the many issues inherent in flexible manufacturing. One of the key issues is the problem of machine group selection in a FMC. Even though precision-based methods such as Multi-Attribute Decision-Making (MADM) methods, expert systems, neural networks, goal-programming methods, fuzzy algorithms, genetic algorithms, simulated annealing, etc. had been proposed in the past, these methods are knowledge-intensive, complicated, require more computation and may go beyond the capabilities of the real decision maker (i.e. user organisation). Hence, this paper presents a simple, systematic and logical methodology for machine group selection in a FMC using digraph and matrix methods. A Machine Group Selection Index (MGSI) is proposed, which evaluates and ranks machine groups for a given machine group selection problem. A step-by-step procedure for evaluation of MGSI is suggested. The unique feature of the proposed methodology is that it offers a general procedure that can be used for any type of selection problem involving any number of selection attributes. An example is included to illustrate the approach.