The goodness of machine-part groups in cellular manufacturing systems is evaluated by different measures available in the literature. The commonly known grouping efficiency measures will be discussed in this paper. None of these measures has the ability to evaluate the efficiency of block -diagonal system and sub-system at the same time. Moreover, sparsity of individual cells was not taken into consideration in these measures. In this paper, a new grouping measure called Comprehensive Grouping Efficacy (CGE) is proposed to overcome the drawbacks of these measures. CGE is tested against some problems from the literature and the results demonstrate the ability of this measure to be used as comprehensive grouping measure since four of the well-known measures are included in the CGE formula. The superiority of CGE is that it can be used to find the efficiency of block-diagonal form, the efficiency of sub-system, sparsity index and efficacy index at the same time, which will give the designer the opportunity to control the cell size. Without knowing the efficiency of sub-systems (individual cells), the system designer will not be able to control the cell size.

Optimality and efficiency are two measures that can be used by the system designer to select or compare between different optimal layouts. At the same time, the system designer has three choices of part assignment to cells in accordance with his needs (minimum sum of voids and /or exceptions). Unfortunately, the impact of choosing the type of part assignment on optimality and/or efficiency is not taken into consideration in any previous studies. In this paper, a critical analysis of the impact of part assignment in cellular manufacturing systems is elaborated on three cases borrowed from the literature. In the first case study, different grouping efficiency measures were used on two different optimal distributions having the same number of cells. These measures give different conflict evaluations, for that the designer’s decision to choose the optimal solution depends on the optimality rather than the efficiency. For the second case, the analysis was performed using three types of part assignment on the same optimal system (same number of cells). The results showed that the designer’s decisions depend on the constraints on the shop floor, since there is a conflict between the efficiency and the optimality. For the third case, one type of part assignment was executed on one system with different number of cells and the designer takes his decision based on the efficiency.