# A Treatise on Reconnoitering the Suitability of Fuzzy MARCOS for Assessment of Conceptual Designs
## 4 Results and Discussion
### Discussion  
Considering the weighted normalized decision matrix in Table 4, a clear picture of the performance of the design alternatives with respect to the design features can be obtained in the form of TFNs. Also, an interesting aspect of the fuzzy MARCOS method is the determination of the best and worst design by selecting the design with the highest upper membership function of the TFNs in all the design features. This implies that the best design will perform well in all the design features, and the worst design will perform poorly in all the design features. Although, in real life, achieving the best design may seem a little bit difficult because a consideration of all the design features in a design may be difficult to achieve. Hence, there will be a trade-off in the design process such that some design features will not be predominantly available in the design. It is worthwhile to note that such design features are also important, but the decision to prioritize the design features has come to play in order to satisfy the features that are necessary for a robust design. Also, when there is a need to prioritize some design features, the alternatives which have the best performance in all these features can easily be identified. In essence, there is a need to classify the design features into cost and beneficial features. The separation of the design features into cost and beneficial features makes it easy to identify the design concepts that will be cost demanding, particularly before fabrication and commercialization. This will go a long way to inform the manufacturer on the logistics that will be involved in the production of the machine before the completion of the design. In this case, design for manufacturing cost and life cycle cost are considered as the cost features. The design for life cycle cost and manufacturing are the cost features as highlighted in Table 4. Considering the upper membership function of the best design concepts in the weighted normalized fuzzy decision matrix in Table 4, it is clear that concept two has the best manufacturing and life cycle costs, but that does not indicate that it is the optimal design concept. However, if the aim of the decision process is to obtain a design with less cost, then design concept two can serve as a best design. Also, it is also clear that the performances of all the design concepts in terms of the beneficial features can be captured in Table 4. This will also help to achieve the identification of design concepts with other beneficial features. Further, considering the upper membership function of the cumulative matrix for the best and worst designs in Table 5, it is obvious that none of the design concepts is closer to the best and worst designs. This is an interesting aspect of the fuzzy MARCOS model because it gives a relative comparison by providing a clear picture of the design alternatives relative to the best and worst designs. The relative position of the design alternatives to the best and worst designs can be depicted in the form of the TFNs, as presented in Figure 3a. This implies that the fuzzy MARCOS method determines a value for the best and worst designs and also provides the values for the design concepts to be assessed. This method is good because it can create a platform for comparison on the distances of the design concept to the best and worst designs. The MARCOS model further determined the optimal design alternative considering the utility degrees, fuzzy utility functions and overall utility function rather than mere defuzzification and comparison with the best and worst designs. Also, considering the comparison in Figure 3a, the model was able to establish the level of performance of the design alternatives relative to the expected performance of the best and worst designs, but a judgment on the optimal design concept