## 5 Discussion  
Based on the initial test setups that we configured and the test results obtained from those configuration settings, up to the engineer's validation on the test results, we can say that the Fuzzy Logic rules that were initially configured based on logical assumptions are close to accuracy. Only one test result was disagreed with by field engineers as this would produce a high cost for final cost justification in an actual setting. From all the tests performed and achieved results, it is shown how much each of the tested indicators impacts other factors in any smart manufacturing system (SMS) configurations. Therefore, engineers in any manufacturing industry must determine the best configuration setup for any production process in the manufacturing environment. This is important as we can see that different arrangements could lead to different values for Lead time, Quality, and Cost, which would directly impact the cost justification of the final product. For example, if in any manufacturing setup where the Lead time will become high, this will affect the quality of the product and the production cost, affect the quality of the product and the production cost, and directly impact the cost justification of the final product. As shown in Figure 3 earlier, for a sample of different manufacturing setups, these will have different values for each factor. For instance, under the setup where the number of raw materials that need to be processed is higher than the number of machines and operators available to process them, the Lead time is expected to become high as the waiting time for each of the raw materials to be processed will increase, thus causing some of the raw materials to be expired and be disposed of, which will increase the production cost again, but the quality of the product itself may turn out to be low quality as it was put on hold in the queue for a more extended period. In this type of setting, the final cost justification is expected to be high as tested and shown in Configuration 3 Test 2 (C3 T2), where the Lead time and Cost are set as high value, accompanied by a low value for Quality. Therefore, any decision-making is best accompanied with actual data and visualized simulation results to assist any manufacturing industry to make the best decision for the configurations needed to produce the best and most efficient result with high-quality products and reasonable cost justification. We have tested and validated in this section that fuzzy Logic-based simulation will contribute greatly to this decision-making process. As recommended during the test results' validation by the actual field engineers, the production line in a manufacturing company requires low lead time, good or best quality, and low production cost in order to sell the final products at a low and reasonable cost. High lead time and high production cost will increase the final cost. Therefore, initial planning for the configuration setup can also prevent lead time from being compromised, as recommended during the validation. Manufacturers should adhere to the best configuration setups to achieve the best results. The developed evaluation model can play a significant role in this decision-making process as the satisfaction rate for this model has been proven to be more than 80%, which is considered close to accuracy in the actual manufacturing world.