*Operations Management - Emerging Trend in the Digital Era*


sector and the type of production, whether continuous or discrete, the degree of importance may change. An arithmetic mean of the values of the 3 companies was also developed in this tabulation and it was noted that from the maximum possible score of 65 points, the company 1 scored 35 points, followed by 61 points by the company 2, then the company 3 with 59 points, and the arithmetic average was

*Conceptualization, Definition and Assessment of Internal Logistics through Different…*

**4.1 Application of fuzzy logic to determine the internal logistics index of a**

diffuse model is shown in **Figure 7**. In **Figure 8** the values of Internal Logistics Index reached according to the input variables are shown. For example, if each group (from A to D) have an average value (5 points), then the Internal Logistics Index reaches a value of 37.4 points. The MATLAB allows vary input values, and

The toolbox of fuzzy logic implemented in MATLAB with the four groups of the

Another way of demonstrate the results between two groups and the Internal Logistic Index can be analyzed from **Figure 8**, where there are represented the A and B groups with the value of 5 points for each group. The maximal value of the Internal Logistic Index in this case will be of 37.50% as it is shown in **Figure 9**. It was established a comparative analysis between results of both models: Excel Tab versus Fuzzy Logic. The obtained results of the Internal Logistic Index by using

the Excel tab was of 79.17% when assessing the 13 component parts. These

*Fuzzy model for evaluating Internal Logistic Index. Source: Authors (from MATLAB).*

*Internal Logistics Index according to the input variables. Source: Authors (from MATLAB).*

**company in the industrial pole of Manaus. Case study**

consequently modifying the value of Internal Logistics Index.

*4.1.1 Internal logistics index company case study*

*DOI: http://dx.doi.org/10.5772/intechopen.94718*

51.67 points.

**Figure 7.**

**Figure 8.**

**141**

#### **Figure 6.**

*Training and retraining of the ANN. Source: Authors (from MATLAB).*

