## 7 Summary of the Analysis of Maturity of Luanda's Region Industries  
To summarise the results of the analysis, the responses were the following:  
1. Simple table of the percentages when the dimension reached 4 or more. 2. Analysis of the probability of the responses being lower than the centre of the scale and classification of the group's response: 1. Density curves of the responses of the items by individual dimension, but summarised in Figure 18 with the overlap of all density curves. 2. Overlapping the cumulative distribution curves of responses by dimension (see Figure 19). 3. Analysis in Table 21 of the percentages when the dimension reached 4 or more. Table 21 shows that knowledge (28.5%), use of Lean tools (10.8%), and the practice of continuous improvement (12.5%) are very low. The other four practices, namely customer value, value chain, use of pulled production, and continuous flow, gave average results between 42 and 57%, showing that, in fact, the value of maturity is very low. The median value of these four practices was affected by the big industries, which raised the numerical value. Figures 19 and 20 and Table 22 show that, of the 39 variables analysed, 25 are highly likely to be correct, so Figure 21 can be presented. \begin{table}
\begin{tabular}{l c} \hline \hline
**Analysis Performed** & **Compatibility Percentage** \\ \hline
4.1—Tool knowledge analysis. & 28.5\% \\
4.2—Tools analysis of use. & 10.8\% \\
4.3—Value to the client (VC). & 45.4\% \\
4.4—Customer value (CV. & 50.0\% \\
4.5—Use of the pull production system (PPS). & 42.8\% \\
4.6—Use of continuous production flow (CPF). & 57.2\% \\
4.7—Continuous improvement analysis (CI). & 12.5\% \\ \hline \hline \end{tabular}
\end{table} 
Table 21: Percentages when the dimension reached 4 or more. Figure 19: Overlapping density curves for item responses by dimension. \begin{table}
\begin{tabular}{c c c c} \hline \hline
**Dimensions** & **Item** & \(\mathbf{p}\) & **Evaluation** \\  & & **(Answer \textless{} 3)** & **(Cut off = 0.5)** \\ \hline \multirow{8}{*}{Customer Value} & 1.1. Customer needs. & 0.0163 & High \\  & 1.2. Order production. & 0.3886 & High \\  & 1.3. Satisfaction survey. & 0.6778 & Low \\  & 1.4. Registration of complaints. & 0.3037 & High \\  & 1.5. Handle complaints. & 0.3978 & High \\  & 1.6. Produce by quality. & 0.0242 & High \\  & 1.7. Accomplish deadlines. & 0.1003 & High \\  & 1.8. Distribute products. & 0.4650 & High \\  & 1.9. Meetings with customers. & 0.6299 & Low \\  & 1.10. Adjustment to purchasing power. & 0.3947 & High \\  & 1.11. Providing information. & 0.1803 & High \\ \hline \multirow{8}{*}{Value Chain} & 2.1. Valuing activities of value. & 0.1174 & High \\  & 2.2. Stock registration. & 0.0146 & High \\  & 2.3. Process time calculation. & 0.2328 & High \\  & 2.4. Identify delay time. & 0.7260 & Low \\  & 2.5. Graphing the process. & 0.4649 & High \\  & 2.6. Track the entire process. & 0.2737 & High \\ \hline \multirow{8}{*}{Pull Production System} & 3.1. Produce by demand. & 0.2032 & High \\  & 3.2. Plan daily production. & 0.5024 & Low \\  & 3.3. Supply MP warehouse. & 0.7883 & Low \\  & 3.4. Level production by demand. & 0.2143 & High \\  & 3.5. Stock location. & 0.0825 & High \\  & 3.6. Visual production devices. & 0.4187 & High \\  & 3.7. Anomaly detection control. & 0.5048 & Low \\ \hline \multirow{8}{*}{Continuous Production Flow} & 4.1. Interconnection in the process. & 0.0001 & High \\  & 4.2. Sequencing operations. & 0.0124 & High \\ \cline{1-1}  & 4.3. Process by unit. & 0.3686 & High \\ \cline{1-1}  & 4.4. Produce as planned. & 0.0412 & High \\ \cline{1-1}  & 4.5. Sort machines by sequence. & 0.0011 & High \\ \cline{1-1}  & 4.6. Absence of interruptions. & 0.6340 & Low \\ \cline{1-1}  & 4.7. Absence of delays. & 0.6235 & Low \\ \hline \hline \end{tabular}
\end{table} 
Table 22: Probability of responses being lower than the centre of the scale and classification of the group’s response. Figure 20: Overlapping the cumulative distribution curves of responses by dimension.