# Nesting Process Automation in the Footwear Industry: A Hybrid Approach to Minimize Material Waste
## 5 Discussion  
This paper has analyzed nesting processes applied to real-world cases of footwear component cutting. This inherently complex process is further complicated by the unique characteristics of the sector, which relies on raw materials of animal origin that are irregular both in both shape and homogeneity. Moreover, the variability across footwear models limits the practicality of using expert rule-based systems. The manual positioning used in our study has been carried out by a qualified expert with a high level of experience gained from years of practice. The learning curve depends very much on the individual's skills and cannot be quantified. For the expert, the result obtained is the best solution, but for another expert, it may be different. There is no manual positioning methodology. The expert learns how to perform the positioning from the person who teaches him and from his own experience. A comprehensive comparison has been conducted between nesting results achieved by human experts and those produced by the proposed automated systems. The results obtained by automatic positioning have achieved a similar or slightly lower use of the raw material compared to manual positioning, so that the initial objective has been met, but no improvement has been achieved in this aspect. However, the objective set with respect to the time spent on resolution has been amply met, as a drastic reduction in time has been achieved. With the NFP algorithm, good results are obtained when we have a wide variety of pieces in different sizes, where the unused material areas between two pieces can be used to place another smaller piece. This is the case in traditional or 'cemented' shoes. However, in non-conventional footwear types--the object of this paper--the number of pieces is reduced, and hybrid algorithms are the ones that have adapted better to this problem, obtaining more optimal results. The findings of this study are promising, suggesting that automated nesting systems overall can successfully match the material utilization efficiency of expert operators while offering significant advantages in processing speed, achieving a 98.26% reduction in processing time compared to manual operations. By employing hybrid algorithms based on metaheuristic approaches and greedy strategies, the study has proven that automated approaches can be particularly effective when applied to the footwear component nesting. The drastic reduction in processing time achieved by these automated systems enables manufacturers to significantly accelerate their cutting operations without sacrificing material optimization. This advancement is particularly valuable in an industry where rapid production cycles and material cost management are decisive competitive factors. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline  & & \multicolumn{3}{c}{**Nesting Jaya + NFP**} & \multicolumn{3}{c}{**Nesting NFP**} & \multicolumn{3}{c}{**Nesting Manual**} \\ \hline
**Case** & **Leather** & **Sets** & **Parts** & **T (s.)** & **Sets** & **Parts** & **T (s.)** & **Sets** & **Parts** & **T (s.)** \\ \hline
1 & 9460 & 18 & 36 & 2.547 & 19 & 39 & 3.922 & 18 & 40 & * \\
1 & 9464 & 14 & 29 & 1.812 & 15 & 31 & 2.156 & 14 & 31 & * \\
1 & 9477 & 17 & 34 & 2.296 & 18 & 38 & 3.535 & 19 & 38 & * \\
2 & 9460 & 15 The application of the strategy applied to this paper could be useful in other fields, such as communications. There is a problem of a similar nature that tries to find the best location for an array of antennas or repeaters to maximize their coverage [44]. In this problem, there are also \"forbidden\" areas where it is not possible to locate antennas or limitations in the area where repeaters can be located. Genetic algorithms have already been implemented to provide a solution [45]; however, this algorithm would make it possible to fix these zones and evolve towards the optimal solution. Future work will focus on expanding the range of nesting algorithms to further improve efficiency.