## 8 Conclusions  
This research work proposes a new strategy for simulating echolocation in order to address methods to solve real-time planning problems, taking advantage of the possibilities offered by new technologies in terms of real-time data acquisition and communication. This approach can serve as an alternative or as a complement to the methods used to solve this problem, instead of the approach of developing heuristic algorithms, which by definition can only provide approximate solutions to the problem.  
An Industrial Sonar algorithm has been developed that can be used to optimise scheduling at different work centres while meeting the objectives of reducing the makespan, reducing the transport time of AMRs and reducing the energy costs and carbon footprint. Thus, this work presents a new methodology for real-time planning that combines different strategies to reduce production times and transport times, minimise energy costs and decrease the carbon footprint, and thus responds to a gap in the literature by integrating these variables and objectives in order to analyse and study production scheduling alternatives that incorporate operational and sustainable aspects into productive environments.  
Furthermore, this new strategy can be used as a corrective strategy, to respond to difficulties that may arise during production, and also as a predictive and preventive simulation tool to design more flexible production processes capable of reacting quickly to any circumstance.  
On the other hand, the Industrial Sonar algorithm proposes a flexible strategy that can be applied to any type of company or industry, adapting to the specificities of each business by using the most appropriate communication method and the most appropriate combination of algorithms at each work centre for that business.  
As a potential future development, the real-time application of the Industrial Sonar algorithm between work centres can be compared and combined with other heuristic algorithms used to calculate the production schedule of all production centres. This would allow for conclusions to be drawn about the response times, the flexibility and the validity of the results in terms of time and energy losses.  
As a future task, we propose applying this algorithm to various business processes to determine the most suitable communication methods for each process and the most effective combination of algorithms for each work centre.  
As a suggestion for future research, the Industrial Sonar algorithm could be applied as a virtual tool for designing flexible production processes that can quickly adapt to any circumstance. This proposal would be specifically aimed at certain types of industry, but it could be extended to all.  
As a future project, we propose linking the Industrial Sonar algorithm with MES/ERP production control programs. This will automate not only the programming in real time, but also its automatic application in production, including the management of the movement of AMRs between work centres.  
Conceptualisation, F.B. and M.-P.L.; methodology, F.B. and M.-P.L.; software, F.B.; validation, F.B. and M.-P.L.; formal analysis, F.B.; investigation, F.B. and M.-P.L.; data curation, F.B. and M.-P.L.; writing--original draft preparation, F.B.; writing--review and editing, F.B. and M.-P.L.; visualisation, F.B., M.-P.L., J.-A.R., P.M. and J.-C.S.; supervision, M.-P.L. and J.-A.R.; project administration, F.B., M.-P.L., J.-A.R., P.M. and J.-C.S. All authors have read and agreed to the published version of the manuscript.  
This research received no external funding.  
Data Availability Statement: The data presented in this study are available on request from the corresponding author. Data are unavailable due to privacy.  
Conflicts of Interest: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.