There is a lot of talk about autonomous vehicles, and Europe is very much focusing on their use and deployment. However, the field use of these vehicles is still very limited. The proposed research refers to a specific category of autonomous vehicles, that is, small ground autonomous vehicles circulating in pedestrian environments, with a focus on their use in operating logistical services. More precisely, this paper presents data collected during a challenging experiment carried out in the city of Trikala, Greece, in the context of the major European project “SHOW”. A statistical analysis of these sampled data concerning service times, in terms of commercial speed, for collecting organic waste from cafeterias is presented. The aim of this paper is to verify whether data collected from autonomous vehicles used for this service are reliable and whether accurate estimates can be derived from these data to be used as standard parameters of these vehicles. For these reasons, we analyze the operational performance of the service performed by small autonomous vehicles, with particular attention to the interactions between them and pedestrians and the ability of users to load and unload small vehicles. More precisely, we verify whether there is an adaptation period in which human–vehicle interactions become smoother and whether commercial speed varies at different times of day, that is, if there are peak periods in which droid speed is limited because of the intensity of interactions with pedestrians. A statistical analysis of these data is proposed to find answers to these research questions. It made it possible to highlight an adaptation curve of humans to droids and that no peak periods emerged where droid speed was limited because of the intensity of interactions with pedestrians. This result is probably related to the fact that stability of service operation was not achieved. Had the period of experimentation been extended, it would probably have been possible to identify peak and off-peak periods and the relative commercial speeds. However, it is important to note that the achievement of service operation stability takes a long time. The results obtained are interesting and contribute to the current state of knowledge. In fact, data analyzed here are collected on public land, refer to interactions that take place between small autonomous ground vehicles and a heterogeneous population, and therefore constitute a starting point for the development of technologies that facilitate human–driver interactions and thus lead to an improvement in the performance of sustainable logistics services managed by autonomous vehicles and facilitate their dissemination.

La aplicación de SMED (Single Minute Exchange of Die o cambio de matriz en menos de 10 minutos) no solo conlleva una reducción en los tiempos de cambio de maquinaria, sino que también reduce otros tipos de pérdidas que ocurren en el lugar de trabajo y que todas las empresas consideran altamente significativas debido al contexto industrial y social en el que operan. La metodología propuesta integra el análisis previo tanto de la maquinaria como del proceso, el análisis y estructuración de tareas, la experiencia del personal involucrado en la aplicación de SMED, herramientas que apoyan a SMED, sistemas de análisis y estandarización KPI/KAI (indicadores clave de rendimiento/indicador de actividades clave). Esto permitirá reducir otras pérdidas en el lugar de trabajo, como accidentes laborales y defectos del proceso que pueden llevar a productos de baja calidad, así como el monitoreo continuo de la maquinaria para reducir el número de averías, entre otros. Este artículo muestra que la aplicación de SMED aporta disciplina, análisis de tareas y una mejor comprensión de la maquinaria y la experiencia del trabajador, al mismo tiempo que ayuda a mejorar los comportamientos, aspectos indispensables al buscar mejoras. El uso de los indicadores de rendimiento establecidos ha sido clave para demostrar que si se disminuyen los accidentes laborales y los costos de fabricación, se aumenta la calidad del producto fabricado. Palabras clave: SMED, Cero pérdidas; 5 porqués; Análisis de paradas; 12 pasos The application of SMED (Single Minute Exchange of Die) gives rise to more than just reduced machinery changeover times. Correct application of SMED also reduces other types of losses which occur in the workplace and which all companies consider highly significant because of the industrial and social context in which they operate. The proposed methodology integrates prior analysis of both machinery and process, analysis and structuring of tasks, the expertise of personnel involved in applying SMED, tools that support SMED, KPI/KAI (Key Performance Indicator/Key Activities Indicator) analysis systems and standardisation. This will enable reductions in other workplace losses, such as occupational accidents and process defects that can lead to poor-quality products, as well as continuous monitoring of the machinery to reduce the number of breakdowns, etc. This article shows that the application of SMED brings discipline, task analysis, and a better understanding of machinery and worker expertise, at the same time helping to improve behaviours - indispensable aspects when seeking improvements. Usage of the performance indicators set out has been the key to demonstrating that if workplace accidents and manufacturing costs are decreased, the quality of the manufactured product is increased. Keywords: SMED; Zero losses; 5 Whys, Breakdown Analysis; Twelve Steps

This study investigates the integration of advanced optimization algorithms within energy-intensive infrastructures and industrial plants. In fact, the authors focus on the dynamic interplay between computational intelligence and operational efficiency in wastewater treatment plants (WWTPs). In this context, energy optimization is thought of as a hybrid process that emerges at the intersection of engineered systems, environmental dynamics, and operational constraints. Despite the known energy-intensive nature of WWTPs, where pumps and blowers consume over 60% of total power, current methods lack systematic, real-time adaptability under variable conditions. To address this gap, the study proposes a computational framework that combines hydraulic simulation, manufacturer-based performance mapping, and a Memetic Algorithm (MA) capable of real-time optimization. The methodology synthesizes dynamic flow allocation, auto-tuning mutation, and step-by-step improvement search into a cohesive simulation environment, applied to a representative parallel-pump system. The MA’s dual capacity to explore global configurations and refine local adjustments reflects both static and kinetic aspects of optimization: the former grounded in physical system constraints, the latter shaped by fluctuating operational demands. Experimental results across several stochastic scenarios demonstrate consistent power savings (12.13%) over conventional control strategies. By bridging simulation modeling with optimization under uncertainty, this study contributes to sustainable operations management, offering a replicable, data-driven tool for advancing energy efficiency in infrastructure systems.