En busca de la excelencia en logística de perecederos

El sector hortofrutícola nacional representa sobre el 40% de la producción agraria y el 30% del consumo alimenticio total español. De esta producción, entre el 92 y el 95% se exporta a la UE (13.000 millones de euros), siendo Alemania, Francia y Reino Unido los principales destinos. Para ello, el transporte por carretera es el modo más utilizado. En este sector, el binomio producción agrícola-transporte se caracteriza por una alta competitividad, márgenes estrechos y unas exigencias de los clientes en cuanto a calidad, trazabilidad y KPI´s (key performance indicators) cada vez más elevadas. Además, aparecen nuevas variables como el interés de las compañías de presentar una imagen más “verde” en sintonía con las demandas sociales. Entre ellas, la huella de carbono o la reducción del desperdicio son conceptos que cada vez nos suenan más. En relación al desperdicio, cabe destacar que la tercera parte de la producción de alimentos para consumo humano acaba en la basura de la cadena de suministro, con una ingente huella de carbono sin utilidad ninguna

¿Cómo gobiernan sus Tecnologías de la Información las universidades españolas?

Comunicación presentada en la Cuarta Conferencia de Directores de Tecnologías de Información y Comunicación de Instituciones de Educación Superior Latinoamericanas (TICAL 2014), Cancún, México, 26-28 mayo 2014.Durante los dos últimos años CRUE-TIC ha promovido la implantación de un sistema de gobierno de las TI en 8 universidades españolas. Para ello se ha utilizado el modelo GTI4U, que se ha desarrollado específicamente para el ámbito universitario, y está totalmente alineado con los principios de la norma ISO 38500. Como resultado de este proceso, somos capaces de establecer cuáles son las mejores prácticas relacionadas con el gobierno de las TI que satisfacen dichas universidades y determinar que se encuentran en un nivel de madurez incipiente aunque con una apuesta decidida por la mejora a corto plazo. También hemos estudiado los 8 casos para determinar cuáles son los factores que dificultan y cuales contribuyen al éxito de la implantación de un sistema de gobierno de las TI en una universidad. Como resultado hemos concluido que existen tres clases de universidades considerando cómo han llevado a cabo la implantación de su gobierno de las TI: defensivas, ofensivas y ofensivas punteras. Entre las conclusiones de esta experiencia podemos establecer que tanto el modelo GTI4U como la metodología utilizada son adecuados para establecer sistemas de gobierno de TI en cualquier universidad (no sólo en las españolas) y por ello consideramos que esta iniciativa es una referencia interesante para cualquier universidad que desee llevar a cabo un buen gobierno de sus TI

Application of Machine Learning to support production planning of a food industry in the context of waste generation under uncertainty

Food production is a complex process where uncertainty is very relevant (e.g. stochastic yield and demand, variability in raw materials and ingredients…), resulting in differences between planned production and actual output. These discrepancies have an economic cost for the company (e.g. waste disposal), as well as an environmental impact (food waste and increased carbon footprint). This research aims to develop tools based on data analytics to predict the magnitude of these discrepancies, improving enterprise profitability while, at the same time, reducing environmental impact aiding food waste management. A food company that produces liquid products based on fruits and vegetables was analyzed. Data was gathered on 1,795 batches, including the characteristics of the product (recipe, components used…) and the difference between the input and the output weight. Machine Learning (ML) algorithms were used to predict deviations in production, reducing uncertainties related to the amount of waste produced. The ML models had greater predictive capacity than a linear model with stepwise parameter selection. Then, uncertainty is included in the predictions using a normal distribution based on the residuals of the model. Furthermore, we also demonstrate that ML models can be used as a tool to identify possible production anomalies. This research shows innovative ways to deal with uncertainty in production planning using modern methods in the field of operation research. These tools improve classical methods and provide production managers with valuable information to assess the economic benefits of improved machinery or process controls. As a consequence, accurate predictive models can potentially improve the profitability of food companies, also reducing their environmental impact.</p

APPLICATION OF THE EXTENDED MRP THEORY TO A BABY FOOD COMPANY

Actual markets require companies to think about new ways to improve their business or to get additional advantages from their existing competences. Such improvements should not be limited to optimisation of individual activity cells but should be the result of broader analyses. Companies should consider their whole supply chains and make deep observation of dependencies between individual activity cells. Material requirements planning (MRP) Theory has proved to be a successful tool for describing and evaluating multistage, multilevel production systems with the use of Net Present Value (NPV) calculation. Recently, this theory has been extended in a way that it also deals with other vital parts of global supply chains, such as distribution, consumption and the reverse logistics. We call this approach the Extended MRP Theory (EMRP Theory). This paper shows how EMRP Theory can be used in analysing business processes for a Spanish company dedicated to baby food production

Comparison of Two Network-Theory-Based Methods for detecting Functional Regions

Background: Functional regions are abstract, uniformly defined territorial units that form an important basis for many development strategies of a country or a region. Objectives: This study analyses the application of network theory to the detection of such regions. Methods/Approach: Functional regions are analysed using two methods based on the graph theory: the Walktrap algorithm and the chain approach. The quality of the two regionalization methods is analysed using the fuzzy set theory with the revised method. Slovenia was used as a case study. Results: The Walktrap algorithm generated eight functional regions; seven of them corresponded to those identified in previous studies. The only difference occurred in the northwestern mountainous part of Slovenia. The chain approach led to similar results, although it resulted in a huge functional urban region of the capital Ljubljana. Conclusions: The results show that the Walktrap algorithm calculates regions that are more closed, where more workers find work in the home region, than the chain approach

On the construction of a Composite Index to assess holistically the sustainability of the evolution of a country

[EN] Economists establish a clear-cut distinction among the ideas of Economic Growth (EG) and Economic Development (ED) and Sustainable Development (SD). However, the definition of the second and third ones tends to be fuzzier than it is for the first one, giving room to misunderstandings and a wrong use and manipulation of ED and SD concepts. In this article, the authors propose an analysis of a territory's evolution on the basis of a composite indicator that combines both streams of thought aligned with environmental and sustainability aspects as well as economic and society factors. To reach this goal a composite indicator with a more comprehensive architecture is designed. It includes concepts of EG and ED, as well as terms of sustainable development and social welfare. The essence of the application of this indicator is to gauge the quality of a country's evolution beyond economic or development terms solely. With this aim, economic, environmental, sustainability and social fields are considered to account in the country's economic evolution computation. To obtain results, a framework to assess key relationships among society fields, a methodology which includes entropy to select best indicators and also a MCDM method to compute the Composite Indicator to Measure a Country Evolution (CIMCE) are provided. The results show that this composite index based on a robust methodology supported by the application of a MCDM method is suitable for the holistic assessment and sustainable management of the evolution of a country as a way for contributing to several Sustainable Development Goals.Hontoria-Hernández, E.; Munier-Buratti, N.; Jiménez-Sáez, F. (2023). On the construction of a Composite Index to assess holistically the sustainability of the evolution of a country. Environmental and Sustainability Indicators. 19:1-14. https://doi.org/10.1016/j.indic.2023.1002821141

The contribution of MCDM to SUMP: the case of spanish cities during 2006–2021

Sustainable Urban Mobility Plans (SUMP) are increasingly popular planning tools in cities with environmental issues where numerous actions are usually proposed to reduce pollution from urban transport. However, the diagnosis and implementation of these processes requires broad consensus from all stakeholders and the ability to fit them into urban planning in such a way that it allows the proposals to become realistic actions. In this study, a review of the sustainable urban mobility plans of 47 cities in Spain during the last 15 years has been carried out, analyzing both the diagnosis and proposal of solutions and their subsequent implementation. From the results obtained, a new framework based on a structured hybrid methodology is proposed to aid decisionmaking for the evaluation of alternatives in the implementation of proposals in SUMP. This hybrid methodology considers experts’ and stakeholders’ opinion and applies two different multi-criteria decision making (MCDM) methods in different phases to present two rankings of best alternatives. From that experience, an analysis based on the MCDM methods called ‘Sequential Interactive Modelling for Urban Systems (SIMUS)’ and weighted sum method (WSM) was applied to a case study of the city of Cartagena, a southeastern middle-size city in Spain. This analytic proposal has been transferred to the practical field in the SUMP of Cartagena, the first instrument of this nature developed after COVID-19 in Spain for a relevant city. The results show how this framework, based on a hybrid methodology, allows the development of complex decision mapping processes using these instruments without obviating the need to generate planning tools that can be transferred from the theoretical framework of urban reality.Authors acknowledge the data and institutional support given by the local authorities of the city of Cartagena to carry out this research

A MCDM methodology to determine the most critical variables in the pressure drop and heat transfer in minichannels

This paper proposes a methodology aiming at determining the most influent working variables and geometrical parameters over the pressure drop and heat transfer during the condensation process of several refrigerant gases using heat exchangers with pipes mini channels technology. A multi-criteria decision making (MCDM) methodology was used; this MCDM includes a mathematical method called SIMUS (Sequential Interactive Modelling for Urban Systems) that was applied to the results of 2543 tests obtained by using a designed refrigeration rig in which five different refrigerants (R32, R134a, R290, R410A and R1234yf) and two different tube geometries were tested. This methodology allows us to reduce the computational cost compared to the use of neural networks or other model development systems. This research shows six variables out of 39 that better define simultaneously the minimum pressure drop, as well as the maximum heat transfer, saturation pressure fluid entering the condenser being the most important one. Another aim of this research was to highlight a new methodology based on operation research for their application to improve the heat transfer energy efficiency and reduce the CO2 footprint derived of the use of heat exchangers with minichannels.Eloy Hontoria is grateful to Project RTI2018-099139-B-C21 financed by FEDER/ Ministerio de Ciencia e Innovación-Agencia Estatal de Investigación

Las competiciones académicas en el proyecto "PROMARC". El mundo de los ekranoplanos.

Las competiciones académicas han sido uno de los recursos utilizados por el proyecto europeo PROMARC, “Promoting Marine Research Careers”, con el fin de animar a la gente joven a buscar puestos de trabajo en la investigación y en la innovación en el sector de la tecnología marina. El proyecto liderado por la WEGEMT, Asociación Europea de Universidades del ámbito de la tecnología marina y ciencias afines, ha recogido la participación de ocho Universidades, tres Asociaciones Europeas y una Fundación. El diseño de ekranoplanos ha sido el centro de una de estas competiciones, finalizando con una serie de ensayos de los finalistas en el Canal de Ensayos Hidrodinámicos de la ETSI Navales de la Universidad Politécnica de Madrid. Después de una revisión de los objetivos y estructura del proyecto y del concepto de este tipo de artefactos, se describe la competición en sus aspectos principalmente técnicos, finalizando con los logros obtenido

Modelling and real-data validation of a logistic centre using TRNSYS®: Influences of the envelope, infiltrations and stored goods

In this paper, the authors aim to support users when modelling scenarios with complex processes entailing thermal loads and infiltrations. The large building analysed is a logistics centre for the replenishment and distribution of perishable foodstuffs where cold chains must be maintained. The logistics centre, with 96 loading/unloading docks, handles large turnovers of different goods. This produces heat inside the facility. Due to continuous loading/unloading, the infiltrations in the building, and the fixed and variable thermal loads, this facility consumes a large amount of energy. Aiming to optimise the centre and contribute to sustainable development goal SDG7, this building has been modelled with a classical non-D envelope using TRNBuild® and also with the more sophisticated 3D software, SketchUp®, to compare and validate their results over a year with real consumption, as well as to assess the main sources of energy consumption. To obtain reliable results, the authors provide some methodology models to identify the sources of the building's thermal losses and quantify the different sources of consumption. These models are useful tools to support decision-makers (to improve insulation and arrange loads, among other things) when trying to reduce energy use in large buildings with intense operating processes. The results indicate that by modelling the entire facility with 3D software, the model estimation differs from real consumption by around 7.22%, while using a non-D model increases the difference to 26%. Additionally, the results show that around 47% of the energy consumption in the building is due to air infiltrations during loading/unloading, 18% is due to perishable products, and around 30% is due to building insulation. The methodology and models presented here, including the possibility of modifying the thermal load profiles, have demonstrated their capacity to reduce and optimise the load demand of refrigeration for warehouses if reliable data records are available.This research was funded by RTI2018-099139-B-C21 from Ministry of Science and Innovation - National Research Agency (MCIN/AEI) 10.13039/501100011033 and by ‘‘ERDF A way of making Europe” of the ‘‘European Union”