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This special issue of the Journal of Industrial Engineering and Management is dedicated on the most recent and relevant research, theories and practices in Industrial Engineering and Operations Management presented at the 14th International Conference on Industrial Engineering and Industrial Management and XXIV Congreso de Ingeniería de Organización - CIO 2020.The CIO 2020 was held on 9th and 10th July 2020 in Leganés - Madrid and was organized by the Universidad Politécnica de Madrid (UPM) and Universidad Carlos III de Madrid (UC3M). This conference is promoted by ADINGOR (Asociación para el Desarrollo de la Ingeniería de Organización) and AIM (European Academy for Industrial Management).

[EN] In this study, we present a methodology to build data-driven simulation models of manufacturing plants. We go further than other research proposals and we suggest focusing simulation model development under a 4-layer architecture (network, logic, database and visual reality). The Network layer includes system infrastructure. The Logic layer covers operations planning and control system, and material handling equipment system. The Database holds all the information needed to perform the simulation, the results used to analyze and the values that the Logic layer is using to manage the Plant. Finally, the Visual Reality displays an augmented reality system including not only the machinery and the movement but also blackboards and other Andon elements. This architecture provides numerous advantages as helps to build a simulation model that consistently considers the internal logistics, in a very flexible way., [ES] En este trabajo presentamos una metodología para la construcción de modelos de simulación data driven para plantas de fabricación. Se ha ido más allá de lo propuesto en otras investigaciones al enfocar el desarrollo del modelo como una arquitectura de 4 capas (red, lógica, base de datos y realidad visual). La capa de Red abarca toda la infraestructura del sistema. La capa lógica incluye el sistema de planificación y control de operaciones, y el sistema de manejo de materiales. La base de datos alberga toda la información necesaria para que represente la simulación, los resultados utilizados para analizar y los valores de la capa lógica para gestionar la planta. Finalmente la capa de realidad visual proporciona un sistema real argumentado, incluyendo no solo la maquinaria y los movimientos, sino también las pizarras y otros elementos andon. Esta arquitectura proporciona numerosas ventajas, como ayudar en la construcción del modelo que de manera consistente considera la logística interna de una manera muy flexible.

[EN] The Praktikum UPV Campus is a huge internship program geared to students still in secondary education that permits them to develop a project within research groups of the Universitat Politècnica de València (UPV). Along that week, the students participating in the program document their projects in blogs. Once the projects are over they also record some videos in which they present their work and their findings. During the next year, these students presents their material to their respective classmates, still in the secondary school, showing examples of what they can already do at the university. The Praktikum UPV Campus also permits students to discover the degrees offered by the university, its facilities, and the life at the university campus, [ES] El Campus Praktikum UPV es un gran programa de prácticas dirigido a estudiantes que se encuentran todavía en la educación secundaria y que les permite desarrollar un proyecto en dentro de uno de los grupos de investigación de la Universitat Politècnica de València (UPV). Durante una semana, los alumnos participantes en el programa documentan el desarrollo de sus proyectos en blogs. Una vez finalizados los mismos, los alumnos graban además vídeos en los que ellos mismos presentan sus proyectos y sus hallazgos. Durante el año siguiente, estos estudiantes presentan su material a sus compañeros todavía cursando la educación secundaria, mostrándoles ejemplos de lo que ellos pueden hacer ya en la universidad. El Campus Praktikum UPV también permite a los alumnos descubrir las titulaciones de grado ofrecidas por la universidad, sus instalaciones y la vida en el campus universitario., The Praktikum UPV Campus has been powered from the Vice-Rectorate of Culture and Student Affairs. It has also has been partially supported by FUNCAE (Fundacion para la Calidad en la Educacion de la Generalitat Valenciana), which has also participated in the diffusion of the program jointly with the Information Office of the University. We are greatly indebted to Mr. Fernando Leon, manager of the FUNCAE, for his support and implication that pemitted the success of this initiative. We, as designers and organizers of the program at the University, want to thank the participation of all the coordinators at the schools, teachers at the university and at the secondary schools, and of course, to all the students that have participated in the campus, who are the leading actors of all this work.

[EN] This paper presents a decision support system to simultaneously solve the supply network configuration problem and the operations scheduling problem for the machine tool industry. A novel database structure, which is able to consider alternative operations and alternative bills of material, has been used. An algorithm for complete enumeration to determine all the feasible solutions using stroke graphs is introduced. A multiagent-based simulator evaluates the different key performance indicators that the supply network deals with for each alternative solution (e.g. workload, profits, delivery times, etc.) to determine that ‘satisficed’ by the collaborative decision-making among its members. A case study based on a Spanish company that assembles highly customised machines and tools in several European plants is considered. From the experiments results based on data linked to this industry, it will be demonstrated that the tool is potentially useful for stakeholders and for the central decision-maker to make decisions collaboratively in a multisite context case, We thank the EWG-DSS and their four expert anonymous referees as well as the guest editorial board for their useful suggestions and criticism on earlier versions of this paper. The research leading to these results has received funding from the European Community's Seventh Framework Programme (FP7/2007-2013) under grant agreement no. NMP2-SL-2009-229333 and has been partially supported by the Spanish Ministry of Science and Innovation within the 'Proyectos de Investigacion Fundamental No Orientada Programme' through Project 'CORSARI MAGIC DPI2010-18243'. Julien Maheut holds a VALi+d grant funded by the Regional Valencian Government (Ref. ACIF/2010/222).

[EN] This paper presents a simulation model that has been created to support decision-making during the layout redesign of an engine and transmission assembly plant in the automotive sector. The plant requires a new layout and supply logistic due to an increase in its complexity and daily production. Discrete event simulation has been used to validate an initial proposal and to propose different what-if scenarios of layout and operations management systems. These scenarios will be evaluated regarding materials flow generated throughout the plants. The main focus of the decision process was focused on safety issues related to the material handling. The simulation model and its description have been done according to the methodology proposed in Sáez Más, García Sabater, Morant Llorca, y Maheut (2016), where the simulation model is focus as a 4-layer architecture (network, logic, database and visual reality). The achieved model is very flexible and modular, and it allows to save modelling time because of the parameterize of different combinations in layout and operations management., [ES] Este trabajo presenta un modelo de simulación, que se ha creado para apoyar el rediseño de las instalaciones de una planta de montaje de motores y transmisiones en el sector del automóvil. La planta requiere de un nuevo layout y logística de aprovisionamiento, debido a un aumento en su complejidad y su producción diaria. La simulación por eventos discretos se utiliza para validar una propuesta inicial y proponer diferentes escenarios what-if de distribución y gestión de las operaciones. Estos escenarios se evalúan considerando el flujo de material generado a lo largo de las instalaciones. El principal objetivo durante la toma de decisiones se centra en aspectos de seguridad relacionados con el movimiento de material. La construcción de modelo de simulación y su descripción en el documento se realiza según la metodología propuesta en Sáez Más, García Sabater, Morant Llorca, y Maheut (2016) donde, el modelo de simulación se enfoca como una arquitectura de 4 capas (red, lógica, base de datos y realidad visual). El modelo obtenido resulta ser muy flexible y modular, lo que permite un ahorro de tiempo de modelado considerable, al parametrizar las diferentes combinaciones de distribución y de gestión de las operaciones.

The aim of this paper is to present a coordination mechanism between MILP models for planning operations within an integrated planning tool. The mechanism presented allows co-ordinate planning models between different domains (procurement, production, transportation), the different planning horizons (mid-term, short-term and very short-term) and between the different planning periods. This mechanism has been design to ensure coordination and integrity between the different plans while meeting the expectations of the different stakeholders involved in the planning process of an automotive plant. The proposed mechanism was implemented in an Advanced Planning and Scheduling system for an engine assembly company.

Part 1: Sustainability; International audience; A trend in up-to date developments in multi-site operations planning models is to consider in details the different ways to produce, buy or transport products and the distributed decision-making process for operations planning. One of the most generic approaches to support global optimization in those supply chain networks by considering all the different operations alternatives and product structures is the Generic Materials & Operations Planning Problem. This problem can be modelled by a Mixed Integer Linear Programming model capable of considering production, transportation, procurement tasks and their alternatives and other relevant issues such as packaging. The aim of this paper is to introduce the implementation of a parallelizable heuristic method for materials and operations planning and its application to a case of a Supply Chain Network of the automotive industry. The approach uses variants of the GMOP model to overcome traditional MRP systems’ limitations.

Part 1: Production Process; International audience; This paper addresses the Generic Materials and Operations Planning (GMOP) problem, a multi-site operations planning problem based on the “stroke” concept. The problem considers a multinational company subject to positive and negative backlogs imposed by using returnable racks that have to be filled by end products and transported to customers, alternative operations (purchase, transformation and transport), different BOM structures given the different operation types (injection operations, assembly operations) performed in the various factories of the supply chain, and capacitated production resources. This paper describes and defines the “stroke” construct that mathematically models the relationships between operations and materials. The mathematical modelling approach is provided, as is a brief description of an operations planning tool that has been implemented. Furthermore, some results obtained in a first-tier level supplier of the automotive industry have been introduced.

The aggregate production planning (APP) problem is concerned with determining the optimum production, work force, and inventory levels for each period of the planning horizon. The aggregate production planning problem is a multiple objective one; that involves many functional areas to create. This paper addresses an implementation of a Decision Support System that supports an aggregate production planning problem. The case study covers a real engine assembler serving from their local premises to clients all over the world, with variable demands and calendars. The core of the global tool is a set of MILP model which calculates working calendars for six different sections of a factory, taking into account production rates defined by the company, its internal and external suppliers working calendars and the union requirements. Moreover, the real system had requirements that are not usually considered on APP literature. The model has been designed and calibrated in a prototype-validation iterative process and has been optimized to calculate scenarios with an acceptable computational time within planners' expectative. The system has been developed using free-software and its interfaces have been designed to require the minimum possible interaction from users. The time cost due to the use of non-commercial software has been assessed

JIT delivery practices require that only what is requested is sent. The simplified solution generally accepts that only, what is going to be sent is what is produced, with minimum inventory. Due to the turbulent environment within the plant, the reality is very different. Such simplifications are not viable and buffers between the delivery process and the production process are often allocated. In this paper we present a single model that successfully integrates the delivery, the production, and the supply process. The model that this paper presents includes usual operations plan objectives (production and delivery) but also regularity constraints that keep the system feasible under JIT approach. both objectives on a single model. This model has been successfully implemented in an engine plant of a global automaker which is now planning the operations (supply, transform, assembly and delivery of the plant) with it. Due to the specific characteristics of the tools used at the factory the model was divided into two different models that could be solved sequentially with a large gain in efficiency. The paper ends with some remarks about the implementation process and future research lines…