Browsing by Keyword "Management Science and Operations Research"
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Item Activating inclusive growth in railway SMEs by workplace innovation(2020-09) Carranza, Garazi; Garcia, Marta; Sanchez, Begoña; Policies for Innovation and TechnologyThe digital revolution is happening, transforming the way we move and produce. Success in the digital revolution means that the rail industries need to use the best available technologies focusing on people. The managerial and organizational practices adopted by railway entities have considerable significance for Railway's ability to succeed in global competition. One of the challenges for railway entities is to deliver innovative products, offering quickness and flexibility to respond to changing demands from their customers. Non-technological innovations and especially Workplace innovation, have a key role to play in the digitalization and acceleration of technological developments, therefore in the railway sector competitiveness. This draws attention to the importance of innovation climate and employees' commitment aiming at improving staff motivation and working conditions, thereby enhancing labor productivity, organizational performance, innovation capability, reactivity to market change, and consequently business competitiveness. As with any emerging opportunity, there is no established path to follow to activate inclusive growth in railway SMEs to uptake Workplace innovation. To address these issues, this paper develops and tests a research model that covers individual behavior, organizational practices, and process practices of innovation among employees, analyzing the impact of Workplace Innovation on firm performance.Item Hot stamping of aerospace aluminium alloys: Automotive technologies for the aeronautics industry(2022-09) Atxaga, G.; Arroyo, A.; Canflanca, B.; EXTREMAT; PROMETAL; SGThis paper proposes the use of the hot stamping process that provides ready to use parts for the obtention of aircraft components as an alternative manufacturing technology to e.g. machined parts. The development has been focused on the study of the high temperature formability of aluminium alloys. The feasibility of hot forming the AA2198 aluminium‑lithium alloy into complex shapes component has been studied. A wide experimental campaign has been carried out to set up the optimum hot stamping process parameters. In addition, forming trials with different geometries (omega and B-pillar shapes) have also been performed and, after the corresponding heat treatment, material properties have been recovered. Simulations of the hot stamping process have been carried out with Pamstamp® 2G software. These results have been correlated with the ones obtained in the experimental campaign. As a final step of the development, a demonstrator corresponding to a wing rib has been successfully manufactured. Characterization carried out to the prototype indicate specifications are fulfilled.Item On the imputation of missing data for road traffic forecasting: New insights and novel techniques: New insights and novel techniques(2018-05) Laña, Ibai; Olabarrieta, Ignacio (Iñaki); Vélez, Manuel; Del Ser, Javier; IAVehicle flow forecasting is of crucial importance for the management of road traffic in complex urban networks, as well as a useful input for route planning algorithms. In general traffic predictive models rely on data gathered by different types of sensors placed on roads, which occasionally produce faulty readings due to several causes, such as malfunctioning hardware or transmission errors. Filling in those gaps is relevant for constructing accurate forecasting models, a task which is engaged by diverse strategies, from a simple null value imputation to complex spatio-temporal context imputation models. This work elaborates on two machine learning approaches to update missing data with no gap length restrictions: a spatial context sensing model based on the information provided by surrounding sensors, and an automated clustering analysis tool that seeks optimal pattern clusters in order to impute values. Their performance is assessed and compared to other common techniques and different missing data generation models over real data captured from the city of Madrid (Spain). The newly presented methods are found to be fairly superior when portions of missing data are large or very abundant, as occurs in most practical cases.Item Prediction and validation of shape distortions in the simulation of high pressure die casting(2018-06) Anglada, Eva; Meléndez, Antton; Vicario, Iban; Idoiaga, Jon Kepa; Mugarza, Aitz; Arratibel, Ernesto; CIRMETAL; Tecnalia Research & Innovation; PROMETALThe use of the thermomechanical simulation is very infrequent in the metal casting industry although the associated results are really useful for the manufacturing process. The main reasons are the complexity, the long calculation times and the difficulties to interpret the results. The parts manufactured by metal casting processes cool from its filling temperature to ambient, which causes a certain stress-strain state. Although the stress levels might be significant, the main worry of the foundrymen is usually the shape distortion. That is, the mismatches between the desired dimensions and the real ones. The problem is that the results obtained from numerical simulation are not directly useful to cover this industrial necessity. This work presents the prediction obtained using the thermomechanical simulation for the final dimensions of a component manufactured in aluminium alloy by high pressure die casting (HPDC) and its validation with the final dimensions of the manufactured component. The methodology established to forecast the mismatches with the reference geometry is also detailed, as it may be useful to encourage the use of this type of simulation in the metal casting industry.Item Privacy-enhancing distributed protocol for data aggregation based on blockchain and homomorphic encryption(2021-11) Regueiro, Cristina; Seco, Iñaki; de Diego, Santiago; Lage, Oscar; Etxebarria, Leire; CIBERSEC&DLT; Tecnalia Research & InnovationThe recent increase in reported incidents of security breaches compromising users' privacy call into question the current centralized model in which third-parties collect and control massive amounts of personal data. Blockchain has demonstrated that trusted and auditable computing is possible using a decentralized network of peers accompanied by a public ledger. Furthermore, Homomorphic Encryption (HE) guarantees confidentiality not only on the computation but also on the transmission, and storage processes. The synergy between Blockchain and HE is rapidly increasing in the computing environment. This research proposes a privacy-enhancing distributed and secure protocol for data aggregation backboned by Blockchain and HE technologies. Blockchain acts as a distributed ledger which facilitates efficient data aggregation through a Smart Contract. On the top, HE will be used for data encryption allowing private aggregation operations. The theoretical description, potential applications, a suggested implementation and a performance analysis are presented to validate the proposed solution.Item A random-key encoded harmony search approach for energy-efficient production scheduling with shared resources(2015-11-02) Garcia-Santiago, C.A.; Del Ser, Javier; Upton, C.; Quilligan, F.; Gil-Lopez, S.; Salcedo-Sanz, Sancho; IAWhen seeking near-optimal solutions for complex scheduling problems, meta-heuristics demonstrate good performance with affordable computational effort. This has resulted in a gravitation towards these approaches when researching industrial use-cases such as energy-efficient production planning. However, much of the previous research makes assumptions about softer constraints that affect planning strategies and about how human planners interact with the algorithm in a live production environment. This article describes a job-shop problem that focuses on minimizing energy consumption across a production facility of shared resources. The application scenario is based on real facilities made available by the Irish Center for Manufacturing Research. The formulated problem is tackled via harmony search heuristics with random keys encoding. Simulation results are compared to a genetic algorithm, a simulated annealing approach and a first-come-first-served scheduling. The superior performance obtained by the proposed scheduler paves the way towards its practical implementation over industrial production chains.