Diseño de un sistema automatizado para mejorar la productividad en la etapa de laminado en la fabricación de la pasta wantan en la empresa Yuc Wa

La empresa YUC WA, se dedica a la producción y comercialización de pasta Wantan, cuyos principales consumidores son los restaurantes orientales “chifas y snacks”, en Chiclayo. Del análisis efectuado se determinó que durante el proceso productivo, en la etapa de laminado se genera una baja productividad de mano de obra (10 kg/hora – hombre); cuyas principales causas se enfocaron en: mano de obra y máquina, causando el cuello de botella. La mano del hombre interviene en un 100%, generando saturación en sus labores. Por otro lado, la máquina laminadora es obsoleta, lo que conlleva a averías constantes, cambios de piezas mensuales y un sinnúmero de mantenimientos. La máquina es utilizada en 43,13%, no en su totalidad, dejando de producir una gran cantidad de pasta Wantan (30378,24 kg/año). Además se calcularon indicadores de productividad de materiales, de máquina y de energía: 1,27 kg de pasta Wantan/kg de harina; 80 kg de pasta Wantan/máquina laminadora y 11 kg de pasta Wantan/kWh respectivamente. Como consecuencia a todas las causas analizadas, se tuvieron pérdidas económicas importantes en todo un año y fueron de S/ 380 184,54 (año 2016). Para dar solución a la problemática de la empresa generada durante el proceso productivo, se logró realizar el diseño de un sistema automatizado de una máquina laminadora. Para su desarrollo se efectuaron diversos cálculos de ingeniería; se utilizó catálogos y se obtuvieron las especificaciones técnicas adecuadas del prototipo diseñado. El diseño mecánico de la máquina laminadora se realizó en SolidWorks, un software asistido por computadora de modelación con sistema CAD, cuya visualización es en 3D. Además, se realizó la programación del controlador lógico programable con su respectiva simulación de control de toda la etapa de laminado en el software So Machine, y los planos eléctricos se presentan en formato CAD para una mejor apreciación de cada símbolo de los dispositivos a utilizar. Con el nuevo sistema diseñado, los indicadores de productividad mejoraron notablemente, la productividad de mano de obra aumentó en 217,39 kg/hora – hombre, la productividad de energía a 17,15 kg de pasta Wantan/kWh y la productividad de máquina a 200 kg/máquina. Por otro lado la utilización de la máquina y el rendimiento de la producción aumentaron en un 100%, los niveles de saturación del operario disminuyeron de 100% a 0,00%, teniendo un incremento en la productividad de mano de obra en un 2074 %; de esta manera se reducen y/o eliminan los problemas originados durante el proceso productivo (cuello de botella); por lo tanto, se considera que el proyecto es viable y rentable para la empresa, puesto que tendrá una inversión total de S/ 64 254,09; con un período de recuperación de 90 días calendarios y por cada sol invertido, se recuperan 17,92 soles, lo que conllevaría a una rentabilidad a gran escala

Measuring social influence and group formation during evacuation process

Evacuees are likely to respond and move forming groups. However specific data about grouping is generally unavailable and the relationship between response and movement times and specific groupings are unknown. Using a simple method, we measure behavioural cohesion of occupants during evacuation processes. The case study involves using the method in a bus station, a sport centre and a library. Results suggest that proximity (visual/verbal contact) is an important factor but not decisive in the formation of evacuation groups. Social ties and whether occupants share a target and/or an activity before the alarm are also deemed to be important factors. This provides an exciting opportunity to advance our knowledge of social influence and group formation during evacuation.The authors would like to thank the European Union for the LETS-CROWD project received funding from the Horizon 2020 Research and Innovation Programme under the grant agreement Nº 740466 and the Spanish Ministry of Economy and Competitiveness for DEFENDER Project Grant, Ref: BIA2015-64866-R, co-funded by ERDS funds

Gender and public perception of disasters: a multiple hazards exploratory study of EU citizens

To explore gender influence on individual risk perception of multiple hazards and personal attitudes towards disaster preparedness across EU citizens. Method: An online survey was distributed to 2485 participants from Spain, France, Poland, Sweden and Italy. The survey was divided into two parts. The first part examined perceived likelihood (L), perceived personal impact (I) and perceived self-efficacy (E) towards disasters due to extreme weather conditions (flood, landslide and storm), fire, earthquake, hazardous materials accidents, and terrorist attacks. The overall risk rating for each specific hazard was measured through the following equation R = (L × I)/E and the resulting scores were brought into the range between 0 and 1. The second part explored people’s reactions to the Pros and Cons of preparedness to compute the overall attitudes of respondents towards preparation (expressed as a ratio between −1 and 1). Results: Although we found gender variations on concerns expressed as the likelihood of the occurrence, personal consequences and self-efficacy, the overall risks were judged significantly higher by females in all hazards (p < 0.01). We also found that, in general, most respondents (both males and females) were in favour of preparedness. More importantly, despite the gender differences in risk perception, there were no significant differences in the attitudes towards preparedness. We found weak correlations between risks perceived and attitudes towards preparedness (rho < 0.20). The intersectional analysis showed that young and adult females perceived higher risks than their gender counterparts at the same age. There were also gender differences in preparedness, i.e., females in higher age ranges are more motivated for preparedness than men in lower age ranges. We also found that risk perception for all hazards in females was significantly higher than in males at the same education level. We found no significant differences between sub-groups in the pros and cons of getting ready for disasters. However, females at a higher level of education have more positive attitudes towards preparedness. Conclusions: This study suggests that gender along with other intersecting factors (e.g., age and education) still shape differences in risk perception and attitudes towards disasters across the EU population. Overall, the presented results policy actions focus on promoting specific DRR policies and practices (bottom-up participatory and learning processes) through interventions oriented to specific target groups from a gender perspective.This project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 832576

Interdependence of flows when merge in rail tunnel evacuations

The understanding of merging flows during evacuation can have important implications for rail tunnels safety. This paper explores the interdependence of the merging of flows coming from the walkway with those exiting the train. Eight train exit configurations were tested using a mock-up of a rail car exit and a lateral walkway involving 77 participants (mean age 48; standard deviation 15; range 18-74). New measurements and data processing methods are proposed allowing statistical analysis to be performed. The results provide quantitative evidence of the preferences between flows. We found that the bias in the evacuation was slightly in favour of the walkway when train exit was at 0 m in height. Contrary to expectations a moderate dominance of walkway flow was observed at 0.8 m in height. Less variation was found for the train exit at 1.2 m in height with a clear priority of walkway flow. This happened despite deference behaviours performed by participants, i.e. people stopped to help those entering from the rail car. This novel contribution aims to provide a new method for those involved in development and validation of new and current evacuation modelling tools and those who want to improve their understanding of merging behaviour during evacuation in rail tunnels.The authors would like to thank the Ministry of Economy, Industry and Competitiveness (MINECO) for funding the SIGNAL project on the frame of the Subprogram RETOS-COLABORACIÓN 2016 call (Ref -RTC-2016-5474-4) as well as the European Union through ERDF funding under the objective of Strengthening Research, Technological Development and Innovatio

Evacuation management system for major disasters

Predicting and understanding mass evacuations are important factors in disaster management and response. Current modelling approaches are useful for planning but lack of real-time capabilities to help informed decisions as the disaster event evolves. To address this challenge, a real-time Evacuation Management System (EMS) is proposed here, following a stochastic approach and combining classical models of low complexity but high reliability. The EMS computes optimal assembly points and shelters and the related network of evacuation routes using GIS-based traffic, pedestrian and routing models including damaged assets or impassable areas. To test the proper operation performances of the EMS, we conducted a case study for the Gran Canaria wildfireThis research and APC was funded by the European Union’s H2020 research and innovation programme under grant agreement No. 832576 (ASSISTANCE project)

Innovations for smoke management in passenger trains

Spanish manufacturer Construcciones y Auxiliar de Ferrocarriles developed an innovative alternative for compartmentation, based on a smoke extraction system, to guarantee safe conditions during evacuation processes in a passenger unit. To demonstrate its performance in a train unit, a real-scale experimental programme, supported by the application of fire computer modelling, was applied in a new Construcciones y Auxiliar de Ferrocarriles' rolling stock. The new smoke exhaust system aims to extract the smoke generated during a fire in the passenger area by exhaust fans of the heating, ventilation, and air conditioning system, allowing the ingress of fresh exterior air in the lower part of the rear ends of the car. These key elements create an air flow that evacuates the smoke to prevent people from being exposed to it. Full-scale fire tests were developed in the train unit following the Australian standard AS 4391-1999. A fire of 140kW was used, and the smoke was generated by a clean smoke machine. Measurement points included six thermocouple trees, 10 gas flow velocity probes and two GoPro HD video cameras (for the estimation of the visibility). The system performance was successful with the tenability criteria, since the value of visibility at the non-fire car was greater than 30 m and the temperature was lower than 30°C during all the tests at a height of 1.7m above the floor. Experimental results were used to validate the computational model. The computational model results show a good accuracy compared with the tests

Bearing assessment tool for longitudinal bridge performance

This work provides an unsupervised learning approach based on a single-valued performance indicator to monitor the global behavior of critical components in a viaduct, such as bearings. We propose an outlier detection method for longitudinal displacements to assess the behavior of a singular asymmetric prestressed concrete structure with a 120 m high central pier acting as a fixed point. We first show that the available long-term horizontal displacement measurements recorded during the undamaged state exhibit strong correlations at the different locations of the bearings. Thus, we combine measurements from four sensors to design a robust performance indicator that is only weakly affected by temperature variations after the application of principal component analysis. We validate the method and show its efficiency against false positives and negatives using several metrics: accuracy, precision, recall, and F1 score. Due to its unsupervised learning scope, the proposed technique is intended to serve as a real-time supervision tool that complements maintenance inspections. It aims to provide support for the prioritization and postponement of maintenance actions in bridge management.Authors would like to acknowledge the discussions with Marcos Pantaleón from APIA XXI, Ambher Monitoring Systems and Banobras S.N.C. This work has received funding from the European’s Union Horizon 2020 research and innovation program under the grant agreement No 690660 (RAGTIME Project) and No 769373 (FORESEE Project). This paper refects only the author’s views. The European Commission and INEA are not responsible for any use that may be made of the information contained therein. David Pardo has received funding from the European Union’s Horizon 2020 research and innovation program under the Marie Sklodowska-Curie grant agreement No 777778 (MATHROCKS), the European POCTEFA 2014-2020 Project PIXIL (EFA362/19) by the European Regional Development Fund (ERDF) through the Interreg V-A Spain-France-Andorra program, the Project of the Spanish Ministry of Science and Innovation with reference PID2019-108111RBI00 (FEDER/AEI), the BCAM “Severo Ochoa” accreditation of excellence (SEV-2017-0718), and the Basque Government through the BERC 2018-2021 program, the two Elkartek projects 3KIA (KK2020/00049) and MATHEO (KK-2019-00085), the grant "Artifcial Intelligence in BCAM number EXP. 2019/00432", and the Consolidated Research Group MATHMODE (IT1294-19) given by the Department of Education

A simple direct method to obtain kinetic parameters for polymer thermal decomposition

In a fire, the polymer combustion occurs when gaseous fuels react with oxygen. The heating of a material could force the release of gaseous fuels during thermal decomposition and pyrolysis. The rate of pyrolysis to define the gaseous fuels is usually interpreted by means of the Arrhenius expression and a reaction model expression, which are characterized by an activation energy, a pre-exponential factor, and a reaction order value. Many methods are available for determining kinetic parameters from thermogravimetric experimental data. However, the most challenging issue is achieving an adequate balance between accuracy and simplicity. This work proposes a direct method for determining the kinetic parameters with only a thermogravimetric experiment at a single heating rate. The method was validated with six polymers, and the results were compared with those from similar procedures, such as the Lyon method and generalized direct method. The results achieved using the simpler approach of the proposed method show a high level of accuracy.Authors would like to thank to the Consejo de Seguridad Nuclear for the cooperation and co-financing the project “Metodologías avanzadas de análisis y simulación de escenarios de incendios en centrales nucleares” and to CAFESTO Project funded by the Spanish Ministry of Science, Innovation and Universities and the Spanish State Research Agency through public–private partnerships (Retos Colaboración 2017 call, ref RTC-2017-6066-8) co-funded by ERDF under the objective “Strengthening research, technological development and innovation

An evacuation model for risk analysis in Spanish road tunnels

In this paper we present EvacTunnel 3.0 an evacuation model design specifically for road tunnels. The model combines coarse network (space discretization) and a microscopic approach for modeling individual behaviors. Based on Monte Carlo methods, the model has the capability to perform multiple simulations by changing random variables of tunnel users such as pre-movement times and walking speeds. The proposed model allows the user to incorporate the effects of fire into the evacuation simulation (importing fire data/results from another model) and, therefore, predicts the number of people directly affected by the smoke (victims). Three verification cases of the proposed model are shown in this paper: 1) risk analysis application, 2) comparison with other evacuation models and 3) a real case application

Intelligent emergency management system for railway transport

Nowadays, a major safety challenge in rail transport is to manage the incidents and emergencies in the most efficient possible way. The current contingency plans tend to be based on static procedures not taking into account how real-time conditions affect them. Consequently, the decision-making process may well suffer delays and the possibility of occurrence for human mistakes could raise since the required measures are expected to be carried out under important pressure. In this study, focused on commuter trains, railway safety is enhanced by a new intelligent emergency management system which aims to support the operator tasks in a realtime incident or emergency situation. This cyber-physical system is composed by two main modules: one on board the train, including sensors and GPS, and other integrated in the control centre addressing four computational models. Those models cover (1) the detection of different types of incidents/emergencies using the information received from on board sensors, (2) the calculation of the evacuation process (if necessary), (3) the selection, estimation of routes and communication with emergency services required for each event, and finally (4) a provision of actions to support the operator decisions. Communication between modules is provided by GPRS due to actual technology available in the pilot trains. This system has been implemented in an actual railway line in Cantabria (Santander-Cabezón de la Sal) and three practical demonstrations were defined based on several use cases, which were tested using a pilot facility incorporating all sensors and devices installed in those trains. Results demonstrated the benefits of the new system.The authors would like to thank the Ministry of Economy, Industry and Competitiveness (MINECO) for funding the SIGNAL project on the frame of the Subprogram RETOS-COLABORACIÓN 2016 call (Ref-RTC-2016-5474- 4), as well as the European Union through ERDF funding under the objective of Strengthening Research, Technological Development and Innovation and also to SETELSA company for their partnership, dedication and support for the developing of the project