Adaptación de un plan de estudios de Máster en base a distintos accesos. Aplicación al Master en Ingeniería Industrial

Ponencia presentada en: VIII Jornadas de Innovación Docente de la UBU, Burgos, 5 de abril de 2016, organizadas por el Instituto de Formación e Innovación Educativa-IFIE de la Universidad de Burgo

Influence of noise level and seniority in the workplace on the SAL, ELI and percentage of hearing loss indices in the diagnosis and prevention of hearing loss in the working population

Introduction: This research relates the most important work-related factors affecting the development of hearing loss to the main methods used as medical assessment criteria in the diagnosis of occupational deafness. These criteria are the Speech Average Loss Index (SAL), the Early Loss Index (ELI) and the Percentage of Hearing Loss, and are applied to data obtained from audiograms performed on workers in occupational medical examinations. Method: Depending on the assessment method selected, these often return different results in grading an individual's hearing status and predicting how it will evolve. To address this problem, medical examinations (including audiograms) were carried out on a heterogeneous sample of 1,418 workers in Spain, from which demographic or personal data (gender, age, etc.), occupational data (noise level to which each individual is exposed, etc.) and other non-work-related factors (exposure to noise outside work, family history, etc.) were also gathered. Using Bayesian Networks, the conditional probability of an individual developing hearing loss was obtained taking into account all these factors and, specifically, noise level and length of service in the workplace. Sensitivity analyses were also carried out using the three scales (SAL, ELI and Percentage Hearing Loss Index), proving their suitability as tools the diagnosis and prediction of deafness. These networks were validated under the Receiver Operating Characteristic curve (ROC) criterion and in particular by the Area Under the Curve (AUC). Results: The results show that all three methods are deficient in so far as detecting preventive hearing problems related to noise in most workplaces. Conclusions: The most restrictive methods for detecting possible cases of deafness are the SAL index and the Percentage Loss Index. The ELI index is the least restrictive of the three methods, but it is not able to discriminate the causes of hearing problems in an individual caused by exposure to noise, either by its intensity level or by the time of exposure to noise. Practical Applications: The use of the three methods in the field of occupational risk prevention is extremely limited and it seems reasonable to think that there is a need for the construction of new scales to correct or improve the existing ones

New ways to evaluate learning. Assessing teamwork using TPM and a Poka-Yoke design

Trabajo presentado en: 2nd International Conference on Higher Education Advances, HEAd’16. 2016. ValenciaIn this paper we present a hands-on experiment for measuring learning through teamwork applied to solving a real problem. The experiment is part of the Production Systems course and involves designing a Poka-Yoke, but not theoretically, as is usually the case, rather an actual working mechanism. To this end, a practical problem is proposed for which a physical machine has to be designed to solve the problem. As part of the same exercise, a TPM is developed, also applied to a real case, such as assembling a bicycle. In the case of the Poka-Yoke, two simultaneous objectives are pursued: to avoid a defective product, and to maximize the production per unit time. The final score is assigned based on a measurement of these two parameters. Once the exercise is assigned, the teamwork is verified to be measured efficiently, even when the number of students is high. The physical design of the elements, as well as the simultaneous engagement by all the students in the exercise, served to considerably raise the motivation of the students

Vulnerability of cyclists on the road. A probabilistic analysis of the database of traffic injuries in Spain focusing on type of involved vehicle and driver culpability

Trabajo presentado en: 29th European Safety and Reliability Conference (ESREL), 22–26 September 2019, HannoverThe goal of this research is to explore the role of the collision partner – vehicle type and driver culpability – in incidents involving injuries to people cycling. Previous research has explored a range of factors affecting cyclist injury severity, but were more frequently focused on cyclist behaviour and/or road conditions. The database for our study includes a total of 12,318 drivers or riders of any vehicles involved in traffic injuries with victims in Spain in 2016, of which 7,488 are injured bicycle riders. The database used in our research was provided by Spain's National Traffic Department (Dirección General de Tráfico - DGT). This research uses Bayesian machine learning techniques. These have been recently used to study the severity of traffic injuries, since they provide a sound methodology for analyzing their causes and risks and predicting the probability of traffic injuries with serious injuries or fatalities. We have found proof that involvement of heavy vehicles substantially increases the likelihood of cyclists being killed or seriously injured, and that drivers are more likely than cyclists to be held responsible for the injury

Data on the main working conditions with influence on the development of hearing loss amongst the occupational population in Spain

Obtaining reliable and objective data on certain working conditions is necessary to analyse the causes and variables that can influence the development of hearing loss amongst the working population. Objective occupational data have been collected from a heterogeneous sample of 1418 workers in Spain, see “How activity type, time on the job and noise level on the job affect the hearing of the working population. Using Bayesian networks to predict the development of hipoacusia” (Barrero et al., 2018) [1]. Among the main factors analysed are the noise levels to which these workers are exposed, measured at their respective workstations, and the assessment of their hearing status, evaluated by audiometric medical tests. These factors provide information to predict the development of hypoacusia

Influence of demand, control and social support on job stress. Analysis by employment status from the V European working conditions survey

Work stress increasingly affects many workers from different countries. Conditions such as high demand, low social support and low job control are considered predictors of increased stress. With data obtained from the V European Working Conditions Survey (EWCS) a Bayesian network model was made. It provides information on the levels of stress in relation to model demand-control-social support (DCS), differentiating into work situations as they are, self-employed, private and public. To deepen understanding of the interrelationships between these variables sensitivity analysis of individual and overall were performed to check the DCS model assumptions. This model applied in the V EWCS identified the variations and similarities between different work situations, proving that having low levels of demand, together with control and high social support, the likelihood of stress decreases.El estrés laboral afecta cada vez en mayor cantidad a trabajadores de diversos países. Condiciones como la alta demanda, bajo apoyo social y bajo control sobre el trabajo se consideran predictores del aumento de estrés. Con datos obtenidos de la V Encuesta Europea sobre Condiciones de trabajo (EWCS), se planteó un modelo de red bayesiana que proporciona información sobre los niveles de estrés en relación al modelo demanda-control-apoyo social (DCS), diferenciado en situaciones laborales como son, autónomo, privado y público. Para profundizar en las interrelaciones existentes entre dichas variables se realizaron análisis de sensibilidad individuales y en conjunto para comprobar las hipótesis del modelo DCS. Este modelo aplicado en la V EWCS permitió identificar las variaciones y similitudes entre las diferentes situaciones laborales, comprobando que al tener niveles bajos de demanda, en conjunto con control y apoyo social alto, la probabilidad de sufrir estrés disminuye

Psychosocial and Ergonomic Conditions at Work: Influence on the Probability of a Workplace Accident

Today, the economic and social importance of occupational accidents is undeniable worldwide. Hence, research aimed at reducing this type of accident is considered a discipline of great interest for society in general. In this environment, working conditions play a fundamental role in the occurrence of accidents, and from their study, results can be obtained that provide information for decision-making that guarantee optimum conditions for the development of the employees’ tasks. Organizing the conditions of work execution is also a task that constitutes an essential aspect for a firm’s productivity, therefore, affecting their viability and results. In this work, a model is proposed for the study of different groups of working conditions and their influence on the probability of occupational accidents, in accordance with the data provided by the 7th National Survey of Working Conditions (VII NSWC). -e survey sampled 8892 workers active in all sectors of national production and is the last nation-wide survey administered in Spain. Bayesian networks (BNs) are used to generate a network that analyzes working conditions in all areas (27 variables have been included in addition to those corresponding to the sector and accident), and then, more specifically, the relationship that is established between ergonomic factors in the workplace, psychosocial factors of the worker, and the probability of an accident. -e results are achieved through the network obtained by highlighting some of the proposed variables. -e dependencies generated by the chosen variables are analyzed, and subsequently, the probability of accident for each of the productive sectors is determined. It is concluded that the ergonomic risks associated with physical strains in the workplace, together with the lack of job satisfaction on the employer’s behalf, both pose a very significant increase in the probability of being involved in an occupational accident, above the other variables of study

The Influence of Recognition and Social Support on European Health Professionals’ Occupational Stress: A Demands-Control-Social Support-Recognition Bayesian Network Model

Healthcare professionals undergo high levels of occupational stress as a result of their working conditions. Thus, the aim of this study is to develop a model that focuses on healthcare professionals so as to analyze the influence that job demands, control, social support, and recognition have on the likelihood that a worker will experience stress.The data collected correspond to 2,211 healthcare workers from 35 countries, as reported in the sixth EuropeanWorking Condition Survey (EWCS). The results obtained fromthis study allowus to infer stress under severalworking condition scenarios and to identify themore relevant variables in order to reduce this stress in healthcare professionals, which is of paramount importance to managing the stress of workers in this sector. The Bayesian network proposed indicates that emotional demands have a greater influence on raising the likelihood of stress due to workload than do family demands. The results show that the support of colleagues, in general, has less effect on reducing stress than social support from superiors. Furthermore, the sensitivity analysis shows that, in high-demand and low-control situations, recognition clearly impacts stress, drastically reducing it

Influence of seat-belt use on the severity of injury in traffic accidents

Background: About 1.35 million people died in traffic accidents around the world in 2018, make this type of accidents the 8th cause of death in the world. Particularly, in Spain, there were 204,596 traffic accidents during 2016 and 2017, out of which 349,810 drivers were injured. The objective of this study was to understand to what extent seat belt non-use and human factors contribute to drivers injury severity. Methodology: The results are based on the information and 2016–17 data provided by the Spain national traffic department “Dirección General de Tráfico” (DGT). The discretization model and Bayesian Networks were developed based on important variables from the literature. These variables were classified as; human factor, demographic factor, conditioning factor and seat belt use. Results: The results showed that failure to wear the seat belt by drivers are likely to increase the risk of fatal and sever injury significantly. Moreover, distraction and road type road can contribute to the accident severity.Background: About 1.35 million people died in traffic accidents around the world in 2018, make this type of accidents the 8th cause of death in the world. Particularly, in Spain, there were 204,596 traffic accidents during 2016 and 2017, out of which 349,810 drivers were injured. The objective of this study was to understand to what extent seat belt non-use and human factors contribute to drivers injury severity. Methodology: The results are based on the information and 2016–17 data provided by the Spain national traffic department “Dirección General de Tráfico” (DGT). The discretization model and Bayesian Networks were developed based on important variables from the literature. These variables were classified as; human factor, demographic factor, conditioning factor and seat belt use. Results: The results showed that failure to wear the seat belt by drivers are likely to increase the risk of fatal and sever injury significantly. Moreover, distraction and road type road can contribute to the accident severity

Investigación conjunta de accidentes, incidentes y riesgos.

La investigación de incidentes y riesgos }unto con los accidentes es una herramienta relativamente reciente en la seguridad industrial, pero cuya implantación garantiza la me}ora de los resultados en seguridad. La reciente implantación en numerosas empre