Designing Cyclic Job Rotations to Reduce the Exposure to Ergonomics Risk Factors

[EN] Job rotation is an administrative solution to prevent work-related musculoskeletal disorders that has become widespread. However, job rotation schedules development is a complex problem. This is due to the multi-factorial character of the disorders and to the productive and organizational constraints of the real working environments. To avoid these problems, this work presents an evolutionary algorithm to generate rotation schedules in which a set of workers rotate cyclically over a small number of jobs while reducing the potential for injury. The algorithm is able to generate rotation schedules that optimize multiple ergonomics criteria by clustering the tasks into rotation groups, selecting the workers for each group, and determining the sequence of rotation of the workers to minimize the effects of fatigue. The algorithm reduces prolonged exposure to risks related to musculoskeletal injuries and simplifies the assignment of workers to different tasks in each rotation. The presented procedure can be an effective tool for the design of job-rotation schedules that prevent work-related musculoskeletal disorders while simplifying scheduled changeovers at each rotation and facilitating job monitoring.Diego-Mas, JA. (2020). Designing Cyclic Job Rotations to Reduce the Exposure to Ergonomics Risk Factors. International Journal of Environmental research and Public Health. 17(3):1-17. https://doi.org/10.3390/ijerph17031073S117173Ouellet, S., & Vézina, N. (2003). L’implantation de la rotation de postes : un exemple de démarche préalable. Perspectives interdisciplinaires sur le travail et la santé, (5-2). doi:10.4000/pistes.3322Bhadury, J., & Radovilsky, Z. (2006). Job rotation using the multi-period assignment model. International Journal of Production Research, 44(20), 4431-4444. doi:10.1080/00207540500057621Jeon, I. S., Jeong, B. Y., & Jeong, J. H. (2016). Preferred 11 different job rotation types in automotive company and their effects on productivity, quality and musculoskeletal disorders: comparison between subjective and actual scores by workers’ age. Ergonomics, 59(10), 1318-1326. doi:10.1080/00140139.2016.1140816Van Wyk, A. E., Swarts, I., & Mukonza, C. (2018). The Influence of the Implementation of Job Rotation on Employees’ Perceived Job Satisfaction. International Journal of Business and Management, 13(11), 89. doi:10.5539/ijbm.v13n11p89Rissén, D., Melin, B., Sandsjö, L., Dohns, I., & Lundberg, U. (2002). Psychophysiological stress reactions, trapezius muscle activity, and neck and shoulder pain among female cashiers before and after introduction of job rotation. Work & Stress, 16(2), 127-137. doi:10.1080/02678370210141530Allwood, J. M., & Lee, W. L. (2004). The impact of job rotation on problem solving skills. International Journal of Production Research, 42(5), 865-881. doi:10.1080/00207540310001631566McDonald, T., Ellis, K. P., Van Aken, E. M., & Patrick Koelling, C. (2009). Development and application of a worker assignment model to evaluate a lean manufacturing cell. International Journal of Production Research, 47(9), 2427-2447. doi:10.1080/00207540701570174Costa, A. M., & Miralles, C. (2009). Job rotation in assembly lines employing disabled workers. International Journal of Production Economics, 120(2), 625-632. doi:10.1016/j.ijpe.2009.04.013Schneider, S., Grant, K. A., Habes, D. J., & Bertsche, P. K. (1997). Ergonomics: Lifting Hazards at a Cabinet Manufacturing Company: Evaluation and Recommended Controls. Applied Occupational and Environmental Hygiene, 12(4), 253-258. doi:10.1080/1047322x.1997.10389500Comper, M. L. C., & Padula, R. S. (2014). The effectiveness of job rotation to prevent work-related musculoskeletal disorders: protocol of a cluster randomized clinical trial. BMC Musculoskeletal Disorders, 15(1). doi:10.1186/1471-2474-15-170KUIJER, P. P. F. M., VISSER, B., & KEMPER, H. C. G. (1999). Job rotation as a factor in reducing physical workload at a refuse collecting department. Ergonomics, 42(9), 1167-1178. doi:10.1080/001401399185054Hinnen, U., Laubli, T., Guggenbuhl, U., & Krueger, H. (1992). Design of check-out systems including laser scanners for sitting work posture. Scandinavian Journal of Work, Environment & Health, 18(3), 186-194. doi:10.5271/sjweh.1589Kuijer, P. P. F. M., van der Beek, A. J., van Dieën, J. H., Visser, B., & Frings-Dresen, M. H. W. (2005). Effect of job rotation on need for recovery, musculoskeletal complaints, and sick leave due to musculoskeletal complaints: A prospective study among refuse collectors. American Journal of Industrial Medicine, 47(5), 394-402. doi:10.1002/ajim.20159Frazer, M., Norman, R., Wells, R., & Neumann, P. (2003). The effects of job rotation on the risk of reporting low back pain. Ergonomics, 46(9), 904-919. doi:10.1080/001401303000090161Asensio-Cuesta, S., Diego-Mas, J. A., Cremades-Oliver, L. V., & González-Cruz, M. C. (2012). A method to design job rotation schedules to prevent work-related musculoskeletal disorders in repetitive work. International Journal of Production Research, 50(24), 7467-7478. doi:10.1080/00207543.2011.653452Vinel, A., Mehdizadeh, A., Schall, M. C., Gallagher, S., & Sesek, R. F. (2018). An Optimization Framework for Job Rotation to Better Assess the Impact on Overall Risk. Proceedings of the Human Factors and Ergonomics Society Annual Meeting, 62(1), 843-847. doi:10.1177/1541931218621192Kher, H. V., Malhotra, M. K., Philipoom, P. R., & Fry, T. D. (1999). Modeling simultaneous worker learning and forgetting in dual resource constrained systems. European Journal of Operational Research, 115(1), 158-172. doi:10.1016/s0377-2217(98)00190-8Eriksson, T., & Ortega, J. (2006). The Adoption of Job Rotation: Testing the Theories. ILR Review, 59(4), 653-666. doi:10.1177/001979390605900407Jeon, I. S., & Jeong, B. Y. (2016). Effect of Job Rotation Types on Productivity, Accident Rate, and Satisfaction in the Automotive Assembly Line Workers. Human Factors and Ergonomics in Manufacturing & Service Industries, 26(4), 455-462. doi:10.1002/hfm.20667Song, J., Lee, C., Lee, W., Bahn, S., Jung, C., & Yun, M. H. (2016). Development of a job rotation scheduling algorithm for minimizing accumulated work load per body parts. Work, 53(3), 511-521. doi:10.3233/wor-152232Yoon, S.-Y., Ko, J., & Jung, M.-C. (2016). A model for developing job rotation schedules that eliminate sequential high workloads and minimize between-worker variability in cumulative daily workloads: Application to automotive assembly lines. Applied Ergonomics, 55, 8-15. doi:10.1016/j.apergo.2016.01.011Padula, R. S., Comper, M. L. C., Sparer, E. H., & Dennerlein, J. T. (2017). Job rotation designed to prevent musculoskeletal disorders and control risk in manufacturing industries: A systematic review. Applied Ergonomics, 58, 386-397. doi:10.1016/j.apergo.2016.07.018Azizi, N., Zolfaghari, S., & Liang, M. (2010). Modeling job rotation in manufacturing systems: The study of employee’s boredom and skill variations. International Journal of Production Economics, 123(1), 69-85. doi:10.1016/j.ijpe.2009.07.010Carnahan, B. J., Redfern, M. S., & Norman, B. (2000). Designing safe job rotation schedules using optimization and heuristic search. Ergonomics, 43(4), 543-560. doi:10.1080/001401300184404Tharmmaphornphilas, W., & Norman, B. A. (2007). A methodology to create robust job rotation schedules. Annals of Operations Research, 155(1), 339-360. doi:10.1007/s10479-007-0219-8Seçkiner, S. U., & Kurt, M. (2007). A simulated annealing approach to the solution of job rotation scheduling problems. Applied Mathematics and Computation, 188(1), 31-45. doi:10.1016/j.amc.2006.09.082Seçkiner, S. U., & Kurt, M. (2008). Ant colony optimization for the job rotation scheduling problem. Applied Mathematics and Computation, 201(1-2), 149-160. doi:10.1016/j.amc.2007.12.006Yaoyuenyong, S., & Nanthavanij, S. (2006). Hybrid procedure to determine optimal workforce without noise hazard exposure. Computers & Industrial Engineering, 51(4), 743-764. doi:10.1016/j.cie.2006.08.018Diego-Mas, J. A., Asensio-Cuesta, S., Sanchez-Romero, M. A., & Artacho-Ramirez, M. A. (2009). A multi-criteria genetic algorithm for the generation of job rotation schedules. International Journal of Industrial Ergonomics, 39(1), 23-33. doi:10.1016/j.ergon.2008.07.009Asensio-Cuesta, S., Diego-Mas, J. A., Canós-Darós, L., & Andrés-Romano, C. (2011). A genetic algorithm for the design of job rotation schedules considering ergonomic and competence criteria. The International Journal of Advanced Manufacturing Technology, 60(9-12), 1161-1174. doi:10.1007/s00170-011-3672-0Sana, S. S., Ospina-Mateus, H., Arrieta, F. G., & Chedid, J. A. (2018). Application of genetic algorithm to job scheduling under ergonomic constraints in manufacturing industry. Journal of Ambient Intelligence and Humanized Computing, 10(5), 2063-2090. doi:10.1007/s12652-018-0814-3Digiesi, S. D., Facchini, F., Mossa, G., … Mummolo, G. (2018). Minimizing and Balancing Ergonomic Risk of Workers of an Assembly Line by Job Rotation: a MINLP Model. International Journal of Industrial Engineering and Management, 9(3), 129-138. doi:10.24867/ijiem-2018-3-129Crawford, J. O. (2007). The Nordic Musculoskeletal Questionnaire. Occupational Medicine, 57(4), 300-301. doi:10.1093/occmed/kqm03

Single users' affective responses models for product form design

This paper presents a neural network based approach to modeling consumers' affective responses for product form design. A theoretical framework for a single user's perception is developed. On the basis of this theoretical framework, a mathematical model which enables single users' responses to different products to be predicted was developed. The results obtained show that the mathematical models developed achieved highly accurate predictions. For the purpose of obtaining a global model various individual mathematical models were created, which were based on the opinions of users representing different groups of opinion. The results suggest that, under some conditions, the combined use of various models of individual users can perform as well as a single model generated on the basis of mean market responses.Diego-Mas, JA.; Alcaide Marzal, J. (2016). Single users' affective responses models for product form design. International Journal of Industrial Ergonomics. 53:102-114. doi:10.1016/j.ergon.2015.11.005S1021145

Measuring the Project Management Complexity: The Case of Information Technology Projects

[EN] Complex projects require specific project management (PM) competences development. However, while no complex projects have standards that are recognized to guide their management, complex projects do not have guides to deal with their complexity. To lead complex projects to success, this complexity must be measured quantitatively and, in our opinion, project management complexity assessment should be based on existing PM standards. In this work, the main project complexity assessment approaches based on PM standards are analyzed, observing that International Project Management Association (IPMA) approach is the closest to a tool that can be used as a complexity quantitative measurement system. On the other hand, several authors have shown that the inherent complexity of specific kind of projects must be measured in a particular way. The main objective of this research is to propose a project management complexity assessment tool for IT projects, providing a Complexity Index that measures the impact that complexity factors inherent to IT projects have under a specific complexity scenario. The tool combines the use of complexity factors defined by IPMA approach and the use of complexity factors found in the literature to manage inherent complexity of IT projects. All these factors were validated by expert survey and the tool was applied to a study case.Poveda Bautista, R.; Diego-Mas, JA.; Leon Medina, DA. (2018). Measuring the Project Management Complexity: The Case of Information Technology Projects. Complexity. 2018:1-19. https://doi.org/10.1155/2018/6058480S119201

Errors Using Observational Methods for Ergonomics Assessment in Real Practice

[EN] Objective: The degree in which practitioners use the observational methods for musculoskeletal disorder risks assessment correctly was evaluated. Background: Ergonomics assessment is a key issue for the prevention and reduction of work-related musculoskeletal disorders in workplaces. Observational assessment methods appear to be better matched to the needs of practitioners than direct measurement methods, and for this reason, they are the most widely used techniques in real work situations. Despite the simplicity of observational methods, those responsible for assessing risks using these techniques should have some experience and know-how in order to be able to use them correctly. Method: We analyzed 442 risk assessments of actual jobs carried out by 290 professionals from 20 countries to determine their reliability. Results: The results show that approximately 30% of the assessments performed by practitioners had errors. In 13% of the assessments, the errors were severe and completely invalidated the results of the evaluation. Conclusion: Despite the simplicity of observational method, approximately 1 out of 3 assessments conducted by practitioners in actual work situations do not adequately evaluate the level of potential musculoskeletal disorder risks. Application: This study reveals a problem that suggests greater effort is needed to ensure that practitioners possess better knowledge of the techniques used to assess work-related musculoskeletal disorder risks and that laws and regulations should be stricter as regards qualifications and skills required by professionals.This work was supported by the Programa estatal de investigacion, desarrollo e innovacion orientada a los retos de la sociedad of the government of Spain under Grant DPI2016-79042-R.Diego-Mas, JA.; Alcaide Marzal, J.; Poveda Bautista, R. (2017). Errors Using Observational Methods for Ergonomics Assessment in Real Practice. Human Factors The Journal of the Human Factors and Ergonomics Society. 59(8):1173-1187. https://doi.org/10.1177/00187208177234961173118759

Effects of Using Immersive Media on the Effectiveness of Training to Prevent Ergonomics Risks

[EN] In this work, the effects of using immersive media such as virtual reality on the performance of training programs to avoid ergonomics risks are analyzed. The advance of technology has made it possible to use low-cost portable devices able to generate highly immersive experiences in training programs. The effects of using this kind of device in training programs have been studied in several fields such as industrial security, medicine and surgery, rehabilitation, or construction. However, there is very little research on the effects of using immersive media in training workers to avoid ergonomics risk factors. In this study, we compare the effects of using traditional and immersive media in a training program to avoid three common ergonomics risk factors in industrial environments. Our results showed that using immersive media increases the participant's engagement during the training. In the same way, the learning contents are perceived as more interesting and useful and are better remembered over time, leading to an increased perception of the ergonomics risks among workers. However, we found that little training was finally transferred to the workplace three months after the training session.This research was funded by Spanish Ministry of Economy, Industry and Competitiveness, grant number DPI2016-79042-R.Diego-Mas, JA.; Alcaide-Marzal, J.; Poveda Bautista, R. (2020). Effects of Using Immersive Media on the Effectiveness of Training to Prevent Ergonomics Risks. International Journal of Environmental research and Public Health (Online). 17(7):1-18. https://doi.org/10.3390/ijerph17072592S118177Perruccio, A. V., Yip, C., Badley, E. M., & Power, J. D. (2017). Musculoskeletal Disorders: A Neglected Group at Public Health and Epidemiology Meetings? American Journal of Public Health, 107(10), 1584-1585. doi:10.2105/ajph.2017.303990Merkesdal, S., Ruof, J., Huelsemann, J. L., Mittendorf, T., Handelmann, S., Mau, W., & Zeidler, H. (2005). Indirect cost assessment in patients with rheumatoid arthritis (RA): Comparison of data from the health economic patient questionnaire HEQ-RA and insurance claims data. Arthritis & Rheumatism, 53(2), 234-240. doi:10.1002/art.21080Gignac, M. A. M., Cao, X., Lacaille, D., Anis, A. H., & Badley, E. M. (2008). Arthritis-related work transitions: A prospective analysis of reported productivity losses, work changes, and leaving the labor force. Arthritis & Rheumatism, 59(12), 1805-1813. doi:10.1002/art.24085Daniels, K., Gedikli, C., Watson, D., Semkina, A., & Vaughn, O. (2017). Job design, employment practices and well-being: a systematic review of intervention studies. Ergonomics, 60(9), 1177-1196. doi:10.1080/00140139.2017.1303085Burgess-Limerick, R. (2018). Participatory ergonomics: Evidence and implementation lessons. Applied Ergonomics, 68, 289-293. doi:10.1016/j.apergo.2017.12.009King, P. M., Fisher, J. C., & Garg, A. (1997). Evaluation of the impact of employee ergonomics training in industry. Applied Ergonomics, 28(4), 249-256. doi:10.1016/s0003-6870(96)00067-1Burke, M. J., Sarpy, S. A., Smith-Crowe, K., Chan-Serafin, S., Salvador, R. O., & Islam, G. (2006). Relative Effectiveness of Worker Safety and Health Training Methods. American Journal of Public Health, 96(2), 315-324. doi:10.2105/ajph.2004.059840Ricci, F., Chiesi, A., Bisio, C., Panari, C., & Pelosi, A. (2016). Effectiveness of occupational health and safety training. Journal of Workplace Learning, 28(6), 355-377. doi:10.1108/jwl-11-2015-0087Brisson, C., Montreuil, S., & Punnett, L. (1999). Effects of an ergonomic training program on workers with video display units. Scandinavian Journal of Work, Environment & Health, 25(3), 255-263. doi:10.5271/sjweh.432Hogan, D. A. M., Greiner, B. A., & O’Sullivan, L. (2014). The effect of manual handling training on achieving training transfer, employee’s behaviour change and subsequent reduction of work-related musculoskeletal disorders: a systematic review. Ergonomics, 57(1), 93-107. doi:10.1080/00140139.2013.862307Yu, W., Yu, I. T. S., Wang, X., Li, Z., Wan, S., Qiu, H., … Sun, T. (2012). Effectiveness of participatory training for prevention of musculoskeletal disorders: a randomized controlled trial. International Archives of Occupational and Environmental Health, 86(4), 431-440. doi:10.1007/s00420-012-0775-3Hoe, V. C., Urquhart, D. M., Kelsall, H. L., Zamri, E. N., & Sim, M. R. (2018). Ergonomic interventions for preventing work-related musculoskeletal disorders of the upper limb and neck among office workers. Cochrane Database of Systematic Reviews, 2018(10). doi:10.1002/14651858.cd008570.pub3Hoe, V. C., Urquhart, D. M., Kelsall, H. L., & Sim, M. R. (2012). Ergonomic design and training for preventing work-related musculoskeletal disorders of the upper limb and neck in adults. Cochrane Database of Systematic Reviews. doi:10.1002/14651858.cd008570.pub2Van Eerd, D., Munhall, C., Irvin, E., Rempel, D., Brewer, S., van der Beek, A. J., … Amick, B. (2015). Effectiveness of workplace interventions in the prevention of upper extremity musculoskeletal disorders and symptoms: an update of the evidence. Occupational and Environmental Medicine, 73(1), 62-70. doi:10.1136/oemed-2015-102992Korunka, C., Dudak, E., Molnar, M., & Hoonakker, P. (2010). Predictors of a successful implementation of an ergonomic training program. Applied Ergonomics, 42(1), 98-105. doi:10.1016/j.apergo.2010.05.006Foxon, M. (1993). A process approach to the transfer of training. Australasian Journal of Educational Technology, 9(2). doi:10.14742/ajet.2104Stone, R. T., Watts, K. P., Zhong, P., & Wei, C.-S. (2011). Physical and Cognitive Effects of Virtual Reality Integrated Training. Human Factors: The Journal of the Human Factors and Ergonomics Society, 53(5), 558-572. doi:10.1177/0018720811413389Berg, L. P., & Vance, J. M. (2016). Industry use of virtual reality in product design and manufacturing: a survey. Virtual Reality, 21(1), 1-17. doi:10.1007/s10055-016-0293-9Mahmood, T., Scaffidi, M. A., Khan, R., & Grover, S. C. (2018). Virtual reality simulation in endoscopy training: Current evidence and future directions. World Journal of Gastroenterology, 24(48), 5439-5445. doi:10.3748/wjg.v24.i48.5439Wong, M. A. M. E., Chue, S., Jong, M., Benny, H. W. K., & Zary, N. (2018). Clinical instructors’ perceptions of virtual reality in health professionals’ cardiopulmonary resuscitation education. SAGE Open Medicine, 6, 205031211879960. doi:10.1177/2050312118799602Farra, S. L., Miller, E. T., & Hodgson, E. (2015). Virtual reality disaster training: Translation to practice. Nurse Education in Practice, 15(1), 53-57. doi:10.1016/j.nepr.2013.08.017Yin, C. W., Sien, N. Y., Ying, L. A., Chung, S. F.-C. M., & Tan May Leng, D. (2014). Virtual reality for upper extremity rehabilitation in early stroke: a pilot randomized controlled trial. Clinical Rehabilitation, 28(11), 1107-1114. doi:10.1177/0269215514532851Sacks, R., Perlman, A., & Barak, R. (2013). Construction safety training using immersive virtual reality. Construction Management and Economics, 31(9), 1005-1017. doi:10.1080/01446193.2013.828844Zhao, D., & Lucas, J. (2014). Virtual reality simulation for construction safety promotion. International Journal of Injury Control and Safety Promotion, 22(1), 57-67. doi:10.1080/17457300.2013.861853Li, X., Yi, W., Chi, H.-L., Wang, X., & Chan, A. P. C. (2018). A critical review of virtual and augmented reality (VR/AR) applications in construction safety. Automation in Construction, 86, 150-162. doi:10.1016/j.autcon.2017.11.003Chi, H.-L., Kang, S.-C., & Wang, X. (2013). Research trends and opportunities of augmented reality applications in architecture, engineering, and construction. Automation in Construction, 33, 116-122. doi:10.1016/j.autcon.2012.12.017Kaufman, R., & Keller, J. M. (1994). Levels of evaluation: Beyond Kirkpatrick. Human Resource Development Quarterly, 5(4), 371-380. doi:10.1002/hrdq.3920050408Bates, R. (2004). A critical analysis of evaluation practice: the Kirkpatrick model and the principle of beneficence. Evaluation and Program Planning, 27(3), 341-347. doi:10.1016/j.evalprogplan.2004.04.011Holton, E. F. (1996). The flawed four-level evaluation model. Human Resource Development Quarterly, 7(1), 5-21. doi:10.1002/hrdq.3920070103Axtell, C. M., Maitlis, S., & Yearta, S. K. (1997). Predicting immediate and longer‐term transfer of training. Personnel Review, 26(3), 201-213. doi:10.1108/00483489710161413Norman, G. (2010). Likert scales, levels of measurement and the «laws» of statistics. Advances in Health Sciences Education, 15(5), 625-632. doi:10.1007/s10459-010-9222-yTaber, K. S. (2017). The Use of Cronbach’s Alpha When Developing and Reporting Research Instruments in Science Education. Research in Science Education, 48(6), 1273-1296. doi:10.1007/s11165-016-9602-2HARRELL, W. A. (1990). PERCEIVED RISK OF OCCUPATIONAL INJURY: CONTROL OVER PACE OF WORK AND BLUE-COLLAR VERSUS WHITE-COLLAR WORK. Perceptual and Motor Skills, 70(3), 1351. doi:10.2466/pms.70.3.1351-1359Clark, R. E. (1983). Reconsidering Research on Learning from Media. Review of Educational Research, 53(4), 445-459. doi:10.3102/00346543053004445Metcalf, S., Chen, J., Kamarainen, A., Frumin, K., Vickrey, T., Grotzer, T., & Dede, C. (2014). Shifts in Student Motivation during Usage of a Multi-User Virtual Environment for Ecosystem Science. International Journal of Virtual and Personal Learning Environments, 5(4), 1-16. doi:10.4018/ijvple.201410010

Realidad virtual para la mejora de los procesos formativos de los trabajadores para la prevención de riesgos ergonómicos.

[ES] Junto con los desórdenes mentales, los trastornos músculo-esqueléticos con origen en el trabajo constituyen la principal de causa de enfermedad laboral y absentismo en la actualidad. Existen dos vías de actuación básicas para su disminución: la reingeniería del sistema productivo y la formación del trabajador. Existe un elevado consenso científico en que el empleo de TICs en los procesos de enseñanza-aprendizaje mejora sustancialmente sus resultados. Así pues, la introducción de nuevas tecnologías de la información y las comunicaciones y el desarrollo de contenidos inmersivos e interactivos pueden mejorar sustancialmente los resultados y la transferencia en la formación de los trabajadores. En este trabajo se han comparado diferentes medios didácticos para la formación de trabajadores con varios niveles de inmersividad e interactividad. Los resultados muestran que la introducción en los procesos formativos de nuevas tecnologías de la información y las comunicaciones, así como contenidos en formatos de alta inmersión e interactividad, mejoran los procesos de enseñanza-aprendizaje, aumentando el interés del trabajador formado, su grado de aprehensión de conocimientos, y la transferencia de estos a la situación real de trabajo.[EN] Mental disorders and work related musculoskeletal disorders are the main causes of occupational disease and absenteeism. There are two basic ways for its reduction: the reengineering of the productive system and the training of the workers. Previous works showed that the use of new technologies in the teaching-learning processes substantially improves their results. Therefore, using new communication technologies and developing immersive and interactive contents can substantially improve the results. In this work we have compared different didactic media for the training of workers with several levels of immersiveness and interactivity. The results show that using new information and communication technologies in the formative processes of the workers, as well as developing contents with high immersion and interactivity, improve the teaching-learning processes, increasing the interest of the trained worker, their degree of apprehension of knowledge, and the transfer of these knowledge to the real work situation.This work was supported by the Programa estatal de investigación, desarrollo e innovación orientada a los retos de la sociedad of the government of Spain under Grant DPI2016-79042-R.Diego-Mas, JA.; Poveda Bautista, R. (2019). Virtual reality to improve workers' skills for the prevention of ergonomics risks. AEIPRO. 1606-1616. http://hdl.handle.net/10251/181237S1606161

Automatic classification of human facial features based on their appearance

[EN] Classification or typology systems used to categorize different human body parts have existed for many years. Nevertheless, there are very few taxonomies of facial features. Ergonomics, forensic anthropology, crime prevention or new human-machine interaction systems and online activities, like e-commerce, e-learning, games, dating or social networks, are fields in which classifications of facial features are useful, for example, to create digital interlocutors that optimize the interactions between human and machines. However, classifying isolated facial features is difficult for human observers. Previous works reported low inter-observer and intra-observer agreement in the evaluation of facial features. This work presents a computer-based procedure to automatically classify facial features based on their global appearance. This procedure deals with the difficulties associated with classifying features using judgements from human observers, and facilitates the development of taxonomies of facial features. Taxonomies obtained through this procedure are presented for eyes, mouths and noses.Fuentes-Hurtado, F.; Diego-Mas, JA.; Naranjo Ornedo, V.; Alcañiz Raya, ML. (2019). Automatic classification of human facial features based on their appearance. PLoS ONE. 14(1):1-20. https://doi.org/10.1371/journal.pone.0211314S120141Damasio, A. R. (1985). Prosopagnosia. Trends in Neurosciences, 8, 132-135. doi:10.1016/0166-2236(85)90051-7Bruce, V., & Young, A. (1986). Understanding face recognition. British Journal of Psychology, 77(3), 305-327. doi:10.1111/j.2044-8295.1986.tb02199.xTodorov, A. (2011). Evaluating Faces on Social Dimensions. Social Neuroscience, 54-76. doi:10.1093/acprof:oso/9780195316872.003.0004Little, A. C., Burriss, R. P., Jones, B. C., & Roberts, S. C. (2007). 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The Influence of Each Facial Feature on How We Perceive and Interpret Human Faces

[EN] Facial information is processed by our brain in such a way that we immediately make judgments about, for example, attractiveness or masculinity or interpret personality traits or moods of other people. The appearance of each facial feature has an effect on our perception of facial traits. This research addresses the problem of measuring the size of these effects for five facial features (eyes, eyebrows, nose, mouth, and jaw). Our proposal is a mixed feature-based and image-based approach that allows judgments to be made on complete real faces in the categorization tasks, more than on synthetic, noisy, or partial faces that can influence the assessment. Each facial feature of the faces is automatically classified considering their global appearance using principal component analysis. Using this procedure, we establish a reduced set of relevant specific attributes (each one describing a complete facial feature) to characterize faces. In this way, a more direct link can be established between perceived facial traits and what people intuitively consider an eye, an eyebrow, a nose, a mouth, or a jaw. A set of 92 male faces were classified using this procedure, and the results were related to their scores in 15 perceived facial traits. We show that the relevant features greatly depend on what we are trying to judge. Globally, the eyes have the greatest effect. However, other facial features are more relevant for some judgments like the mouth for happiness and femininity or the nose for dominance.This study was carried out using the Chicago Face Database developed at the University of Chicago by Debbie S. Ma, Joshua Correll, and Bernd Wittenbrink.Diego-Mas, JA.; Fuentes-Hurtado, FJ.; Naranjo Ornedo, V.; Alcañiz Raya, ML. (2020). 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Improving Distributed Decision Making in Inventory Management: A Combined ABC-AHP Approach Supported by Teamwork

[EN] The need of organizations to ensure service levels that impact on customer satisfaction has required the design of collaborative processes among stakeholders involved in inventory decision making. The increase of quantity and variety of items, on the one hand, and demand and customer expectations, on the other hand, are transformed into a greater complexity in inventory management, requiring effective communication and agreements between the leaders of the logistics processes. Traditionally, decision making in inventory management was based on approaches conditioned only by cost or sales volume. These approaches must be overcome by others that consider multiple criteria, involving several areas of the companies and taking into account the opinions of the stakeholders involved in these decisions. Inventory management becomes part of a complex system that involves stakeholders from different areas of the company, where each agent has limited information and where the cooperation between such agents is key for the system's performance. In this paper, a distributed inventory control approach was used with the decisions allowing communication between the stakeholders and with a multicriteria group decision-making perspective. This work proposes a methodology that combines the analysis of the value chain and the AHP technique, in order to improve communication and the performance of the areas related to inventory management decision making. This methodology uses the areas of the value chain as a theoretical framework to identify the criteria necessary for the application of the AHP multicriteria group decision-making technique. These criteria were defined as indicators that measure the performance of the areas of the value chain related to inventory management and were used to classify ABC inventory of the products according to these selected criteria. Therefore, the methodology allows us to solve inventory management DDM based on multicriteria ABC classification and was validated in a Colombian company belonging to the graphic arts sector.Pérez Vergara, IG.; Arias Sánchez, JA.; Poveda Bautista, R.; Diego-Mas, JA. (2020). Improving Distributed Decision Making in Inventory Management: A Combined ABC-AHP Approach Supported by Teamwork. Complexity. 2020:1-13. https://doi.org/10.1155/2020/6758108S1132020Poveda-Bautista, R., Baptista, D. C., & García-Melón, M. (2012). Setting competitiveness indicators using BSC and ANP. International Journal of Production Research, 50(17), 4738-4752. doi:10.1080/00207543.2012.657964Castro Zuluaga, C. A., Velez Gallego, M. C., & Catro Urrego, J. A. (2011). Clasificación ABC Multicriterio: Tipos de Criterios y efectos en la asignación de pesos. ITECKNE, 8(2). doi:10.15332/iteckne.v8i2.35Morash, E. A., & Clinton, S. R. (1998). Supply Chain Integration: Customer Value through Collaborative Closeness versus Operational Excellence. Journal of Marketing Theory and Practice, 6(4), 104-120. doi:10.1080/10696679.1998.11501814Fabbe-Costes, N. (2015). Évaluer la création de valeurdu Supply Chain Management. Logistique & Management, 23(4), 41-50. doi:10.1080/12507970.2015.11758621Flores, B. E., & Clay Whybark, D. (1986). Multiple Criteria ABC Analysis. International Journal of Operations & Production Management, 6(3), 38-46. doi:10.1108/eb054765Partovi, F. Y., & Burton, J. (1993). Using the Analytic Hierarchy Process for ABC Analysis. International Journal of Operations & Production Management, 13(9), 29-44. doi:10.1108/01443579310043619Balaji, K., & Kumar, V. S. S. (2014). Multicriteria Inventory ABC Classification in an Automobile Rubber Components Manufacturing Industry. Procedia CIRP, 17, 463-468. doi:10.1016/j.procir.2014.02.044Ramanathan, R. (2006). ABC inventory classification with multiple-criteria using weighted linear optimization. Computers & Operations Research, 33(3), 695-700. doi:10.1016/j.cor.2004.07.014Van Kampen, T. J., Akkerman, R., & Pieter van Donk, D. (2012). SKU classification: a literature review and conceptual framework. International Journal of Operations & Production Management, 32(7), 850-876. doi:10.1108/01443571211250112Flores, B. E., Olson, D. L., & Dorai, V. K. (1992). Management of multicriteria inventory classification. Mathematical and Computer Modelling, 16(12), 71-82. doi:10.1016/0895-7177(92)90021-cGajpal, P. P., Ganesh, L. S., & Rajendran, C. (1994). Criticality analysis of spare parts using the analytic hierarchy process. 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Multi-criteria ABC inventory classification with mixed quantitative and qualitative criteria. International Journal of Production Research, 52(3), 776-786. doi:10.1080/00207543.2013.838328Ishizaka, A., Pearman, C., & Nemery, P. (2012). AHPSort: an AHP-based method for sorting problems. International Journal of Production Research, 50(17), 4767-4784. doi:10.1080/00207543.2012.657966Yu, M.-C. (2011). Multi-criteria ABC analysis using artificial-intelligence-based classification techniques. Expert Systems with Applications, 38(4), 3416-3421. doi:10.1016/j.eswa.2010.08.127Tsai, C.-Y., & Yeh, S.-W. (2008). A multiple objective particle swarm optimization approach for inventory classification. International Journal of Production Economics, 114(2), 656-666. doi:10.1016/j.ijpe.2008.02.017Aydin Keskin, G., & Ozkan, C. (2013). Multiple Criteria ABC Analysis with FCM Clustering. Journal of Industrial Engineering, 2013, 1-7. doi:10.1155/2013/827274Lolli, F., Ishizaka, A., & Gamberini, R. (2014). New AHP-based approaches for multi-criteria inventory classification. International Journal of Production Economics, 156, 62-74. doi:10.1016/j.ijpe.2014.05.015Raja, A. M. L., Ai, T. J., & Astanti, R. D. (2016). A Clustering Classification of Spare Parts for Improving Inventory Policies. IOP Conference Series: Materials Science and Engineering, 114, 012075. doi:10.1088/1757-899x/114/1/012075Zowid, F. M., Babai, M. Z., Douissa, M. R., & Ducq, Y. (2019). Multi-criteria inventory ABC classification using Gaussian Mixture Model. IFAC-PapersOnLine, 52(13), 1925-1930. doi:10.1016/j.ifacol.2019.11.484Babai, M. Z., Ladhari, T., & Lajili, I. (2014). On the inventory performance of multi-criteria classification methods: empirical investigation. International Journal of Production Research, 53(1), 279-290. doi:10.1080/00207543.2014.952791Schneeweiss, C. (2003). Distributed decision making––a unified approach. 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Machine learning for multi-criteria inventory classification applied to intermittent demand. Production Planning & Control, 30(1), 76-89. doi:10.1080/09537287.2018.1525506Kartal, H., Oztekin, A., Gunasekaran, A., & Cebi, F. (2016). An integrated decision analytic framework of machine learning with multi-criteria decision making for multi-attribute inventory classification. Computers & Industrial Engineering, 101, 599-613. doi:10.1016/j.cie.2016.06.004López-Soto, D., Angel-Bello, F., Yacout, S., & Alvarez, A. (2017). A multi-start algorithm to design a multi-class classifier for a multi-criteria ABC inventory classification problem. Expert Systems with Applications, 81, 12-21. doi:10.1016/j.eswa.2017.02.048Dweiri, F., Kumar, S., Khan, S. A., & Jain, V. (2016). Designing an integrated AHP based decision support system for supplier selection in automotive industry. 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Job rotation as a method for disabled workers integration

[ES] La Rotación de Puestos de Trabajo permite la variación de las tareas llevadas a cabo por los trabajadores y el tiempo empleado en cada una de ellas, facilitando la alternancia de los grupos musculares utilizados y la incorporación progresiva de trabajadores con problemas músculo-esqueléticos. Con la rotación es posible asignar a los trabajadores limitados a puestos compatibles con sus capacidades y restringir el tiempo que se exponen a factores de riesgo a los que son especialmente sensibles.Este trabajo presenta la aplicación del algoritmo DPI-ASEPEYO al diseño de agendas de RPT para prevenir los trastornos músculo-esqueléticos e integrar a trabajadores con limitaciones físicas, psíquicas o de comunicación en entornos de trabajo caracterizados por una elevada repetitividad de movimientos, como ocurre, por ejemplo, en las líneas de ensamblaje.[EN] Job rotation allows workers to vary their tasks and the time employed in each one of them, facilitating the change of the muscular groups used and the progressive incorporation of workers with musculoskeletal disorders. With the job rotation is possible to assign workers to workstations compatible with their limited capacities and to restrict the time that they are exposed to risk factors to which they are especially sensible. This paper presents the application of DPI-ASEPEYO algorithm, to the design of Job Rotation schedules to prevent musculoskeletal disorders and to integrate workers with physical, psychic or communication limitations in environs characterized by high repetitive movements as it happens, for example, in assembly lines.Agradecemos a la Universidad Politécnica de Valencia su apoyo a esta investigación a través de su Programa de Apoyo a la Investigación y Desarrollo 2009 y su financiación a través de los proyectos PAID-06-09/2902 y PAID-05-09/4215.Asensio Cuesta, S.; Diego-Mas, JA.; González-Cruz, MC. (2011). La rotación de puestos de trabajo como medio para la integración de trabajadores con discapacidad. DYNA: Ingeniería e Industria. 86(3):350-360. https://doi.org/10.6036/3863S35036086