In Memoriam Dario Franco

Vicens-Salort, E. (2014). In Memoriam Dario Franco. Editorial Universitat Politècnica de València. doi:10.4995/ijpme.2014.2004SWORD112

Parámetros en el diseño de puestos de trabajo simples

Se describen los parámetros básicos a establecer cuando se diseña un Puesto de Trabajo para la fabricación de una pieza o producto. Se definen el tiempo de ciclo y la capacidad de producción del puesto de trabajo. Se definen los conceptos de estándar de trabajo y productividad del recurso mano de obra. Se definen los mismos conceptos para los otros tipo de recursos que se utilizan en un puesto de trabajo. Se visualizan todos estos parámetros mediante los diagramas hombre-máquina. Y se establece cómo calcularlos.Vicens Salort, E. (2011). Parámetros en el diseño de puestos de trabajo simples. http://hdl.handle.net/10251/1378

Investimentos em transporte intermodal no Brasil poderia beneficiar o crescimento do PIB

[PT] Brasil é um dos países em desenvolvimento que faz parte dos BRICS, os quais juntos têm um potencial de crescimento e consumo de mais de 50% do PIB global. A distribuição de bens produzidos no território brasileiro requer um gerenciamento complexo devido a suas dimensões continentais. Uma rede de transporte mais eficiente e integrado deve reduzir os preços e trazer competitividade aos produtos brasileiros. A solução não é única e requer um planejamento global dos transportes, incluindo o uso de vários meios, transportes intermodais, o que reduzirá custos e tempo de entrega. Optou-se por um estudo qualitativo de banco de dados de agências governamentais e análise de estudos publicados sobre o tema. Este estudo apresenta os dados de custos baseado em preços internacionais. O Brasil tem adotado, tradicionalmente, o transporte rodoviário, apesar de ter outras opções disponíveis, como ferrovias ou hidrovias. Os resultados indicam que se o país não faz os investimentos necessários em modais adequados, perderá competitividade internacional levando à diminuição do PIB. Estudos de simulação de investimentos em modos de transporte e suas implicações sobre o crescimento do PIB seria o curso natural deste estudo. A importância deste trabalho é apontar para a necessidade urgente de investigar e investir outros meios de transporte nos países em desenvolvimento[EN] Brazil is one of developing countries part of the BRICS, which together have the potential to increase production and consumption by more than 50% of global GDP. The distribution of food produced in Brazilian territory requires a complex assessment, due to its continental dimensions. A network of more efficient and integrated transportation should reduce prices and bring competitiveness to Brazilian products. The solution is not unique and requires a global transportation planning, including using various means, intermodal transportation, to reduce costs and delivery time. This study aimed to analyze alternative modals other than roads, to deliver products within Brazilian territory. A database qualitative study was selected using governmental agencies data and analysis of published studies on the topic. Simulation was done to bring the decision-making using officials data projection. Using data from the literature review of government data on the subject, and further application in transport, simulation was applied seeking other alternatives for roads. Results presented national options and their costs based on international prices. Brazil has traditionally adopted road transportation, and other options are available, as railways or waterways. Results also indicate that if the country does not make the necessary investments in adequate modals, it will lose international competitiveness leading to decrease in the GDP. Include simulation studies on investments in modes of transport and its implications on GDP growth would be the natural course of this study. The importance of this study is to point out the urgent need to investigate and invest other means of transport in developing countriesThe authors wish to thank CAPES and CNPQ, and the Universitat Politècnica de València (UPV).Garcia, S.; Vicens Salort, E.; Nääs, I. (2015). Investment in intermodal transportation in Brazil could benefit the country's agribusiness GDP growth. Revista Brasileira de Engenharia de Biossistemas (Online). 9(1):90-98. doi:10.18011/bioeng91201590-98S90989

Sistema de Ayuda a la Toma de Decisiones para la gestión de Incidencias

[ES] Este artículo aborda los DSS, sistemas de ayuda a la toma de decisiones, cuando estas deben tomarse por incidencias en la empresa. La incidencia no es más que un evento no programado por la empresa, que puede repercutirnos negativamente en la empresa. Con lo que tenemos que crear métodos para actuar en su resolución de forma rápida y eficaz. Lo principal es definir los tipos de decisión por su forma de resolución, tanto por estar guiadas por las políticas y las normas de la empresa, como por quien toma las decisiones, creando una jerarquía en la toma de decisiones en la empresa, y dando importancia a una adecuada recogida de información y un tratamiento efectivo de la misma por la organización.[EN] This article talks about how the DSS (Decision Support Systems), working in support of decision making when these incidents are given by the company. The incidence is an event not expected by the company, which may have a negative impact in the company. So, it is necessary developing methods to act on its resolution quickly and efficiently. The main thing is to define the types of decisions by way of resolution, both being guided by the policies and rules of the company, as the decision maker, creating a hierarchy in decision-making in the company, and giving importance a good collection of information and the most effective treatment of this for use in the company.Esta investigación se ha llevado a cabo en el marco del proyecto financiado por el Vicerrectorado de Investigación de la Universitat Politècnica de València titulado “Sistema de ayuda a la toma de decisiones ante decisiones no programadas en la planificación jerárquica de la producción (ADENPRO-PJP)” Ref. SP20120703.Valero, R.; Boza García, A.; Vicens Salort, E. (2013). Sistema de Ayuda a la Toma de Decisiones para la gestión de Incidencias. En Industrial Engineering and Complexity Management. Grupo INSISOC. 1043-1049. http://hdl.handle.net/10251/78108S1043104

Diagnosis of quality management systems using data analytics - A case study in the manufacturing sector

[EN] The main objective is to improve customer satisfaction by developing and testing a method to study quality management systems by analysing the key performance indicators of balanced scorecards in manufacturing environments. The methodology focuses on the identification and quantification of relationships between internal and external metrics that allow moving from performance measurement to effective performance management. It has been tested as a case study approach using real data from two complete years of the balanced scorecard of a leading manufacturing company. The results provided a new understanding of how the quality management system works that was used to make systemic and strategic decisions to improve the long-term performance of the company. Industry practitioners with a moderate level of data analytical skill can use it to help managers and executives improve management systems.Sánchez-Márquez, R.; Albarracín Guillem, JM.; Vicens Salort, E.; Jabaloyes Vivas, JM. (2020). Diagnosis of quality management systems using data analytics - A case study in the manufacturing sector. Computers in Industry. 115:245-263. https://doi.org/10.1016/j.compind.2019.10318324526311

Diseño de puestos de trabajo complejos. Equilibrado de la capacidad e interferencias

En Vicens-Salort, E. y otros (2010) se estudió el diseño de Puestos de Trabajo Simples. Se establecía que para incrementar la productividad de un recurso de fabricación, como la mano de obra, se podían utilizar dos estrategias. La primera, cuyo objetivo es reducir la demora de proceso (DP) del sistema, se podría basar en la asignación de varias máquinas a un mismo operario. La segunda, cuyo objetivo es reducir la demora inherente (DI) del sistema, se basaría en el equilibrado de las diferentes capacidades (Cap) y tiempos de ciclo (TC) entre los elementos que constituyen el sistema. Aquí se pretende estudiar estas dos estrategias de mejora de la productividad en un sistema de fabricación: la reducción de las demoras de procesos mediante Asignación Multimáquina y la reducción de la Demora Inherente mediante el Equilibrado y ajuste de los tiempos de ciclo al Tiempo de Ciclo Requerido (o Tackt Time) determinado por la demanda de los productos que se fabrican. Previamente se definen algunos conceptos nuevos como el de Puesto de Trabajo Complejo y el de Batería de recursos.Vicens Salort, E.; Andrés Romano, C.; Miralles Insa, CJ. (2015). Diseño de puestos de trabajo complejos. Equilibrado de la capacidad e interferencias. http://hdl.handle.net/10251/5087

A systemic methodology for the reduction of complexity of the balanced scorecard in the manufacturing environment

[EN] The main objective of this paper is to develop and validate a methodology to select the most important key performance indicators from the balanced scorecard. The methodology uses and validates the implicit systemic hypothesis in the balanced scorecard model, together with a qualitative and statistical analysis. It helps to determine a small set of indicators that summarizes the company's performance. The method was tested using actual data of 3 complete years of a multinational manufacturing company's balanced scorecard. The results showed that the scorecard can be summarized in six metrics, one for each dimension, from an initial scorecard composed of 90 indicators. In addition to reducing complexity, the method tackles the hitherto unresolved issues of the analysis of the trade-offs between different dimensions and the lagged effects between metrics.Sánchez-Márquez, R.; Albarracín Guillem, JM.; Vicens Salort, E.; Jabaloyes Vivas, JM. (2020). A systemic methodology for the reduction of complexity of the balanced scorecard in the manufacturing environment. Cogent Business & Management. 7(1):1-18. https://doi.org/10.1080/23311975.2020.1720944S11871Anand, M., Sahay, B. S., & Saha, S. (2005). Balanced Scorecard in Indian Companies. Vikalpa: The Journal for Decision Makers, 30(2), 11-26. doi:10.1177/0256090920050202Banker, R. D., Chang, H., Janakiraman, S. N., & Konstans, C. (2004). A balanced scorecard analysis of performance metrics. European Journal of Operational Research, 154(2), 423-436. doi:10.1016/s0377-2217(03)00179-6Bansal, A., Kauffman, R. J., & Weitz, R. R. (1993). Comparing the Modeling Performance of Regression and Neural Networks as Data Quality Varies: A Business Value Approach. Journal of Management Information Systems, 10(1), 11-32. doi:10.1080/07421222.1993.11517988Boj, J. J., Rodriguez-Rodriguez, R., & Alfaro-Saiz, J.-J. (2014). An ANP-multi-criteria-based methodology to link intangible assets and organizational performance in a Balanced Scorecard context. Decision Support Systems, 68, 98-110. doi:10.1016/j.dss.2014.10.002Chytas, P., Glykas, M., & Valiris, G. (2011). A proactive balanced scorecard. International Journal of Information Management, 31(5), 460-468. doi:10.1016/j.ijinfomgt.2010.12.007Dong, Y., & Qin, S. J. (2018). A novel dynamic PCA algorithm for dynamic data modeling and process monitoring. Journal of Process Control, 67, 1-11. doi:10.1016/j.jprocont.2017.05.002Ferenc, A. (2011). Balanced scorecard measurement applications at a car manufacturer supplier company. https://pdfs.semanticscholar.org/f10e/409533c49dd2934ace78405126978302ab96.pdfFisher, R. A. (1992). Statistical Methods for Research Workers. Breakthroughs in Statistics, 66-70. doi:10.1007/978-1-4612-4380-9_6Gans, D. J. (1981). Corrected and Extended Tables for Tukey’s Quick Test. Technometrics, 23(2), 193-195. doi:10.1080/00401706.1981.10486265Grillo, H., Campuzano-Bolarin, F., & Mula, J. (2018). Modelling performance management measures through statistics and system dynamics-based simulation. Dirección y Organización, (65), 20-35. doi:10.37610/dyo.v0i65.526Gurrea, V., Alfaro-Saiz, J.-J., Rodriguez, R., & Verdecho, M. J. (2014). Application of fuzzy logic in performance management: a literature review. International Journal of Production Management and Engineering, 2(2), 93. doi:10.4995/ijpme.2014.1859Hoque, Z. (2014). 20 years of studies on the balanced scorecard: Trends, accomplishments, gaps and opportunities for future research. The British Accounting Review, 46(1), 33-59. doi:10.1016/j.bar.2013.10.003Junior, I. C. A., Marqui, A. C. & Martins, R. A. (2008). Multiple case study on balanced scorecard implementation in sugarcane companies. http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.572.3364&rep=rep1&type=pdfKaplan, R. S. (2009). Conceptual Foundations of the Balanced Scorecard. Handbooks of Management Accounting Research, 1253-1269. doi:10.1016/s1751-3243(07)03003-9Ku, W., Storer, R. H., & Georgakis, C. (1995). Disturbance detection and isolation by dynamic principal component analysis. Chemometrics and Intelligent Laboratory Systems, 30(1), 179-196. doi:10.1016/0169-7439(95)00076-3Malmi, T. (2001). Balanced scorecards in Finnish companies: A research note. Management Accounting Research, 12(2), 207-220. doi:10.1006/mare.2000.0154Morard, B., Stancu, A. & Jeannette, C. (2013). Time evolution analysis and forecast of key performance indicators in a balanced scorecard. Global Journal of Business Research, 7(2), 9–27.Noerreklit, H., & Schoenfeld, H.-M. W. (2000). Controlling Multinational Companies: An Attempt to Analyze Some Unresolved Issues. The International Journal of Accounting, 35(3), 415-430. doi:10.1016/s0020-7063(00)00064-9Rodriguez, R. R., Saiz, J. J. A., & Bas, A. O. (2009). Quantitative relationships between key performance indicators for supporting decision-making processes. Computers in Industry, 60(2), 104-113. doi:10.1016/j.compind.2008.09.002Sanchez-Marquez, R., Albarracin Guillem, J. M., Vicens-Salort, E., & Jabaloyes Vivas, J. (2018). A statistical system management method to tackle data uncertainty when using key performance indicators of the balanced scorecard. Journal of Manufacturing Systems, 48, 166-179. doi:10.1016/j.jmsy.2018.07.010Sánchez Márquez, R., Albarracín Guillem, J. M., Vicens-Salort, E., & Jabaloyes Vivas, J. (2018). Intellectual Capital and Balanced Scorecard: impact of Learning and Development Programs using Key Performance Indicators in Manufacturing Environment. Dirección y Organización, (66), 34-49. doi:10.37610/dyo.v0i66.534Verdecho, M.-J., Alfaro-Saiz, J.-J., & Rodriguez-Rodriguez, R. (2014). A Performance Management Framework for Managing Sustainable Collaborative Enterprise Networks. 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An Approach to the Industrial Organization Engineering Background in Spain

[EN] In this article we review the historic background of Spanish Industrial Engineering and briefly compare it with its equivalents in the USA and other countries, indicating similarities and differences. We present the actions taken in Spain that have consolidated Organizational Engineering. First, we describe the early history in the older Schools of Industrial Engineering. We follow reporting the new Industrial Organization speciality in the Degree in Industrial Engineering and the Second Cycle of Industrial Organization Engineering that extends until the end of the last century. We present the actual academic organization to adapt to the European Higher Education Area (EHEA) along with the impact that its adaptation has had on the new Degrees, Master Degrees and Postgraduate Courses. Finally, a short section deals with the Organizational Engineering Development Association (ADINGOR), given its importance for the visibility and consolidation of Spanish Organizational Engineering in Spain and elsewhere.Companys Pascual, R.; Lario Esteban, FC.; Vicens Salort, E.; Poler, R.; Ortiz Bas, Á. (2017). An Approach to the Industrial Organization Engineering Background in Spain. Lecture Notes in Management and Industrial Engineering. 11-23. doi:10.1007/978-3-319-55889-9_2S1123ADINGOR. (2008). Documento de Requisitos para la verificación del título de “Grado en Ingeniería de Organización Industrial”. Boletín de la Asociación para el Desarrollo de la Ingeniería de Organización.ANECA. (2006). Libro Blanco. Título de Grado en Ing: de Organización Industrial.Companys, R. (2001). La Organización Industrial en la ETSII. Sevilla: Congreso de Ingeniería de Organización.Fons Boronat, J. M. (2001). La Ingeniería de Organización: Una visión desde la Administració de Empresas. Sevilla: Congreso de Ingeniería de Organización.Mula, J., Díaz Madroñero, M., & Poler, R. (2012). Configuración del Grado en Ingeniería de Organización Industrial en las universidades españolas. Dirección y Organización, 47, 5–20

Special Issue: Engineering Digital Transformation

García Sabater, JJ.; Poler, R.; Mula, J.; Vicens Salort, E. (2018). Special Issue: Engineering Digital Transformation. Journal of Industrial Engineering and Management. 11(2):185-186. https://doi.org/10.3926/jiem.2510S18518611

Intellectual Capital and Balanced Scorecard: impact of Learning and Development Programs using Key Performance Indicators in Manufacturing Environment

[EN] Within the current context, the Intellectual Capital has been unveiled as one of the Key drivers for companies¿ long-term profitability and sustainability. This paper proposes a new methodology using Key Performance Indicators (KPIs) from the Balanced Scorecard of a Manufacturing Company to confirm the impact of Learning and Development Programs in the actual performance of the organization. Statistical Multivariate and Multiple Regression techniques are applied as a systemic approach using KPIs to firstly analyze and confirm the impact of Learning & Development and secondly to design the best strategy for short term financial results and long term sustainability. The proposed methodology was applied in a Manufacturing Company to confirm its validity in practical terms.[ES] En el contexto actual, el Capital Intelectual ha resultado ser uno de los factores clave para la sostenibilidad y viabilidad de las compañías a largo plazo. En este documento se propone una nueva metodología que usa Indicadores Clave de Rendimiento del Cuadro Integral de Mando de una compañía manufacturera para confirmar el impacto de Programas de Desarrollo y Aprendizaje en la eficiencia real de la organización. Métodos Estadísticos Multivariantes y de Regresión Múltiple se han aplicado como técnica sistémica para primero analizar y confirmar dicho impacto y seguidamente diseñar la mejor estrategia para los resultados a corto plazo y la sostenibilidad a largo plazo. La metodología propuesta fue aplicada en una compañía manufacturera para confirmar y validar el método de forma práctica.Sánchez-Márquez, R.; Albarracín Guillem, JM.; Vicens Salort, E.; Jabaloyes Vivas, JM. (2018). Intellectual Capital and Balanced Scorecard: impact of Learning and Development Programs using Key Performance Indicators in Manufacturing Environment. Direccion y Organizacion. 66(diciembre 2018):34-49. http://hdl.handle.net/10251/122578S344966diciembre 201