Relationship between lean manufacturing tools and their sustainable economic benefits.

Traditionally, the isolated relationship of total preventive maintenance (TPM), quick setup (QS), overall equipment effec- tiveness (OEE), and one-piece flow (OPF) with economic sustainability (ESU) has been investigated; however, these lean manufacturing (LM) tools are implemented together into production systems, and traditional research does not report their relationships and interactions. To contribute to this gap, this paper integrates all those variables in a structural equation model (SEM), which are related by seven hypotheses that are validated using the partial least squares (PLS) technique using information from 176 responses to a questionnaire applied to the Mexican maquiladora industry. Additionally, a sensitivity analysis has been carried out to determine the probability of occurrence at high and low implementation levels for all variables when they occur in isolation, jointly and conditionally. Findings indicate that TPM is a precursor of QS and OEE, while QS is a precursor of OEE and OPF, OEE is a precursor of OPF and ESU, but also OPF is a precursor of ESU. The sensitivity analysis indicates that low levels of TPM are a risk for reaching adequate levels of OEE and QC, while low levels in OEE and OPF are a risk for reaching adequate ESU levels

Territorios sustentables en contexto de pandemia

La obra ofrece trabajos que brindan un conocimiento científico sobre el impacto de la pandemia en la salud, la economía, el ambiente y los territorios y se plantean desafíos para hacer más sostenible la vida en las ciudades y en el campo para insertarse y poder competir a nivel global

Reducing the environmental impact of surgery on a global scale: systematic review and co-prioritization with healthcare workers in 132 countries

Abstract Background Healthcare cannot achieve net-zero carbon without addressing operating theatres. The aim of this study was to prioritize feasible interventions to reduce the environmental impact of operating theatres. Methods This study adopted a four-phase Delphi consensus co-prioritization methodology. In phase 1, a systematic review of published interventions and global consultation of perioperative healthcare professionals were used to longlist interventions. In phase 2, iterative thematic analysis consolidated comparable interventions into a shortlist. In phase 3, the shortlist was co-prioritized based on patient and clinician views on acceptability, feasibility, and safety. In phase 4, ranked lists of interventions were presented by their relevance to high-income countries and low–middle-income countries. Results In phase 1, 43 interventions were identified, which had low uptake in practice according to 3042 professionals globally. In phase 2, a shortlist of 15 intervention domains was generated. In phase 3, interventions were deemed acceptable for more than 90 per cent of patients except for reducing general anaesthesia (84 per cent) and re-sterilization of ‘single-use’ consumables (86 per cent). In phase 4, the top three shortlisted interventions for high-income countries were: introducing recycling; reducing use of anaesthetic gases; and appropriate clinical waste processing. In phase 4, the top three shortlisted interventions for low–middle-income countries were: introducing reusable surgical devices; reducing use of consumables; and reducing the use of general anaesthesia. Conclusion This is a step toward environmentally sustainable operating environments with actionable interventions applicable to both high– and low–middle–income countries

Modelado de procesos smed y tpm con ecuaciones estructurales: estudio del caso de la industria maquiladora mexicana

Las simulaciones de sistemas fotovoltaicos sirven para estimar la producción en nuevas instalaciones y evaluar la eficiencia de los materiales en distintas zonas geográficas. El principal objetivo de esta tesis es la disminución de la incertidumbre en estas simulaciones a través de la reducción de la incertidumbre en los datos de radiación solar, ya que éstos aportan actualmente alrededor de un 50% de la incertidumbre total. Las simulaciones no se suelen realizarse con mediciones de radiación solar debido a la escasez de estaciones con piranómetros. Sin embargo, la incertidumbre de estas mediciones es fundamental en la mayor parte de estudios de radiación solar. Hemos observado que la incertidumbre de los fotodiodos de silicio es muy superior a la de los piranómetros térmicos cuando no son calibrados adecuadamente. Esta incertidumbre puede ser incluso superior a la de las mejores bases de datos de radiación debido a la aparición de fallos operacionales en las estaciones, los cuales son muy comunes en redes regionales y agrícolas como SIAR. Los métodos de control de calidad más utilizados, como los que propone la BSRN, no son capaces de detectar este tipo de errores. Por tanto, hemos desarrollado un nuevo método de control de calidad, denominado BQC, que es capaz de detectar defectos operacionales y de equipo analizando la estabilidad de las desviaciones entre varias bases de datos de radiación y las mediciones del sensor. Las simulaciones de sistemas fotovoltaicos utilizan generalmente estimaciones obtenidas a partir de imágenes de satélite debido a su alta resolución espacial y temporal. Hemos verificado que las bases de datos obtenidas a partir de satélites geoestacionarios, como SARAH y NSRDB, proporcionan los datos con el menor bias e incertidumbre. También hemos evaluado el potencial de los datos de reanálisis para complementar a los modelos de satélite en las regiones polares. Los resultados obtenidos confirman que no es recomendable el uso de versiones antiguas como ERA-Interim o MERRA, pero revelan que nuevos modelos como ERA5 o COSMO-REA6 son una alternativa válida. Estos resultados llevaron a la inclusión de ambas bases de datos en el simulador online PVGIS. Sin embargo, los usuarios de estos productos deben tener en cuenta sus limitaciones; especialmente la variación de sus errores con el grado de claridad del cielo debido a una deficiente predicción de nubes. El análisis de la propagación del bias en las simulaciones confirmó que SARAH es la mejor base de datos para modelar sistemas fotovoltaicos en la mayor parte de Europa, mientras que ERA5 es la mejor alternativa en el norte de Europa. Este estudio también reveló que los errores en la predicción de nubes amplifican el bias de los datos de reanálisis en las simulaciones. Estas amplificaciones son a veces superiores al bias de las estimaciones de radiación solar por lo que deben ser consideradas al seleccionar bases de datos para la simulación de sistemas fotovoltaicos.PV system simulations are used to estimate the energy yield of new installations and assess the performance of PV materials in different regions. This thesis focuses on reducing the uncertainty of these simulations by quantifying and decreasing the uncertainty in solar radiation data, which currently accounts for around 50% of the total uncertainty. Simulations seldom use solar radiation measurements due to the scarcity of ground sensors. However, the uncertainty in measurements is the basis of most solar radiation studies. We found that low-cost photodiodes present substantially larger uncertainties than thermopile pyranometers if they are inadequately calibrated. The uncertainty further increased due to operational failures, which were very common in regional and agricultural networks, leading to uncertainties in measurements higher than those of the best radiation databases. Moreover, these defects were not detected by the most widely used QC methods, such as the BSRN tests. Hence, we developed a new QC procedure, the BQC, that identified most operational defects and some equipment errors by analyzing the stability of the deviations between several radiation databases and measurements. Solar radiation estimations are customarily used to assess PV systems due to their extensive spatiotemporal coverage and high resolution. We verified that databases from geostationary satellites, such as SARAH or NSRDB, should be preferred to assess the solar resource because they present the smallest bias and uncertainty. We have also evaluated the potential of reanalyses to complement satellite-based data in high latitudes. We confirmed that former ERA-Interim and MERRA reanalyses should be avoided, but we found that ERA5 and COSMO-REA6 are valid alternatives to satellite-based databases. These results validated the incorporation of both reanalyses in the online simulator PVGIS. However, users should take into account their limitations; primarily the strong dependence of their deviations on the atmospheric transmissivity due to the incorrect modeling of clouds. The analysis of the uncertainty propagation through PV simulations confirmed that SARAH should be preferred to assess PV systems in Central and South Europe, whereas it revealed that ERA5 is the best alternative in Northern Europe. We also found that cloud-related errors in reanalyses amplified the bias through the simulations. These amplifications should be accounted for selecting databases because their magnitude is sometimes larger than the bias of solar radiation estimations

“Modelado de herramientas para la optimización de procesos de producción mediante ecuaciones estructurales”.

Esta tesis tiene como objetivos, analizar el efecto que tienen las herramientas de manufactura esbelta como Single Minute Exchange of Die (SMED) y Mantenimiento Productivo Total (TPM) sobre los objetivos que se obtienen de su implementación en las industrias maquiladoras de Ciudad Juárez y en la industria del vino de La Rioja en España. Así mismo, se tiene como objetivo analizar el efecto de las Tecnologías de Manufactura Avanzada (AMT) sobre los beneficios que se obtienen al implementarlas en la industria maquiladora de Ciudad Juárez. Para cumplir con los objetivos mencionados, se construyeron cinco modelos de ecuaciones estructurales que relacionan las actividades de cada una de las herramientas y las tecnologías de manufactura avanzada con los beneficios que se obtienen de su implementación. Los modelos se desarrollaron en el software WarpPls 6.0 con la información obtenida de la industria maquiladora de Ciudad Juárez y la industria del vino de La Rioja en España. Esta información se recabó con cinco cuestionarios diferentes construidos de la revisión de literatura y se utilizó para construir cuatro cuestionarios diferentes los cuales se validaron por juicio de expertos y de manera estadística. Con los resultados obtenidos de los modelos analizados, se puede decir que los gerentes y/o administradores de las industrias maquiladoras de Ciudad Juárez tienen un punto de partida al momento implementar metodologías como SMED y/o TPM, es decir, los gerentes pueden consultar los resultados en estos modelos con el fin de identificar las actividades más importantes al momento de la implementación de dichas metodologías. Asimismo, se destacan las tecnologías de manufactura avanzada que más contribuyen a los beneficios dentro de la industria maquiladora. De la misma forma, se da un punto de partida para los administradores de las bodegas de la industria del vino de la Rioja sobre la importancia de la infraestructura regional y local en los planes de producción y el uso de las TIC´s para el seguimiento de las materias primas y los productos terminados y como el transporte correcto dentro de esta industria trae beneficios económicos

Impact of Infrastructure and Production Processes on Rioja Wine Supply Chain Performance

This paper presents a structural equation model for analyzing the relationship between four latent variables: infrastructure, production processes, transport benefits, and economic benefits within the supply chain for wine from La Rioja, Spain, by incorporating 12 observed variables. The model proposes six hypothesis that were tested using information gathered from 64 surveys completed by managers of several wineries in the region. The WarpPLS v.5 ® software (Version 5.0, Script Warp Systems, Laredo, TX, USA) was used to execute the model and analyze the direct, indirect, and total effects among latent variables. The results show that the control of production processes is a direct source of economic and transport benefits because of its higher explanatory power of those variables. Similarly, infrastructure is a direct source of transport and production benefits, and some of them are given indirectly. In addition, infrastructure does not have a direct effect on economic benefits; however, there were indirect effects given through production process and transport benefits. Infrastructure is a very important variable because of its influence in the final performance, but also because of its high environmental impact. Finally, economic benefits were explained in 43.8%, 19.1% belonging to production process, 21.1% coming from transport benefits, and 3.7% from infrastructure

Modelado de procesos smed y tpm con ecuaciones estructurales: estudio del caso de la industria maquiladora mexicana

Las simulaciones de sistemas fotovoltaicos sirven para estimar la producción en nuevas instalaciones y evaluar la eficiencia de los materiales en distintas zonas geográficas. El principal objetivo de esta tesis es la disminución de la incertidumbre en estas simulaciones a través de la reducción de la incertidumbre en los datos de radiación solar, ya que éstos aportan actualmente alrededor de un 50% de la incertidumbre total. Las simulaciones no se suelen realizarse con mediciones de radiación solar debido a la escasez de estaciones con piranómetros. Sin embargo, la incertidumbre de estas mediciones es fundamental en la mayor parte de estudios de radiación solar. Hemos observado que la incertidumbre de los fotodiodos de silicio es muy superior a la de los piranómetros térmicos cuando no son calibrados adecuadamente. Esta incertidumbre puede ser incluso superior a la de las mejores bases de datos de radiación debido a la aparición de fallos operacionales en las estaciones, los cuales son muy comunes en redes regionales y agrícolas como SIAR. Los métodos de control de calidad más utilizados, como los que propone la BSRN, no son capaces de detectar este tipo de errores. Por tanto, hemos desarrollado un nuevo método de control de calidad, denominado BQC, que es capaz de detectar defectos operacionales y de equipo analizando la estabilidad de las desviaciones entre varias bases de datos de radiación y las mediciones del sensor. Las simulaciones de sistemas fotovoltaicos utilizan generalmente estimaciones obtenidas a partir de imágenes de satélite debido a su alta resolución espacial y temporal. Hemos verificado que las bases de datos obtenidas a partir de satélites geoestacionarios, como SARAH y NSRDB, proporcionan los datos con el menor bias e incertidumbre. También hemos evaluado el potencial de los datos de reanálisis para complementar a los modelos de satélite en las regiones polares. Los resultados obtenidos confirman que no es recomendable el uso de versiones antiguas como ERA-Interim o MERRA, pero revelan que nuevos modelos como ERA5 o COSMO-REA6 son una alternativa válida. Estos resultados llevaron a la inclusión de ambas bases de datos en el simulador online PVGIS. Sin embargo, los usuarios de estos productos deben tener en cuenta sus limitaciones; especialmente la variación de sus errores con el grado de claridad del cielo debido a una deficiente predicción de nubes. El análisis de la propagación del bias en las simulaciones confirmó que SARAH es la mejor base de datos para modelar sistemas fotovoltaicos en la mayor parte de Europa, mientras que ERA5 es la mejor alternativa en el norte de Europa. Este estudio también reveló que los errores en la predicción de nubes amplifican el bias de los datos de reanálisis en las simulaciones. Estas amplificaciones son a veces superiores al bias de las estimaciones de radiación solar por lo que deben ser consideradas al seleccionar bases de datos para la simulación de sistemas fotovoltaicos.PV system simulations are used to estimate the energy yield of new installations and assess the performance of PV materials in different regions. This thesis focuses on reducing the uncertainty of these simulations by quantifying and decreasing the uncertainty in solar radiation data, which currently accounts for around 50% of the total uncertainty. Simulations seldom use solar radiation measurements due to the scarcity of ground sensors. However, the uncertainty in measurements is the basis of most solar radiation studies. We found that low-cost photodiodes present substantially larger uncertainties than thermopile pyranometers if they are inadequately calibrated. The uncertainty further increased due to operational failures, which were very common in regional and agricultural networks, leading to uncertainties in measurements higher than those of the best radiation databases. Moreover, these defects were not detected by the most widely used QC methods, such as the BSRN tests. Hence, we developed a new QC procedure, the BQC, that identified most operational defects and some equipment errors by analyzing the stability of the deviations between several radiation databases and measurements. Solar radiation estimations are customarily used to assess PV systems due to their extensive spatiotemporal coverage and high resolution. We verified that databases from geostationary satellites, such as SARAH or NSRDB, should be preferred to assess the solar resource because they present the smallest bias and uncertainty. We have also evaluated the potential of reanalyses to complement satellite-based data in high latitudes. We confirmed that former ERA-Interim and MERRA reanalyses should be avoided, but we found that ERA5 and COSMO-REA6 are valid alternatives to satellite-based databases. These results validated the incorporation of both reanalyses in the online simulator PVGIS. However, users should take into account their limitations; primarily the strong dependence of their deviations on the atmospheric transmissivity due to the incorrect modeling of clouds. The analysis of the uncertainty propagation through PV simulations confirmed that SARAH should be preferred to assess PV systems in Central and South Europe, whereas it revealed that ERA5 is the best alternative in Northern Europe. We also found that cloud-related errors in reanalyses amplified the bias through the simulations. These amplifications should be accounted for selecting databases because their magnitude is sometimes larger than the bias of solar radiation estimations

Impact Analysis of Total Productive Maintenance: Critical Success Factors and Benefits

This book present the state of the art in Total Productive Maintainance (TPM) and its benefits. The authors present a survey applied to 368 manufacturing industries in order to determine their level of execution of TPM. Then a series of causal models are presented. For each model, the authors present a measure of the dependency between the critical success factors and the benefits obtained, allowing industry managers to differentiate between essential and non-essential activities. The content also allows students and academics to obtain a theoretical and empirical basis on the importance of TPM as a lean manufacturing tool in the context of industry 4.0

Effect of AMT on Responsive Supply Chain Strategy, Pull System and Responsiveness to Market

This paper presents a model of structural equations in which four variables (advanced manufacturing technology, Pull system, responsiveness to market and, responsive supply chain strategy) are related using six hypotheses. The objective of the research is to measure the effect that occurs between these variables and identify the most important activities that have the greatest effect on the others. The model is statistically validated with information of 254 responses to a questionnaire applied in the manufacturing industry and the partial least squares technique is used. The results indicate that advanced manufacturing technologies indirectly help companies to be able to respond to changes in demand and allow them to offer a rapid response in the changing market through the implementation of a pull system

Effect of advanced manufacturing technology on responsive supply chain strategy, pull system and responsiveness to market

Nowadays, companies are requiring a fast response to market, and supply chain must be adapted. This paper presents a structural equation model (SEM) integrating advanced manufacturing technology, pull system, responsiveness to market as independent latent variables, and responsive supply chain strategy as dependent latent variable. Those variables are related using six hypotheses. The SEM is aimed to measure the effect among latent variables and identify the most important activities that have the greatest effect. The SEM is statistically validated using information from 254 responses to a questionnaire applied in the manufacturing industry, and the partial least squares (PLS) technique is used. Findings indicate that advanced manufacturing technologies indirectly support companies to be able to respond to changes in demand and allow them to offer a rapid response in the changing market through the pull system implementation