ABSTRACT. En esta comunicación presentamos algunos resultados y conclusiones en relación a un proyecto de investigación donde nos interesamos a las potencialidades y dificultades de los proyectos interdisciplinarios como propuestas didácticas. En esta ponencia nos limitaremos a las potencialidades de los proyectos interdisciplinarios para desarrollar modelizaciones en procesos argumentativos que se producen en el marco de un proyecto interdisciplinario. El proyecto a partir del cual basamos la investigación consiste en el cálculo, cons-trucción e instalación de molinos Savonius para pobladores rurales en economía de subsistencia que habitan en el norte de la meseta patagónica argentina

ABSTRACT. Sabemos que generar competencias de trabajo en grupo en los y las estudiantes de ingeniería es un desafío latente en los últimos años. Si bien la mayoría de las y los docentes podría asegurar que dan actividades para que se desarrollen en grupo, serían muy pocos/as los/as que dirían que han enseñado a trabajar en grupo. Por otro lado, la actual situación de distanciamiento social y de clases no presenciales ha resultado en un gran número de trabajos prácticos grupales como estrategia de enseñanza-aprendizaje virtual. En este trabajo, se exponen 2 actividades desarrolladas en la materia Gestión de la Calidad cuyas estrategias didácticas se basan en el Estudio de Casos y el Juego de Roles, mediante el trabajo grupal y se utilizan Autoevaluaciones y Coevaluación cómo métodos para el aprendizaje y mejora continua del hecho de trabajar en grupos formados aleatoriamente. En los casos abordados deben aplicar las herramientas AMFE (Análisis Modal de Fallos y Efectos) y el Diagrama de Causa y Efecto (Ishikawa) y QFD (Despliegue Funcional de la Calidad). Posteriormente, todos completan una grilla de auto y co-evaluación, programada en la plataforma Moodle, donde se evalúan aspectos como compromiso, respeto, integración en el grupo, escucha y preparación. Los resultados indican que la experiencia significó un crecimiento personal de la habilidad de trabajar en grupo, principalmente por el espacio de reflexión y retroalimentación generado.

ABSTRACT. Este trabajo se basa en una primera experiencia académica sobre el dictado de las materias del ciclo superior de matemáticas complementado con el uso y programación en la plataforma OCTAVE. Fue puesta en práctica para las carreras de Ingeniería en Alimentos e Ingeniería en Biotecnología de la Universidad Nacional de Río Negro durante los años 2019-2020.

ABSTRACT. This work presents an active learning methodology called Project-based learning (PBL) for developing artificial intelligence (AI) in a computer vision course of an undergraduate engineering degree. The objective of the course was to develop image recognition capabilities using Deep Learning (DL)/Machine Learning (ML) technics in real-world problems. The PBL learning methodology helped students search for real-world problems, develop complex solutions, and generate synergy among team members. The main role of the professor was to advise, guide and motivate the students throughout the course. The pedagogic innovation with active learning methodologies offered the professor the opportunity to create a dynamic motivating learning environment based on experiences. Each undergraduate engineering student had the opportunity to develop the skills and techniques of their profession: teamwork, proactivity, innovation, and leadership. The results obtained by the student teams showed problem-solving, including the use of automatic navigation equipment with AI, detection of the malaria parasite, recognition of non-human individuals to control vehicular traffic.

ABSTRACT. Para medir el conocimiento adquirido por un estudiante sobre un conjunto de objetivo de aprendizaje dado, es necesario realizar una evaluación. En general, en los colegios se utilizan pruebas estandarizadas para realizar esto. Sin embargo, este tipo de evaluaciones no logra captar el real conocimiento de los estudiantes sobre un conjunto de objetivos de aprendizajes determinado. En el presente trabajo se propone un nuevo método para realizar test que se adapten a los conocimientos de los estudiantes. Para ello, se consideran la relación entre los distintos objetivos de aprendizaje y la información histórica de un banco de preguntas.

ABSTRACT. El objetivo de este estudio fue analizar la tendencia de la temperatura y la precipitación actual y futura de la Región Pampeana (Argentina). Se utilizó información de precipitación y temperatura máxima y mínima in situ y datos futuros provistos por el modelo CCSM4. Se definieron cinco períodos de es-tudio: presente (2000-2019), futuro cercano RCP 4.5 y RCP 8.5 (2020-2039) y futuro lejano RCP 4.5 y RCP 8.5 (2080-2099). En cada uno de ellos, se calculó la tendencia termo-pluviométrica con el test de Mann Kendall. El área de estudio mostró señales de calentamiento atmosférico con significancia estadística en el presente y el futuro cercano y lejano bajo el escenario RCP 8.5. La precipitación tuvo tendencia negativa en el presente y se incrementó hacia el futuro. La variabilidad termo-pluviométrica impacta negativamente sobre la producción agropecuaria. Por lo tanto, estos resultados son esenciales para los tomadores de decisiones y los productores agropecuarios, dado que sirven de base para el diseño de medidas de mitigación orientadas a reducir los impactos de la variabilidad climática sobre las economías regionales.

ABSTRACT. La Región Pampeana es una de las áreas más productivas de la Argentina y por ello muy dependiente de las condiciones climáticas. El conocimiento de su variabilidad climática es esencial para orientar políticas destinadas a mejorar la calidad de vida de la población y el ambiente. El objetivo de este estudio fue analizar las tendencias de la precipitación y la temperatura durante las últimas seis décadas. Se utilizaron series de datos diarios de 50 estaciones meteorológicas durante el período 1960-2019. Luego, se analizó la tendencia termo-pluviométrica a escala local y regional, aplicando el test de Mann Kendall. La Región Pampeana presentó un aumento de las precipitaciones de 116 mm en los últimos 60 años, mientras que la temperatura mostró tendencias positivas y significativas en la mayor parte del área de estudio. Se identificó un aumento térmico regional superior a 1 ºC. La información generada en esta investigación es esencial para que los actores locales y tomadores de decisiones diseñen planes de adaptación a las condiciones a las que está expuesta el área de estudio.

ABSTRACT. El agua es un recurso natural indispensable para la actividad humana. En acuíferos costeros de espesor y extensión limitados, las variaciones en el uso del suelo pueden condicionar la calidad y cantidad de agua disponible para la explotación, ya sea para uso industrial o para abastecimiento de la población. El objetivo de este trabajo es cuantificar la expansión de las áreas forestadas y el efecto de esta expansión sobre la disponibilidad de agua subterránea, en la localidad de Mar de las Pampas, Partido de Villa Gesell, Provincia de Buenos Aires. A partir de imágenes satelitales y fotografías aéreas, mediante el mapeo manual detallado de los tipos de cobertura en la zona de estudio, se realizó un análisis del uso del suelo para los años 1975 y 2014. Se calcularon balances hídricos a partir de datos de precipitación, teniendo en cuenta las propiedades hidrológicas características del terreno, para asignar un valor de recarga a cada tipo de cobertura. Los resultados indican una reducción de la recarga de un 26% durante el período 1975-2014, lo cual deberá tenerse en cuenta para la planificación del uso sustentable del recurso hídrico subterráneo, en una localidad actualmente en crecimiento.

ABSTRACT. The wood drying is an important stage in the production process of a sawmill since it is where lumber acquires the level of humidity required by the market. Generally, it is a batch process that is carried out in dryers that operate in parallel out of phase. To cover the energy needs of the process, boilers fed with the by-products generated in the productive stages of the sawmill are used. To operate efficiently, the filling and scheduling of the dryers and the boiler feed and opera-tion must be planned simultaneously. In this paper, these decisions are addressed through a mixed integer linear programming model (MILP) using state-task net-work concepts based on a discrete time formulation. Different work criteria relat-ed to sawmill operation are analyzed, achieving very significant results for the performance of this industry.

ABSTRACT. In this work, a solution approach based on column generation for the log transportation problem in the Argentine forest industry is presented. This problem involves making decisions that covers aspects related to the size of the truck fleet, different types of delivered raw materials, different regional bases where trucks begin and end the routes, legal and contractual restrictions, among others, generating a problem very difficult to solve. This work is focused on the determination of the routes to be performed by the truck fleet to supply the plants with the available raw materials in the forest sites, at minimum cost. A representative case study of the Argentine forestry sector is presented and the corresponding results are detailed. The proposed approach allows solving problems with more than 500 full truck loads to transport per day (approximately 13,500 tons of raw materials) in less than 15 minutes of execution and with a negligible optimality gap.

ABSTRACT. The theme Industry 4.0 is a topic that interest is rising in several areas, as it deals with a revolution in the form of production through the introduction of disruptive technologies, which completely changes traditional processes. In parallel, there is great pressure from communities and governments for sustainable development from a social and environmental point of view, this makes companies look for technologies capable of contributing to a sustainable development policy of the organization. The present work aims to analyze articles that aim to investigate the means of investments in clean technologies and environmental innovations, such as estimates of return on investments and their barriers. Through the methodolo-gy of a systematic literature review, a bibliographic portfolio was composed of scientific articles. To make research feasible, limited taxes were considered, con-sidering only articles published in the English language, between the years 2000 to 2019 and available in the Web of Science, Scopus, and Science Direct data-bases.

ABSTRACT. In this paper we address an extension of the economic lot-sizing problem with remanufacturing, in which environmental costs are considered in the objective function in addition to the traditional economic costs. Separate costs for emissions, water and energy consumptions are assumed for the manufacturing and remanufacturing activities as well as to carry on positive inventories of both used and serviceable products. We provide a mixed-integer linear programming formulation for the problem and suggest several solving procedures based on the Tabu Search metaheuristic. In order to evaluate the suggested procedures, we compare them against an optimization solver over a benchmark set of instances of the literature extended for the problem. From the results obtained of the numerical experimentation, we can conclude that the suggested procedures are able to achieve near optimal solutions in a time-effective way. This effect is particularly significant for large instances of the problem. In addition, we consider an objective function with weighted costs, in order to analyze the effect of including environmental costs in the hybrid production-remanufacturing systems.

ABSTRACT. We address an extension of the discrete lot-sizing and scheduling problem in which the demand of products can be also satisfied by remanufacturing used products returned to the origin. A mixed-integer linear programming formulation is provided for the problem, assuming dynamic demand and returns values, and time-invariant costs of setup and holding inventory. We then present a numerical experimentation carried out with the mathematical model for the case of a single product, in order to evaluate the efficiency in both costs and solving times compared to the traditional problem without returns. From the results obtained we conclude that the problem with recovery options can lead to economic benefits only under certain assumptions on the costs and amounts of returns. In addition, according to the runtimes obtained for large instances of the problem, it seems to be much more difficult to solve than its traditional version without returns.

ABSTRACT. A mathematical model for the pulp and paper supply chain (P&PSC) network design is presented in this work, where the integration of bioethanol production is evaluated. The optimization model is used to analyze the impact of three cost reduction strategies: economies of scale, transport, and dynamic capacity. The problem is formulated as a generalized disjunctive programming (GDP) model and reformulated as mixed integer linear programming (MILP) one. It is implemented in GAMS and its feasibility has been tested using data from a real case study from Argentina.

ABSTRACT. The municipal solid waste system is a complex reverse logistic chain which comprises several optimisation problems. Although these problems are interdependent -- i.e., the solution to one of the problems restricts the solution to the other -- they are usually solved sequentially in the related literature because each is usually a computationally complex problem. We address two of the tactical planning problems in this chain by means of a Benders decomposition approach: determining the location and/or capacity of garbage accumulation points, and the design of collection routes for vehicles. We also propose a set of valid inequalities to speed up the resolution process. Our approach manages to solve medium-sized real-world instances in the city of Bahía Blanca, Argentina, showing smaller computing times in comparison to the full MIP model for large instances.

ABSTRACT. Teams are fundamental for innovation and efficient communication may be fundamental for team performance. The aim of this paper is to present the use of sociometric badges in real workplace teams to display how team structure com-munication patterns can be measured and analyzed. The selected method consists of four case studies of different organizations, where the unit of analysis is repre-sented by a meeting team. Use of this emergent technology allowed the evaluation of vocalization distribution, turn taking frequency and overlapping speech met-rics. Main results of the analysis showed that team vocalization tenure corre-sponds to performance results but vocalization distribution does not, which was unexpected. We found where the average speech segment was high, the meeting overcome the 100% of team vocalization tenure, and the total overlap time was al-so high. We identified different kinds of overlapping speech. Higher overlapping seems to occur more frequently when total overlap time is high but dominance is low than when total overlap and dominance are both high. Badges metrics also al-lowed a preliminary identification of three meeting stages. Finally, we identified possible future research lines.

ABSTRACT. Este trabajo compara los costos de medios de pago e impositivos asociados a ventas cobradas bajo diferentes modalidades (efectivo, medios bancarios y billeteras virtuales) y sensibiliza estos resultados ante incrementos de actividad o subdeclaración de ingresos. Metodológicamente se efectúa un análisis de caso simulado (microempresa de Bahía Blanca, Argentina) para dos regímenes tributarios: general y simplificado. Para ambos tipos de contribuyentes, el efectivo, el envío de dinero mediante billeteras virtuales y las transferencias son los medios de pago más económicos; mientras que las tarjetas de crédito, el point y el link de pago resultan los más onerosos. En términos relativos, la empresa adherida al régimen general afronta menores costos por medios de pago y mayores costos tributarios, respecto a la suscrita al régimen simplificado. La subdeclaración del 30 % de los ingresos en efectivo reduce a la mitad los costos impositivos por peso de ventas. El principal limitante a la adopción de medios electrónicos de pago en firmas pequeñas se asocia a la informalidad y no a los costos de transacción.

ABSTRACT. Work design is being constantly transformed by technology and requirements for polyvalent workers piloting the work system instead of operating it. Performance no longer depends exclusively on working hours, but in multiple aspects that balance the vision of production systems results. The purpose of this paper is to investigate self-management teams’ implementation and its effects on performance. A Brazilian cosmetics company case study of team development was used as a guidance for this investigation and company performance reports were the data source for descriptive statistics and multivariate analysis. Boxplot performance analysis was applied over team building stages along with One-way Variance Analysis to test average performance differences among stages’ transitions. Tukey test was sequentially applied to identify its statistic differences in pairs. Results revealed team development reached the expected performance over team stages. Forming to storming, though, was the only transition with no performance average gains. Storming to norming was the highest improvement, which meets literature principles. The present research is limited to a single sociotechnical environment and performance measurement is based on average data. Therefore, specific conclusions imply further research to extend findings to other contexts. However, the present study identified empowerment best practices to achieve superior performance. The originality of this paper consists on providing consistent connection between team development theory and practice, exploring sociotechnical approach benefits through practices into performance.

ABSTRACT. Este artículo tiene como objetivo la implementación de un modelo de localización de instalaciones para analizar el uso de los domicilios en el canal tradicional (tiendas de barrio) para mejorar la cobertura de la demanda de frutas y verduras con los cambios que ha supuesto la emergencia sanitaria causada por el COVID-19. Este tema presenta una gran relevancia dadas las restricciones de distanciamiento social y movilidad implementadas por muchos gobiernos para disminuir el contagio y garantizar la seguridad alimentaria de la población. El modelo busca la mejor configuración espacial de tiendas habilitadas para domicilios que incremente el acceso y la disponibilidad a las frutas y verduras. Se usó como caso de estudio los municipios de Chía y Cajicá en la región central de Colombia. Los resultados muestran que no es necesario más del 40% de tiendas habilitadas con servicio de domicilio para lograr la cobertura geográfica de las zonas críticas que son las áreas periféricas. Sin embargo, para incrementar la cobertura de la demanda si es necesario habilitar en más del 50% de tiendas el servicio de domicilio.

ABSTRACT. A qualidade da energia elétrica é importante para todos os setores da cadeia de fornecimento, desde a geração até a transmissão e distribuição da eletricidade. O aumento do número de empresas resulta em um acréscimo de cargas na rede, tornando necessário um monitoramento adequado da qualidade de energia, tanto pelas distribuidoras quanto pelos consumidores. A baixa qualidade de energia elétrica independente da sua causa, pode gerar perdas significativas aos consumidores, sendo as indústrias as mais afetadas em razão do seu alto consumo para produção de bens. Os distúrbios e as perdas de energia podem ocasionar a queima ou mau funcionamento de equipamentos, afetando diretamente o processo produtivo. É necessário identificar através do monitoramento, medição e análise, as situações que afetam a qualidade da energia em todos os segmentos. Nessa perspectiva, o presente estudo tem como objetivo realizar uma revisão sistemática de literatura para identificar os fatores que mais influenciam na qualidade do fornecimento da energia elétrica. O conhecimento dos fatores torna possível às organizações traçar um plano de gerenciamento da qualidade, podendo gerar um maior investimento em tecnologias para melhoria da produção e diminuição de gastos advindos desse consumo.

ABSTRACT. A indústria 4.0 vem mudando a forma de produzir, oferecendo tecnologias inteligentes aos sistemas de manufatura para a transformação tecnológica das plantas fabris. Esta mudança depende de aplicações e combinações de tecnologias digitais como a (IoT) para o monitoramento online para a realização da coleta, do armazenamento e da transformação dos dados do processo em informações valiosas para auxiliar nas tomadas de decisões. Neste contexto, constatou-se, que as pequenas e médias indústrias apresentam dificuldades na utilização dos dados de processo e são apontadas como um elo fraco, tornando-se as maiores vítimas na transição para a indústria 4.0. A pesquisa apresenta como objetivo a avaliação de como estão sendo tratada a medição de desempenho baseada em dados para máquinas, no contexto da indústria 4.0. A abordagem metodológica segue por meio da aplicação do método (Knowledge Development Process-Constructivist) Proknow-C, para a construção do Portifólio Bibliográfico e da Análise Bibliométrica de forma estruturada alinhando ao tema de pesquisa. O resultado apresentou o método de seleção do Portfólio Bibliográfico e a Análise Bibliométrica para mensurar de forma qualitativa e quantitativa o grau de relevância e reconhecimento científico da seleção do Portfólio Bibliográfico, o qual possibilitou a análise dos dados para construção de um modelo de medição de desempenho com base nas fontes dos artigos pesquisados.

ABSTRACT. There are several reasons for an organization to begin managing its energy use more efficiently. Regulations, resource scarcity, environmental impacts, increased consumer pressure and increased competitiveness are all reasons that have high-lighted energy management in recent years, both in the political and business landscape. In addition, associated with the expectation of increasing the efficiency of energy management systems, the application of technologies from Industry 4.0 is discussed. While promising, there are still few studies in the literature that ad-dress the relationship between these areas. Thus, through an integrative systemat-ic literature review, this paper presents and discusses the concepts and character-istics of Advanced Energy Management Systems, which are based on the integra-tion of Energy Management Systems and I4.0 technologies. The paper guides fu-ture works and companies that wish to apply Industry 4.0 technologies to their energy management systems by presenting potential benefits of this integration.

ABSTRACT. Este trabalho tem por objetivo analisar o impacto do agendamento de horário para refeições no tempo de espera em fila em um restaurante universitário. O estudo foi realizado com base no restaurante tipo self-service localizado na Universidade Federal do Paraná - campus Centro Politécnico, o maior polo da universidade atualmente, no qual o tempo de espera em fila externa é elevado em determinados horários. Empregou-se a metodologia de simulação de eventos discretos para reprodução do sistema, sendo os seus procedimentos implementados computacionalmente via MATLAB®. Os resultados obtidos são promissores, indicando que a adoção da política de agendamentos reduz o tempo médio em filas externas, e internas dependendo da distribuição de chegada da demanda, desde que os agendamentos nos horários de menor demanda para a refeição sejam preenchidos.

ABSTRACT. Nos últimos anos o termo inovação encontra-se em evidência. A mudança dos ambientes corporativos e a necessidade de inserção de novas tecnologias que ficam obsolescentes cada vez mais rápidas fazem com que decisões sobre qual destas utilizar seja bem fundamentada e baseie-se em critérios de relevância pelos diversos membros do setor. O impacto de uma decisão pode gerar uma linha tênue entre ganhos e prejuízos grandes para a empresa. A melhor maneira de contornar os impactos é tomar a decisão levando-se em consideração as principais dimensões da inovação. O artigo traz uma pesquisa sobre a preferência das camadas operacionais e de gestão de uma empresa de grande porte com relação às dimensões da inovação. A pesquisa foi realizada fazendo uso do método AHP (Analytic Hierarchy Process), comparando as dimensões. A ferramenta com AHP foi desenvolvida em python, sendo voltada à web, o que tornou possível a sua realização de uma forma mais rápida e de maneira remota.

ABSTRACT. Com a Revolução Industrial, os processos de produção sofreram muitas mudanças no método de trabalho, inovações e mobilidade. Com isso, aumentou a competitividade entre as empresas a consumidores cada vez mais exigentes. Nesse contexto, as empresas focaram no desenvolvimento de novos produtos, procurando obter maior rendimento com menos desperdícios adotando práticas lean. Além disso, com o objetivo de produzir com consciência, adotaram práticas green. Com a aplicação de práticas lean e green as empresas conseguem reduzir a quantidade de resíduos, melhorando a utilização de recursos produtivos e, consequentemente, aumentar a competitividade das empresas frente ao mercado consumidor. Para as pequenas e médias empresas (PME) a aplicação desses conceitos é mais complexa, devido à quantidade de recursos disponíveis. O objetivo desse trabalho é analisar o nível de maturidade de aplicação dos conceitos lean e green no processo de desenvolvimento de novos produtos de pequenas e médias empresas brasileiras e japonesas. A metodologia utilizada para atingir o objetivo foi a multicriterial, aliando o método Processo de análise hierárquica e variável linguística TOPSIS 2-Tuple. A pesquisa foi delimitada por PMEs japonesas e brasileiras, do mesmo setor e com foco em desenvolvimento de novos produto. Os resultados esperados são que o contexto japonês esteja com os princípios lean e green mais aplicados que o contexto brasileiro, principalmente na metodologia lean, visto que foi onde surgiu essa filosofia e está sendo utilizada há muito mais tempo, permitindo uma maturidade maior nas empresas.

ABSTRACT. The multi-objective optimization of a direct current rotary dryer that works with pozzolan in a semi-dynamic condition is described in this article. Four objective functions are minimized using the NSGA-II algorithm, these objective functions are: (1) the pozzolan humidity at the exit of the rotary dryer, (2) the heat given off by the rotary dryer to the environment, (3) the operating costs of the production process and (4) the number of new starts of the rotary dryer. The operating parameters for the 24-hour simulation were obtained. Simulation results show that it is not recommended to interrupt the dryer operation due to the high operating costs that this generates.

ABSTRACT. In this work, we propose a hierarchical optimization model to support har-vest and local routing decisions of fresh agricultural products. The proposed model has been motivated by the fact that small growers of fresh produce very often face difficulties in terms of availability of local (or first-mile) logistics at reasonable prices which results in lower profit margins and more food waste. So, in order to reduce the cost of first-mile logistics they can co-ordinate the consol-idation of the harvests from different growers to send their products to the pack-ing facility. Hence, we integrate harvesting and routing operations for a set of small growers with the aim to reduce their operational costs. The proposed frame-work has been implemented and preliminary evaluated with some instances con-sidering as case study farmers of fresh produce in the central region of Chile.

ABSTRACT. Com o crescente desenvolvimento econômico e tecnológico, as empresas estão cada vez mais descobrindo possibilidades de mercados, mas também estão encontrando mais concorrência e uma exigência maior na qualidade de seus produtos. Com o advento do Lean Manufacturing, muitas melhorias podem ser aplicadas no chão de fábrica, mas uma das mais efetivas é a simulação de eventos discretos. Com a simulação é possível representar com facilidade todas as etapas de estocagem, logística, fabricação e inspeção de uma entidade (matéria prima, produto semiacabado e produto final). Com a representação dos fenômenos no modelo de simulação se torna possível a identificação de qual melhor layout, aonde estão os gargalos, as perdas, quais estações de trabalho não estão trabalhando como deveriam, quais produtos possuem maior valor agregado. Este trabalho tem como objetivo desenvolver um modelo de simulação que represente da melhor maneira possível o setor de preparação de madeira em uma indústria moveleira. Por meio da análise dos processos produtivos que envolvem este setor, desenvolver ferramentas que possibilitem a coleta de dados do chão de fábrica, integração destes dados com o software de simulação e validação do modelo comparando os resultados com o histórico de produção. Posteriormente, é realizada a análise crítica do modelo, desenvolvimento das possíveis melhorias e aplicação destas no chão de fábrica. Por meio da metodologia utilizada, espera-se que o modelo atinja um elevado índice de similaridade com a realidade, proporcionando a fácil identificação dos gargalos e dando subsídios para a tomada de decisão da empresa.

ABSTRACT. This paper proposes a mixed-integer linear programming (MILP) model that is implemented based on a rolling horizon scheme to solve an aggregate production planning decision problem of a manufacturing company that produces snacks in Monterrey, Mexico. The demand of the company is characterized by trends and seasonality. The proposed solution is evaluated by means of computational experiments to determine the relation between demand uncertainty and flexibility of a production system. A 2k factorial experimental design and a multivariate regression were performed. Results show forecast bias and length of frozen period in the rolling horizon have a strong effect on total profit. The safety stock level was also found to be a significant factor, depending on the level of bias.

ABSTRACT. This paper presents an improvement of the branch and bound algorithm for the blocking-in-process and setup times permutation flow shop problem with total flow time criterion, which is known to be NP-Hard for m≥2. For that, a new ma-chine-based lower bound which exploits the machine idleness and the occurrence of blocking is proposed. Computational experiments were performed using a da-tabase that contains 27 classes of problems, varying the number of jobs (n) and the number of machines (m). Results show that the algorithm can handle most of the n<20 problems in less than one hour. Therefore, this work can support the scheduling of many applications in manufacturing systems with limited buffers and setup times.

ABSTRACT. The recent pandemic crisis has highlighted the importance of efficiency-oriented strategies to prevent the collapse of health systems under limited resources over the world. This assessment combines the advances in the outranking Multicriteria Decision Aid to the frontier estimations of Data Envelopment Analysis to support resource management in hospitals during the pandemic. The methodology involves determining an optimal direction for input contraction using the PROMETHEE method based on the value judgment of health experts in the frontline of COVID-19 to estimate the production capacity of hospitals through linear programming. The assessment aims at providing an avenue for local administrations' strategic planning.

ABSTRACT. The municipal government of Caruaru (PE), Brazil, has made several efforts to control the spread of the new coronavirus (COVID-19) in the municipality. The first action was the creation of a crisis management committee. Since then, Caruaru adopted some preventive actions, such as: suspension of classes in public and private schools and universities; prohibition of local commerce activities and non-essential services; creation of digital platforms to enable the commercialization of goods and services; cleaning and disinfection of public areas; investigation of people crowding; proposition of awareness campaigns and assistance to the vulnerable population. Despite all these preventive actions and the numerous awareness campaigns, there are a large number of reports of disrespect for the actions imposed. Does the population understand the need for social distancing? Do they understand the risk of the disease? Several strategies can guide individual actions and they have a direct and real reflection on the social distancing. Therefore, this study aimed to understand the residents' perceptions of social distancing and, consequently, the resumption of economic activities in the municipality. The results show that the population understands contagion risk from COVID-19, understands the need for social distancing, and prophylactic measures to reopen the commercial activities and recognize myths of the disease. However, there is a failure to comply with the actions imposed by the municipality.

ABSTRACT. The Covid-19 Pandemic affects social and economic relations in all national economies and the world economy, and their financial markets. Investment and production financing in economies take place through these markets, in particular in the capital market. The idiosyncratic risk represents the risk associated only with a specific productive project, with an economic sector, or with a specific national economy. This work aims to estimate the idiosyncratic risk of the Brazilian economy, through heteroscedastic conditional models, to verify the initial impact of the Covid-19 Pandemic on the risk associated with productive projects developed in the Brazilian and emerging economies, and to their financing and investments. Daily data in US$ cover-ing the period from June 30, 2017 to July 1, 2020 were used. Keywords: Covid-19 Pandemic, Idiosyncratic Risk, Brazilian Economy.

ABSTRACT. Social distancing and quarantine are considered the so far most effective policy to prevent an increasing contagion of COVID-19. While the economic impact from the implementation of this strategy is evident, empirical assessments to measure the impact on the disease outbreak are still scarce. The first results reported in this assessment aim at quantifying this prospect. Data over time and over the 27 Brazilian federations in 5 regions provided by Google’s COVID-19 Community Mobility Reports and classified by place categories (Retail and Recreation, Grocery and Pharmacy, Parks, Transit Stations, Workplaces, and Residences) are autoregressed on the COVID-19 incidence in Brazil using Generalized Linear Poisson Regression to measure the dynamic impact of mobility on each socioeconomic category. The assessment provides estimations for the time gap between contagion and data disclosure for public authorities decision-making, first estimations regarding the propagation R0 and R0+ in Brazil, and the mobility impact and marginal contribution for each place categories. The most critical cities in Brazil based on Optimized Hotspots Analysis are investigated with a brief discussion on the effects of population density and the Carnival in São Paulo and Rio de Janeiro. Suggestions for local planning based on the results are reported in the conclusion.

ABSTRACT. The Coronavirus SARS-CoV-2 (COVID-19) emerged by December 2019, in Wuhan, China; it was reported and, a few months after, in the most of countries we are living a pandemic of an (almost) unknown disease never observed before. For this reason, the importance of a good measurement on the counting of observed cases has a crucial role. This work addresses the time-lagged effect problem via Bayesian analysis supported by a stochastic discrete-event simulation to give an answer to the truthfulness of the data and to validate the obtained results in terms of proportions based on an expected result in the particular case of Spain. Obtained results show that the reported data is untruthful and can make wrong any analysis, but even when the simulating results are as we expected they might be wrong in terms of absolute numbers. However, the most important knowledge we get is related to the fact that the disease might be considered under control because it is more likely that a person gets recover than She/He dies.

ABSTRACT. En el presente trabajo se proponen distintos modelos de Programación Lineal Entera (PLE) que resuelven de forma exacta el problema de ruteo diario de camiones en la industria forestal. El objetivo en todos los casos es generar las rutas de los camiones involucrados a un costo mínimo, mientras se garantiza el suministro de materia prima a las plantas implicadas. Los modelos que se encuentran habitualmente en la literatura asumen que los viajes que se deben realizar se conocen de antemano o se generan en una etapa previa. A diferencia de esos enfoques, en este trabajo se genera la configuración de cada viaje junto con las decisiones de asignación de materia prima y ruteo. El modelo propuesto se evalúa en varios escenarios, demostrando en todos ellos que el enfoque propuesto resuelve eficientemente el problema abordado y mejora la performance respecto a los modelos ya existentes en la literatura.

ABSTRACT. Forest planning, based on mathematical optimization, makes it possi-ble to model the complexity of a forest system. In this work, two approaches to forest plantation planning were evaluated. Firstly, the aim was to regulate produc-tion and, secondly, to maximise economic benefit. The models proposed give sat-isfactory results and allow different forest management scenarios to be explored efficiently.

ABSTRACT. Resumen. Este trabajo estudia las decisiones logísticas asociadas a la asignación de un conjunto de pedidos de flores a un conjunto de plantas de producción con criterios de eficiencia y equidad. Adicionalmente se consideran restricciones de sincronización para la asignación de los productos con destino a los Estados Uni-dos. Se implementó un algoritmo de tipo heurístico para optimizar el balance en-tre oferta y demanda que evalúa tres reglas de ordenamiento de los subpedidos en conjunto con posibles días de desfase. La herramienta permitió resolver instancias con alrededor de 13000 subpedidos. El modelo se válida en un caso real de ma-nufactura del sector agroindustrial de las flores. Los resultados de los experimen-tos logran demostrar la capacidad del algoritmo para la asignación y sincroniza-ción de los subpedidos. Utilizando días de desfase se alcanzaron porcentajes de asignación del 100% de los subpedidos con la regla de ordenamiento aleatoria y minimizando la cantidad de residuo.

ABSTRACT. Con el objetivo de incrementar rendimientos metanogénicos en procesos de co-digestión anaerobia, se comparó el Potencial Bioquímico de Metano (PBM) de purín de cerdo y tres co-sustratos: macroalgas, plantas acuáticas, y restos de podas. Adicionalmente, para estimar parámetros cinéticos del bioproceso se implementó el Modelo de Remoción Biológica de Nutrientes Nº2 (BNRM2). Los resultados de PBM indican que la macroalga \textit{Spirogyra sp.} posee el mayor potencial para la generación de metano, produciendo 157,2 $\pm$ 66,1 mlCH$_4$/gSV, alrededor de tres veces más respecto a los otros co-sustratos. BNRM2 logró ajustar satisfactoriamente el comportamiento observado en las curvas de PBM, permitiendo identificar los parámetros más sensibles. Se concluye que la incorporación de macroalgas en bioprocesos de co-digestión anaerobia contribuye a potenciar la producción de metano. El empleo de BNRM2 en dichos bioprocesos puede servir tanto para estimar parámetros de difícil acceso empírico, como para predecir resultados empleando diversos co-sustratos.

ABSTRACT. La aplicación de fitosanitarios se ha vuelto una herramienta fundamental en el proceso actual de producción agropecuaria. La misma es compleja y dominada por muchos factores. A fin de ayudar a reducir las pérdidas y maximizar la eficiencia se decide realizar un ensayo con 3 pastillas de pulverización(3D-Defy-XR11002VP-TXA8002VK) a 2,6 bar de presión, con 50 litros de tasa de aplicación y 17 km/h de velocidad, circulando con el botalón a 0,75m sobre bancos que simulan objetivos tridimensionales donde se colocaron tarjetas hidrosensibles. Se evaluó Densidad de impactos, DV0,5 y Eficiencia. Se ob-tuvieron valores mayores de todos los parámetros en los objetivos horizontales. Las pastillas con algún tipo de angulación antero posterior mejoraron la unifor-midad de aplicación entre objetivos verticales. Las pastillas anguladas no mejoran las características de aplicación en objetivos verticales en comparación con el resto de las pastillas.

ABSTRACT. La investigación en temas relacionados con las prácticas de la calidad en cadenas de suministro es una tendencia creciente en los últimos años. Es de particular interés el estudio del impacto de aquellas sobre el desempeño de las cadenas de suministro. Aunque en la literatura se han desarrollado trabajos con modelos o metodologías de análisis sobre esta temática, los aportes continúan siendo escasos. Por ello, en este trabajo se desarrolla un modelo estructural de la relación entre las prácticas de calidad y el desempeño sostenible de cadenas de suministro. La metodología utilizada se basó en una revisión exhaustiva de trabajos previos para identificar enfoques y variables. En el modelo desarrollado las prácticas de calidad se representan en cinco variables de entrada: gestión de proveedores, aseguramiento de calidad, gestión del producto, gestión del cliente y administración y gestión.

ABSTRACT. The Paraguayan Chaco region is in a process of rural electrification, nevertheless, some commu-nities still use power units (generators) for the supply of electricity, while others communities have electricity distribution lines but suffer frequent supply interruptions due to the long distances between the sub-stations and the communities. This is the case of Fuerte Olimpo, which counts with electricity services through a distribution line of 23 kV, which suffers of reliability problems due to its extension of 150 kilometers, and has had 827 hours of electricity supply interruptions in 2019. This study proposes 3 alternatives to operate jointly with the current electricity distribution line: i) with generators, ii) photovoltaic solar energy with battery bank, and iii) through battery banks. The simulation and optimization has been made through the use of HOMER Energy soft-ware, in order to determine the most efficient energy source, considering the economic, environ-mental and technical criteria. The results show that: i) the generators are the most efficient alterna-tive from an economic perspective, with 0,118 USD/kWh of levelized cost of energy (LCOE), but presenting environmental issues. In the other hand, ii) the photovoltaic solar energy has an LCOE of 0,164 USD/kWh, but without greenhouse gases (GHG) emissions. Finally, iii) the mix of electricity distribution line and battery banks has a LCOE of 0,163 USD/kWH and presents null impact to the environment. This study recommends the use of the third alternative as the source of electricity in Fuerte Olimpo, considering the proposed objectives.

ABSTRACT. El calentamiento global ha tenido impactos negativos en la calidad de vida, la eficiencia de diferentes sectores productivos y el medioambiente. Los principales responsables de este calentamiento global son los gases de efecto invernadero (GEIs), en particular el díoxido de carbono ($CO_2$). Por otra lado, la malnutrición es un tema complejo a nivel mundial, alcanzando alrededor del 60\% de la población. Este trabajo aborda ambos problemas mediante el planteamiento de un modelo matemático para planificar las minutas alimentarias de un casino de una Universidad Pública de Chile, satisfaciendo requerimientos de calorías, cantidad de raciones diarias y de diversidad de preparaciones; minimizando la generación de dióxido de carbono equivalente ($CO_{2}$ eq). Los resultados muestran que una minuta generada por el modelo propuesto permite una disminución de un 96,85\% en las emisiones generadas en comparación con aquellas planificadas habitualmente para un periodo base de 25 días. Se concluye que este modelo podría ayudar a generar minutas diarias alimentariamente saludables y ecológicamente amigables.

ABSTRACT. Cluster analysis refers to the problem of optimally segmenting a set of entities and there are several types of algorithms to reach this purpose. It can be applied in decision making, machine learning, data mining and pattern recognition. The objective of this work is to develop a simple and fast partition heuristic to solve the cluster analysis problem, were the optimality criteria is the smallest distances between the vertices of the same cluster. To verify the proposed heuristic, tests were made in instances ranging from 20 to 5000 nodes and with different degrees of complexity. The developed heuristic can be applied to large size datasets were time could be limitation factor, as an example of application, the heuristic developed was used to choose the location for installing anaerobic co-digesters for the production of biogas in the state of Paraná, Brazil.

ABSTRACT. The growing use of agrochemicals added to the harm that contaminated containers cause to the environment and to the health of the population, make it necessary to establish a reverse supply chain for the recovery and correct treatment of empty containers. Current regulations establish that they must be triple-rinsed and sent to collection centers, where containers are consolidated and shipped to treatment/recycling plants. Containers can also be sent to these plants directly. Given this problem, this contribution proposes an MILP multi-period model to define the optimal configuration of the reverse supply chain network of empty agrochemical containers. Provided a superstructure including farms and the location of the potential nodes (collection centers and plastic treatment plants), the model determines which facilities to install and when, their corresponding sizes, as well as how they would operate along the planning horizon. In addition, the model establishes which are the material flows among the various nodes in each planning period (network topology). The proposed model has been verified by addressing a realistic case study, which has been solved under different scenarios, exhibiting good computational performance. The obtained results allow reaching satisfactory conclusions in relation to model scalability and sensitivity.

ABSTRACT. En la actualidad la planificación de las medidas de control para la continuidad del negocio y la resolución de imprevistos son elementos esenciales que las compañías de servicios básicos deben gestionar para disponer del buen funcionamiento de sus procesos en el caso de una interrupción. El reconocimiento de los procesos de mayor impacto para la organización es vital para el desarrollo sostenible y/o incluso para la supervivencia de cualquier organización. Un estudio de caso ha sido llevado a cabo en una empresa sanitaria de Chile priorizando los procesos de mayor impacto que podría permitir elaborar una política de prevención, lo que conlleva a un plan de inversiones. Para esto, se ha considerado cinco impactos al negocio como indispensables de ser contrastados para cada uno de los ocho procesos que posee la organización en estudio. Para la elaboración de esta priorización se aplica el Proceso de Jerarquía Analítica considerando opiniones de expertos y datos empíricos.

ABSTRACT. The Strategic Planning explores and projects the possible future changes of the environment to define the strategies. The Scenarios prospectively design possible futures and, consequently, the union of these two tools represents an enormous potential to improve the way of facing the future. The general objective "To develop a methodological proposal to create strategy maps that consider probable futures", the methodology integrates Scenarios with BSC, in order to relate and reflect the dynamics of environmental changes with the strategic objectives and with the strategies defined by the organizations. The methodological approach is qualitative based on the design of the Case Study because it seeks to validate a methodology, the generalization of the case study does not imply that in similar industries the same results will be obtained, but it is studied how plausible is the proposed methodology to formulate strategy maps for the management and administration of strategies in organizations. Defines three Scenarios, the strategy map is constructed for each one of them, using the ANP to determine the weight of the causal relationships in each scenario. The probabilities of occurrence of each scenario are assigned using AHP, finally achieve a "Global Scenario" that incorporates the three initially defined scenarios. Finally, the methodology is established to adjust and adapt the objectives and established strategies. This methodology was applied in two companies in Chile. The evaluation of the companies with respect to the intervention carried out coincided in that it is a real and valuable contribution to improve their business management.

ABSTRACT. The economic development of a company is directly linked to its capacity for technological innovation and the improvement of its products and services. In this scenario, the article presents a case study related to Banco do País, a centenary banking organization operating in Brazil. With the technological advance present in its activities, the company identified that its massive number of services agen-cies gradually became irrelevant for the purpose of the company. The paper ad-dresses a decision-making process regarding the identification of an agency that has low performance and is conducive to the closure of its activities in a county in Rio de Janeiro. In the decision analysis, the PROMETHEE-SAPEVO-M1 meth-od is performed, enabling a transparent assessment with data of different natures. For the application of the modeling, a web platform is implemented, allowing a clear evaluation through its numerical and graphic analysis, providing the identifi-cation of the most favorable agency for closure, without loss of effectiveness and enabling the allocation of reduced costs to the improvement of services and digital channels of the company.

ABSTRACT. Este trabajo analiza políticas públicas relacionadas con el cubrimiento de las instalaciones de salud en el área rural de Colombia. La localización, la cobertura y el tipo de instalación de salud en muchos países emergentes no han sido factores a tener en cuenta cuando se ha diseñado la red hospitalaria. Esto ha generado que muchas regiones experimenten una baja cobertura y otras estén sobrecubiertas. En el caso de Colombia, la jerarquía de niveles de servicio de las instalaciones de salud ha generado que el área rural cuente con deficiencias en el cubrimiento espacial al tener acceso solamente a servicios primarios. Por esta razón, este trabajo evalúa la situación actual en términos de la cobertura espacial de las instalaciones de salud y propone un modelo matemático de programación lineal entera mixta (MILP) para incrementar esta cobertura, así como la de la demanda teniendo en cuenta restricciones particulares de la situación rural de Colombia. Los resultados evidencian como el cambio en la distribución geográfica de las instalaciones existentes puede mejorar la cobertura espacial al reducir las distancias que los habitantes de una vereda deben recorrer para atender las necesidades de los servicios médicos.

ABSTRACT. The Brazilian Navy's main mission is to control maritime areas, deny the use of the sea to the enemy and design the Naval Power, thus defending the Brazilian Jurisdictional Waters (BJW). For this, a robust naval force is needed to enable the fulfillment of its mission. The Brazilian Navy Fleet is located in the interior of Guanabara Bay, where the Port of Rio de Janeiro is also located. This fact weak-ens the National Defense since there is the possibility of carrying out, by ships, submarines, or mines enemies, a dam or blockade of the only exit to the sea. Therefore, this paper aims to select the most suitable city to be the headquarters of the Second Fleet of the Brazilian Navy. Several localities distributed throughout practically all navigable areas of the Brazilian territory were analyzed as possible headquarters for the Second Squadron. For the structuring of the problem, the Soft Systems Methodology (SSM) was used. For the decision-making process, hybrid modeling was used, with the SAPEVO-M method to obtain the weights of the criteria and the VIKOR method for the evaluation of alternatives. For the composition of the model, the criteria Distance to the Sea (KM), Width of Depar-ture (KM), Distance from Rio de Janeiro (MN), Infrastructure for Repairs, and State of the Sea (Scale) were selected. After the application of the methods, the city of Belém was selected as the most indicated to be the headquarters of the new Brazilian Fleet.

ABSTRACT. A tomada de decisão na área da saúde é uma atividade complexa. Assim, diversas ferramentas têm sido desenvolvidas a fim de dar suporte ao usuário durante este processo. Uma destas ferramentas é a abordagem de questionário, utilizada em modelos de processo desenvolvidos em BPMN. Além disso, a modelagem de processos focada nas decisões, como o DMN, está ganhando destaque, tanto na literatura quanto nos ambientes de negócios. Neste contexto, esta pesquisa tem como objetivo analisar o suporte à tomada de decisão fornecido pela abordagem de questionário em modelos de processo desenvolvidos em BPMN e DMN. Assim, essas linguagens foram utilizadas para a modelagem de um dos tratamentos disponíveis para pacientes diagnosticados com acidente vascular cerebral (AVC). Foi realizado um estudo da literatura a fim de investigar como o BPMN e o DMN vêm sendo empregados no apoio à decisão para processos na área da saúde. Também é apresentada a aplicação do BPMN e DMN junto à técnica de modelo de questionário no processo para tratamento do AVC. Para finalizar, a análise comparativa das duas técnicas é apresentada, mostrando que, em DMN, o processo apresenta um ganho considerável na simplificação visual do processo quando o foco é a observação das decisões. Também, quando aplicado junto ao modelo de questionário, é evidente que tal técnica torna muito mais fácil o processo de implementação de ferramentas para apoio a decisão durante o caminho clínico.

ABSTRACT. This article investigates the bicycle allocation strategy in a competitive market of bicycle sharing at autonomous stations. The data scientist seeks to understand the market in the shortest possible time, while the customer wants to obtain the best experience of integrated use between the different modes of transportation. The initial position of bicycle stations, the coverage area and the allocation method are investigated, and with the assessment by mobility specialists or customers, the AHP method is fed, whose results combined with the previous data are grouped into clusters to detect the best and worst bike share stations. The case study was performed with real data from a bicycle sharing network in the city of São Paulo to demonstrate the effectiveness and feasibility of the proposed solution. The results show that the proposed method was able to quickly identify the efficiency of the position of bike share stations, enabling their further optimization.

ABSTRACT. Interoperability is a necessity for organizations to achieve their business objectives and remain in the market. For this, it must be continuously measured and improved. This paper aims to show a systematic literature review about interoperability assessment, using the methodology Proknow-C, with the objective of raising the main aspects of the researchs. Three phases of the method were made On the first phase was made the selection of the bibliographic portfolio (BP), were found 21 papers related to the subject. In sequence on the second phase was made a bibliometric analysis, at the third phase was performed a systematic analysis from the eleven papers that showed a model. The more expressive areas on the BP are the engineering and computer science. Is perceived a preponderance from studies focused on supply chain and government area assessment.

ABSTRACT. Quando se pensa em diferencial estratégico para melhorar a competitividade de um negócio, quase sempre os processos de S&OP (Sales and Operations Planning) e sua evolução, o IBP (Integrated Business Planning), estão em pauta. Estes processos, descrevem como os negócios devem criar e integrar seus planos estratégicos (vendas, marketing, desenvolvimento, fabricação, logística e finanças) para gerenciar o negócio e ao mesmo tempo, equilibrar o que está sendo produzido com que está sendo vendido. Este artigo apresenta uma pesquisa sobre como os processos de S&OP e IBP podem melhorar o fluxo de trabalho em um banco privado do Brasil, bem como podem ser usados em empresas ou departamentos do setor de serviços, e não só em empresas do setor industrial, setor precursor onde o S&OP foi utilizado pela primeira vez. O método de pesquisa adotado foi o de pesquisa-ação tendo sido realizada uma coleta de dados de departamentos específicos do banco privado e, até o momento, foram sugeridas algumas mudanças nos fluxos de trabalho. Na próxima etapa desse trabalho será utilizado um modelo de maturidade de S&OP/IBP, com intuito de identificar novas oportunidades de melhoria nos processos do banco privado e medir os resultados financeiros dessas melhorias.

ABSTRACT. O processo de empréstimos é essencial para sistemas financeiros. E com a queda dos juros, tal processo ganha espaço. Processos podem ser analisados por meio da mineração de processos, que tem como objetivo a análise a partir de dados sobre a execução do processo, o que permite o seu aprimoramento. Assim, esta pesquisa tem como objetivo o uso de técnicas de MP a fim de identificar melhorias para tornar esse processo competitivo em um ambiente mais tecnológico e capaz de atender uma demanda crescente. Inicialmente, foi realizada uma revisão sistemática da literatura para compreender o estado da arte da MP em ambientes financeiros. Na sequência, foi utilizada a técnica PM² a fim de compreender o registro coletado, realizar o seu tratamento, aplicar técnicas de mineração de processos e, então, propor melhorias. Desse modo, evidenciou-se que a MP, em sistemas bancários, é fortemente proposta junto a outras técnicas como forma de criar sistemas de previsão e identificação de fraudes. Porém, muitas vezes, não são realmente implementadas. Logo, conclui-se que o processo possui muitas oportunidades de melhorias, entre elas o desenvolvimento de técnicas que evitem que os clientes enviem documentos errados, um rearranjo das atividades entre os recursos, a eliminação da atividade “W_Handle_Leads” que não agrega valor. Como trabalhos futuros, propõe-se o desenvolvimento de um sistema de juros de empréstimos mais inteligente baseado em técnicas de aprendizagem de máquina que compreendem critérios mais sensíveis à necessidade e capacidade de pagamento do cliente.

ABSTRACT. This paper pretends to approach and analyse opportunities and risks that arises under the Industrial digital paradigm. Known by different names like Industry 4.0, Smart Manufacturing, or Production 4.0, among other terms digitalization in industry is advancing at a tremendous speed, and is pushing stablished firms to change and adopt new tools. Besides it opens opportunities to technological startups to deliver new products and services to the industrial market. As an example of opportunities in operating models, it is clear that digitalization under the model Industry 4.0 and the advantages of Industrial Internet of the Things (IIoT), allows faster response to customer demands, increase flexibility allowing the adaptability to manufacturing processes, and provides a tremendous amount of tools for quality improvement in the processes, among other ad-vantages. This article addresses the data driven organization as digitalization evolves and the progress of Artificial Intelligence (AI) and Machine Learning (ML) solutions for industry, such as those presented by new companies like LLamasoft, which provides AI for supply chain management (SCM), and Canvass Analytics, which provides an AI/ML platform to optimize processes, among a fresh bunch of startups that are evolving exploiting opportunities in this field.

ABSTRACT. With the rise of Industry 4.0 an era of real-time global connectivity between customers and the processes that transform consumer goods is imminent. Faced with the need to satisfy the current dynamic demand, the Japanese technology industry has developed an innovative production system called Seru, which is distinguished by its satisfactory results in economic and environmental terms. This study poses a production planning problem in a Seru production system considering heterogeneous workers and the energy consumption of production. To solve it, a multi-objective mathematical model is proposed in order to balance the production time between workers (intra-Seru) and between serus (inter-Seru) and minimize the total energy consumption. For larger instances, a metaheuristic algorithm is developed based on the evolutionary algorithm NSGA-II. Finally, the effectiveness of the proposed genetic algorithm is evaluated by comparing the area under the curve obtained with the solutions of the pareto frontier that it generates and the area under the curve from the pareto frontier of the multi-objective linear optimization model created via epsilon constraint.

ABSTRACT. Manufacturing execution concepts at the highest level of automation and interoperability are proposed by Industry 4.0. This is thanks to a group of information and communication technologies capable of creating integrated and connected systems, known as – cyber-physical systems. This network of integrated systems has been promoting gains in productivity, altering the profile of the workforce and the very conception of the work that will have more cognitive demands, increasing competitive potential. Therefore, organizations are more than ever willing to adapt for this scenario. Aiming to facilitate this digital transformation, avoiding an inefficient allocation of financial and human resources, the present work proposes a framework that provides the necessary guidelines for such a transformation becomes viable. This will be done by a series of analysis using multicriteria decision making methods (MCDM), evaluating the maturity of legacy systems, with a focus in the field of industrial maintenance. Those analysis are also based on the RAMI4.0 architecture, Total Productive Maintenance (TPM), Framework for Enterprise Interoperability (FEI), and will provide companies with guidelines for adequacy plans. To test and validate this framework, a multinational industrial entity belonging to the automotive sector was selected as a case study. The application results confirm that such tool can help in digital transformation projects and indicates adjustments for this to be done in a better way.

ABSTRACT. Given the nature of the activities that take place in agricultural production, it is necessary to develop a plan that integrates the resources available to achieve positive outcomes in the future. Due to the generation of poor forecasts based on highly variable approaches such as selective average method that ignore uncontrollable factors of significant impact on the responses set and which feed the planning carried out, the latter has turned out to be deficient in determining when to harvest banana's crops and therefore contributes to an increase in costs for a banana producer by not synchronizing supply-demand and cost associated to food security. As a solution, this paper develops a partially integrated business management process, which makes it possible to minimize costs-variations and it also allows the desired synchronization. This process consists of characterizing the system and identifying the relevant factors to subsequently generate a prediction that does include non-controllable variables such as rain. The identification of the relationship between rainfall and the percentage of harvested bananas allowed to design a planning model that not only efficiently distributes the available resources given the technical constricts but also determine a harvesting schedule that responds to the best possible compliance with demand for the company and a correct food security. Thus, the obtained results generate a prediction with a stronger reliability which, through a more accurate planning model program, leads to an effective harvesting program that goes in line with the company goals

ABSTRACT. Small and medium-sized enterprises (SMEs) represent a large portion of the economy and the availability of countries' jobs. These organizations, compared to large ones, have some advantages such as the faster response to changes and adoption of new systems and new technologies, as well as some limiting factors, such as financial capacity to investments, and reduced human resources to per-form all necessary tasks. With the advent of the so-called Fourth Industrial Revolution, new technologies emerge, with its multiple trends in applications and integration of physical and cyber systems, leading to new production strategies necessary for companies to position and competitive advantage in the long-term market. The great challenge for organizations, especially for SMEs, is to perceive and understand quickly, appropriately and assertively, the movement of abrupt changes resulting from these trends of convergence of technologies and systems, which requires training and guidance for the people involved in the process to implement Industry 4.0. The present work proposes a Roadmap for the imple-mentation of Industry 4.0 for SMEs, based on the concept of Lean Thinking. It is intended to present a new perspective through a guideline that supports and al-lows decision makers to better understand the process to adopt the digital trans-formation in their SMEs organizations.

ABSTRACT. With the recent advances in automation and information technologies that triggered the ongoing transformation of production systems into cyber-physical systems (CPS), many industrial organizations have been recently adopting data collection technologies to improve the efficiency and effectiveness of their processes. The Big Data Analytics are being used to analyze large amounts of data and help improve different aspects of an industrial operation. As enterprises face challenges such as increasing costs, quality control and operations. Systematizing how to apply data analytics to improve their processes and practices is, hence, a relevant issue. This paper contributes to this by providing an understanding of how to develop a data analytics process management in manufacturing industries. First, it reviews the existing literature related to data analytics, focusing on analysis and information requirements for manufacturing process and framework. Second, it discusses the major functionalities of data analytics process by presenting available in the literature, focusing on features that are useful for process management. Finally, it presents and discusses the implications for future research of a conceptual framework for the definition of data analytics process management.

ABSTRACT. The aim of industry 4.0 is to promote productivity and innovation by incorporating emerging IT technologies, where machine learning is playing a central role in this industrial revolution. In this sense, the production of new materials could take advantage of novel virtual testing approaches based on data science for supporting the design of new polymers. Nevertheless, the lack of data for learning virtual testing models constitutes a hard challenge for progressing in these innovative techniques. Therefore, it is especially important to create reliable databases for polymer study and make them available to the scientific community. In this work, we have focused on the generation of a trustworthy database of Refractive Index (RI) of synthetic polymers. This paper details the different types of errors found in the data source and the corrections made during the curation and cleaning of this database. Additionally, some Quantitative Structure-Property Relationship models for predicting RI, inferred without domain expert intervention, are presented and discussed for illustrating how virtual testing can be applied using this database.

ABSTRACT. Within the data science and artificial intelligence fields of study, machine learning have supported performance improvement in medicine, manufacturing, law and even sport environments. The purpose of this paper is to investigate how machine learning has been used as a tool to improve the assertiveness of decision-making, providing competitive advantages in the wide field of operations management. This exploratory research analyzes the content of five machine-learning studies, relating each of them to Slack’s strategy pillars: cost, speed, quality, flexibility and dependability. Research design was limited to Scopus’ papers published exclusively in high impact journals. Results emphasize the important role of machine learning in organizational competitive advantages and limitations are used to address further research suggestions, extending the present investigation with a more extensive bibliographic portfolio analysis. The contribution of this paper is a matrix analysis of how machine-learning projects indirectly contribute to at least three strategy dimensions simultaneously. Complementarily, an illustration was built for a better comprehension of the interrelationships among the strategic pillars reinforced by the analyzed studies.

ABSTRACT. El análisis de la eficiencia de una red de Centros de Atención Primaria de Sa-lud (CAPS) adquiere relevancia debido a que los servicios provistos en este nivel de atención son financiados mediante fondos públicos. Existen diver-sos métodos de medición de la eficiencia de una unidad de producción que permiten evaluar su desempeño y proponer estrategias de mejora. En particu-lar, para las instituciones proveedoras de servicios de salud existe una vasta literatura que utiliza el análisis envolvente de datos (DEA). En este trabajo se aplica el DEA para evaluar la eficiencia técnica de los CAPS del partido de Bahía Blanca (provincia de Buenos Aires, Argentina). Para ello, se agrupan los CAPS según las especialidades disponibles (enfermería, clínica médica y pediatría) y se emplea: un modelo DEA BCC output orientado y un modelo de Supereficiencia para evaluar la eficiencia técnica en cada grupo. Los re-sultados difieren entre los grupos. En los que tienen las 3 especialidades, la mayoría de los CAPS son eficientes. Por el contrario, en los CAPS que tienen enfermería y clínica médica, así como los que solo tienen enfermería, la ma-yoría de los CAPS son considerados ineficientes. Se concluye que puede aumentarse la eficiencia, a partir de incrementar las consultas y/o reducir la cantidad de horas de trabajo, en el uso de los recursos públicos asignados al primer nivel de atención en el partido de Bahía Blanca lo cual permitiría me-jorar las condiciones de acceso de la población más vulnerable a la atención de la salud

ABSTRACT. Las técnicas tradicionales de evaluación de eficiencia, DEA, asumen la hipótesis de que los valores de inputs y outputs son determinados con certeza. Sin embargo, en el mundo real, muchos procesos de producción involucran a menudo datos que son imprecisos, vagos o ambiguos. En estos casos, la impreci-sión o vaguedad puede ser expresada como una función de pertenencia dentro del ámbito de la lógica difusa. Si bien se han desarrollado varios modelos DEA-Fuzzy (FDEA) para manejar la incertidumbre en inputs y outputs, las aplicacio-nes para medir eficiencia en bancos han sido escasas. El objetivo de este trabajo es aplicar en forma comparativa el modelo DEA- CCR y el método FDEA propuesto por Guo y Tanaka, que surge como una extensión del modelo CCR clásico. Este método, proporciona una medida de eficiencia para cada unidad evaluada a partir de vectores de inputs y outputs difusos triangulares simétricos. Se utilizan estos métodos para evaluar la eficiencia técnica de las principales enti-dades bancarias de capital público de los estados que son parte o asociados al MERCOSUR. El estudio se realiza sobre las entidades bancarias nacionales de 9 países del MERCOSUR, en actividad durante el año 2019. Se puede concluir que el modelo FDEA utilizado es aplicable y proporciona una medida de la eficiencia de las entidades bancarias a diferentes niveles de posibili-dad, consistente con la proporcionada por el método DEA clásico.

ABSTRACT. A preocupação das organizações em redução de custos com energia elétrica, seja para otimização da economia organizacional, cumprimento de requisitos regulatórios ou melhoria da imagem no mercado, estão cada vez mais percebidos e incorporados no mercado corporativo. Assim, o objetivo deste artigo é discutir modelos existentes sobre melhores práticas em eficiência energética em edifícios comerciais. Para atingir o objetivo, foi realizada uma revisão sistemática da literatura em dezesseis artigos relacionados à temática, buscando suas principais contribuições e pontos convergentes. A pesquisa apresenta um panorama das proposições existentes de Modelos de Melhores Práticas de Eficiência Energética em edificações e principais contribuições, e pode ser utilizado como referência para proposição de novos modelos, considerando os gaps identificados neste estudo.

ABSTRACT. O objetivo deste estudo é descrever o desenvolvimento de uma máquina peletizadora para empresas que manufaturam produtos fracionados, dentre as quais inclui-se as alimentícias, calçadista, farmacêutica, automotiva, gráfica, eletroeletrônica, de materiais de construção, entre outras. Nesse contexto, observa-se problemas ocorridos pelo processo manual utilizado nas empresas, dentre os quais destacam-se as doenças relacionadas ao trabalho ocasionada pelos esforços e repetição das atividades. Desta forma, o desenvolvimento e aplicação do equipamento visa auxiliar a minimização ou eliminação das mesmas. Para isto, o referencial teórico adotado aborda os temas inovação, Pro-cesso de Desenvolvimento de Produto (PDP) e os tipos de carregamentos para o processo de peletização. Para atingir o objetivo, utilizou-se técnicas como por exemplo, a Matriz da casa da qualidade, Brainstorming e função global do produto e dividiu-se em tarefas dentro das fases de projeto informacional, conceitual e detalhado a partir do modelo de [15]. No estudo de caso, obteve-se as especificações-meta do produto no projeto informacional, na fase de projeto conceitual selecionou-se a concepção mais adequada e por fim, no projeto detalhado demonstrou-se o projeto com maiores de-talhes. Utilizando essa metodologia desenvolveu-se o projeto de um equipamento novo no mercado, considerando uma alta produtividade, diminuindo os riscos com doenças relacionadas ao trabalho e respeitando as normas regulamentadoras de segurança.

ABSTRACT. The healthcare product manufacturing industries are constantly changing, so they must find new ways to remain competitive in the market. With the concepts of the Industry 4.0 they search for new methods to integrate and optimize manufacturing processes. Seeking to contribute with optimization of the production control in CNC machining lines of a healthcare product, this research develops a system of data extraction and representation using an interoperable approach, called System ADCS 4.0. By its use, it is possible to share data in a systematic and structured way, so the management environment can control the production line process, evaluating the quality and productivity indicators of the company in an automated way. It consists in an application that receives the data from the machine, and translate it into a proper ontology, developed during this research. This way, the data will be treated according to semantic rules, by the application of an inference engine, generating knowledge, that will support professionals to take assertive decisions based on the data generated and displayed in a dash-board. Forms were created, using the BonitaSoft, to represent the results obtained from the application of the System ADCS 4.0, that consists in the representation of the indicators and the defects that occurred during the ma-chining process. The developed system helps companies to increase the productive process by reducing cost, time and it also helps professionals in the decision-making process.

ABSTRACT. Technology development projects are constantly subject to risks and uncertainties and their performance are key to deliver the organizational value. Failing to meet project goals and objectives is critical, therefore, projects must be able to cope with an environment of complexity and pressure. This paper aims to assess and improve project resilience by using the Functional Resonance Analysis Model (FRAM) to look at project review process, a stage-gate milestone typical to Systems Engineering process. FRAM is supported by the Resilience Engineering perspective that things go wrong by the same reasons they go right, and everyday work is subject to variability and small adjustments, which is key to address such project environments. After assessing sources of variability and aggregating them, means to manage variability are proposed order to increase process resilience.

ABSTRACT. Course Timetabling at universities can be defined as the scheduling of different courses in specific time slots. To carry out this process it is necessary to take into account key factors such as: available courses, the distribution of time slots and lecturers' availability. In addition, there are resources that are essential for the model performance. For instance, the available classrooms and their capacity to completely satisfy the specific demand of students. In this study, a mixed integer linear programming model is presented to find the optimal schedule of the courses. Results show that the proposed model provides feasible solutions where all the proposed factors are considered.

ABSTRACT. Inventory management aims to determine and control inventory levels within physical inventory, so that meeting the need for product availability and minimiz-ing inventory-related costs must be well balanced. In the automotive sector, spe-cifically in the auto parts branch, balancing costs and product availability is an ar-duous task. This research looks for alternative solutions to the problems derived from the lack of adequate inventory management for a spare parts company in Mexico. The objective of this work is to propose a new inventory policy that al-lows minimizing total inventory costs while satisfying the target service level for the company's customers. To carry out the objective, there is a previous analysis of the data of the selected products, through the forecast future demand using ARIMA models, to evaluate two inventory policies (s, S) and (R, S). The two policies allow minimizing inventory levels and days, as well as the costs associat-ed with excess inventory and inefficient handling of the same. Once the best in-ventory policy was defined, a joint replenishment system proposed by Atkins and Iyogun in 1998 was used, allowing items with low demand to be included in the orders for items with greater movement, thus eliminating a higher configuration cost in the near future. When the low-moving item reaches its reorder point.

ABSTRACT. En este trabajo se aborda un caso de estudio de la industria manufacturera del calzado. Particularmente, se analiza el caso de una PyME de calzado de cuero de Argentina. El estudio se focaliza en la variabilidad de rendimiento que implica trabajar con materias primas de origen animal, y su consiguiente impacto en la capacidad de producción. Para ello se modeló el proceso de producción respetando todos los factores que incorporaban incertidumbre al problema. Se generaron simulaciones de eventos discretos para analizar el sistema, y se detectó el cuello de botella. Al analizar las potenciales alternativas para salvar la limitación en la capacidad, se optó por la incorporación de un nuevo trabajador. Los resultados de la propuesta de solución permitieron mostrar que incorporar un trabajador aumentaba la productividad más que proporcionalmente al incremento directo de mano de obra.

ABSTRACT. El gran número de trabajos abordando el problema de scheduling en plantas batch deja en evidencia su importancia para lograr una operación eficiente de la planta, como así también su dificultad y el número de variantes que se pueden presentar. Usualmente el scheduling ha sido resuelto de manera simplificada, teniendo como datos el número y tamaño de batches (o lotes) necesarios para satisfacer la demanda. Más recientemente, han sido desarrollados modelos que resuelven simultáneamente el problema de batching, o sea determinar el número y tamaño de los lotes, y scheduling, logrando en general mejores soluciones. Sin embargo estos modelos son de una gran complejidad computacional, debido a su naturaleza combinatoria, por lo que lograr el desarrollo de modelos eficientes que permitan abordar problemas de gran tamaño continúa siendo un desafío. En este trabajo se presenta un novedoso modelo de programación mixta entera lineal (MILP) para la resolución simultánea del batching y scheduling en una planta batch multietapa, con unidades distintas operando en paralelo y fuera de fase en cada etapa.

ABSTRACT. La necesidad de generar programas de producción sustentables, ha contribuido a nuevos desarrollos innovadores en la gestión de operaciones. En muchos casos se han generado enfoques y herramientas que permitieron mejorar la sustentabilidad de las industrias. Dentro de esas mejoras, un tema recurrente, es la reducción del consumo energético y de las emisiones de carbono. En este trabajo se aborda el problema de scheduling de flow-shop con consideraciones energéticas utilizando estrategias de lot-streaming. El consumo energético se modela dentro de la función objetivo, junto con el makespan, por medio de una suma normalizada y ponderada. De esta forma, la reducción del consumo energético guía el proceso de optimización. Los experimentos evalúan el impacto de utilizar estrategias de lot-streaming en este tipo de problemas. Los resultados permitieron demostrar que el lot-streaming es una estrategia eficiente a la hora de resolver este problema, permitiendo mejorar tanto el makespan como el consumo energético total con respecto al problema sin lot-streaming. A su vez, se incorporó la selección de velocidades de procesamiento para cada sublote, lo que mejoró la estrategia.

ABSTRACT. In this contribution, a novel framework for the Shop-floor Scheduling Nervousness (SN) is presented. The SN is defined as an evolving state associated to an on-going schedule domain. The approach is suitable to be instantiated within industry 4.0 manufacturing environments.

ABSTRACT. This paper addresses the problem of developing an ontology for manufacturing process capability. This is important in order to achieve the semantical integration of various manufacturing planning and execution software and hardware (equip-ment) systems. The reported research has been performed within a framework of Industrial Ontology Foundry (IOF) in which the authors are active participants. Manufacturing process capability is seen as a composition or combination of ca-pabilities and functions of resources participating in the process. Theoretical foundation for the capability composition is presented. Individual participant re-source functions are established based on axiomatic design. The function and ca-pability of the whole manufacturing processes is derived from individual re-sources using axiomatic design composition of functions. The overall approach is applied on example of prismatic parts, their features, and machining processes. For each machining process, machine tool brings one set of functions, while the cutting tool (mill or drill) bring its own functions. When assembled together for the manufacturing process those functions become capabilities in the whole pro-cess. The approach is illustrated on several feature geometries (holes, slots and pockets)

ABSTRACT. A Indústria 4.0 pode ser entendida como um novo estágio industrial e, atualmente, se trata de um dos tópicos mais populares nos campos profissional e acadêmico. Este conceito tem o smart manufacturing como seu elemento central. Espera-se que a Indústria 4.0 tenha um impacto significativo na cadeia de suprimentos, no modelo de negócios e processos. No entanto, a adoção de tecnologias avançadas para os países emergentes pode ser mais desafiadora. Os países emergentes têm sua economia mais direcionada à extração e comercialização de commodities, suas empresas estão frequentemente atrás em termos tecnológicos quando comparadas com seus similares nos países desenvolvidos. Diante deste contexto, este artigo analisa primeiro os requisitos específicos dos países emergentes antes de realizar uma revisão abrangente da literatura sobre os modelos de maturidade disponíveis atualmente para Indústria 4.0. Em seguida, ele discute os modelos de maturidade em relação à sua "adequação" aos requisitos específicos das economias emergentes. No processo, determina-se e discute as lacunas da pesquisa e, finalmente, propõe-se uma possível via para resolvê-las, criando ou adaptando um modelo de maturidade dedicado para as economias emergentes ou adaptando algum dos modelos existentes. Como forma de validação a abordagem será testada em uma empresa do ramo do alumínio.