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Manufacturing systems are subject to continuous changing conditions, which are due both to external reasons (e.g. changing demand) and to the natural system evolution, (e.g. machine degradation, operators’ upskilling). At tactical level, production engineers are challenged to continuously improve the system performance. At strategical level, the manufacturing company must monitor the system status and proactively identify reconfiguration actions to ensure system fitness to the evolving competitive scenario. A novel Digital Twin based on an analytical model for performance evaluation of manufacturing system embedding evaluation of joint parameter variations is introduced. In particular this work concentrates on how tactical decision makers can benefit from an integrated system model. The method is proved in a real industrial case in the railway sector.

Asynchronous systems with deterministic processing times are critical for fabricating discrete parts, especially in countries offering high salaries. Despite their widespread application, it is difficult to analyze these systems using conventional analytical modeling tools as commonly used hypotheses for these models consider different conditions compared to real behaviors. This paper presents a new analytical model for the performance evaluation of asynchronous two-stage manufacturing lines fabricating discrete parts with finite buffer capacity. A continuous-time Markov chain flow model that mimics the behavior of discrete asynchronous manufacturing systems by employing threshold-based control mechanisms is presented. The results obtained with the proposed model are compared with those using discrete event simulation, and they show good agreement. The model proposed in this paper can be used as a building block for the evaluation of longer asynchronous lines.

The paper proposes an energy consumption cross-level model for a demand driven machine tool working in a manufacturing system. The aim is to optimize performance of manufacturing system engaging more than one organizational level, in this case the machine and the system levels. The paper exploits a former study on Pareto optimal Minimum Energy-Time functions, representing the best possible machine setups under varying cycle-time. The functions are used to model machine productive states, whereas stochastic behaviours (failures, blocking, starvation) and inter-machine interactions are described using a Markovian General Threshold Model. Here, instead of using a constant power per machine state assumption, a functional relationship between processing rate and machine energy demand is used. A stand-by energy-saving policy, which exploits the flexibility in adopting a variable processing rate and a settable threshold level of the interoperational parts buffer as a trigger, is developed and benchmarked. The model is used to analyse an industrial case study of a three-station transfer machine. It takes into account a number of cost contributing factors, apart from sole energy demand, such as tooling cost, operator cost, inventory and costs related to potentially undelivered throughput. The application of the proposed cross-level optimization scheme to a case study showed an improvement both in energy-efficiency and in profitability of the production system under investigation. Moreover, it has been demonstrated that a model exploiting knowledge from both levels can avoid suboptimal setups resulting from treating single-level problems independently.

Sensors and human machine interfaces for collaborative robotics will allow smooth interaction in contexts ranging from industry to tele-medicine and rescue. This paper introduces a bidirectional communication system to achieve multisensory telepresence during the gestural control of an industrial robotic arm. Force and motion from the robot are converted in neuromorphic haptic stimuli delivered on the user's hand through a vibro-tactile glove. Untrained personnel participated in an experimental task benchmarking a pick-and-place operation. The robot end-effector was used to sequentially press six buttons, illuminated according to a random sequence, and comparing the tasks executed without and with tactile feedback. The results demonstrated the reliability of the hand tracking strategy developed for controlling the robotic arm, and the effectiveness of a neuronal spiking model for encoding hand displacement and exerted forces in order to promote a fluid embodiment of the haptic interface and control strategy. The main contribution of this paper is in presenting a robotic arm under gesture-based remote control with multisensory telepresence, demonstrating for the first time that a spiking haptic interface can be used to effectively deliver on the skin surface a sequence of stimuli emulating the neural code of the mechanoreceptors beneath.

Background: Ecologic studies support non-pharmacologic measures to protect against SARS-CoV-2, but few studies have evaluated their effects at the individual level in the community. We aimed to assess the magnitude of the associations of social distancing and mask use with laboratory-confirmed infection by SARS-CoV-2 in adults living in Porto Alegre, Brazil, a city with 1,483,771 inhabitants. Methods: We conducted a population-based case-control study from late April to June 2020. Cases came from a list of all cases mandatorily notified to municipal authorities; controls were antibody-negative participants of three representative household surveys conducted at the same time-period. Findings: In logistic regression analyses of 271 cases and 1396 controls adjusted for age, sex, race, educational attainment, income, household size and pandemic moment, those reporting moderate to greatest adherence to social distancing had between 59% (OR=0·41; 95%CI 0·24-0·70) and 75% (OR=0·25; 0·15-0·42) lower odds of becoming infected, compared to those reporting very little adherence. Lesser out-of-household exposure reduced odds between 52% (OR=0·48; 0·29-0·77) and 75% (OR=0·25; 0·18-0·36), compared to going out every day all day. In a subsample of controls with data on mask use and cases of equivalent pandemic moment (198 cases and 420 controls), mask use reduced odds of infection by 87% (OR=0·13; 0·04-0·36). Interpretation: Greater social distancing and always using masks while away from home provided major protection against SARS-CoV-2. These simple measures can be of great benefit during the upcoming phases of the pandemic. Funding: IATS/FAPERGS, UNIMED Porto Alegre, Instituto Cultural Floresta, Instituto Serrapilheira, Ministry of Health. Declaration of Interests: The authors have no conflicts of interest to declare. Ethics Approval Statement: The ethics committee of the Hospital de Clinicas de Porto Alegre approved our study (No. 31499420·5·0000·5327) and the Brazilian National Ethics Committee (No. 30415520·2·0000·5313) approved the accompanying seroprevalence surveys. All participants gave prior informed consent, in written form by the controls and verbally for cases.

LoRa networks have been gaining ground as a solution for Internet of Things because of their potential ability to handle massive number of devices. One of the most challenging problems of such networks is the need to set the Spreading Factors (SF) used by the terminals as close to a uniform distribution as possible, to guarantee reliable transmission of packets. This can be tackled through stochastic allocations based on centralized strategies, and more recently some contributions proposed fully distributed approaches based on game theory. However, these studies still consider games of complete information, where users have full knowledge on each other payoffs. In reality, it would be more appropriate to extend these approaches to Bayesian games, as we propose to do here. More precisely, we extend the game theoretic formulation to a semi-supervised allocation, where the distributed character of the allocation is retained as the nodes still act independently in choosing their SF, based on what they think it is their best preferred choice. We also utilize the central gateway as a coordinator regulating these proposals and the interaction of the nodes with the coordinator is framed as a Bayesian entry game, where nodes exploit a prior to decide whether to join the proposed allocation or not. Under this framework, nodes reach a satisfactory compromise between the assignment they receive from the network and their desired rate.

This special issue of Flexible Services and Manufacturing is an outgrowth of the 11th InternationalConference held in Acaya, Italy sponsored by the organization Stochastic Models of Manufacturingand Service Operations (SMMSO). These international conferences gather together knowledgeableindividuals from all over the world every two years to communicate and share ideas. The conferences havebeen ongoing since 1997.The main purpose of this special issue is to present innovative results of stochastic models of Manufacturing and Service System operations united by common methodologies and problems. Service systems(non-manufacturing) papers in this volume demonstrate that their operations are strongly related tomanufacturing system operations and methodologies.

In sectors as semiconductor fabrication, pharma industry and food production, discrete production processes are intertwined with continuous production processes. Since continuous processes frequently produce large batches of material requiring fairly long processing times, restart policies aiming at scrap reduction especially due to work-in-progress perishability are commonly used to control the material flow in multi-stage production systems. A performance evaluation model integrating control mechanisms is proposed to assess the impact of local restart policies at system level. A real case study in the food production is presented, where the parameters of restart policies are optimized to maximize production quality.

Objetiva-se neste artigo compreender como é percebido, pelas famílias cooperadas, o incentivo da Cooperativa Agropecuária de Patrocínio – COOPA/MG sobre os processos sucessórios nas propriedades de seus cooperados e o envolvimento familiar e juvenil nas atividades da instituição. A pesquisa apresenta metodologia de cunho qualitativo do tipo exploratória. A coleta de dados foi realizada por meio de aplicação de questionários junto a 41 Famílias cooperadas. Ficou clara a importância da organização cooperativa para o desenvolvimento das atividades nas unidades familiares de produção e o importante envolvimento de toda a família nas atividades desenvolvidas pela cooperativa. No entanto, as Famílias cooperadas não percebem, por parte da cooperativa, ações de envolvimento direto relacionadas aos processos sucessórios.

O objetivo deste estudo foi identificar os fatores de risco para o baixo peso ao nascer (BPN) de gestacoes unicas, por meio da regressao logistica com desfecho binario, utilizando dados do SINASC do RS no ano de 2008. A populacao do estudo foi de 131.736 nascidos vivos (NV) apos correcoes. Utilizou-se a regressao logistica multipla com nivel de significância de 5%. A analise dos dados foi realizada utilizando-se o aplicativo computacional PASW 17.0. No RS, em 2008, 8,1% dos recem-nascidos apresentaram BPN. Foram identificados os fatores de risco significativos para o BPN de maes: nuliparas (OR=1,41); com idade materna maior ou igual a 35 anos (OR=1,40); com escolaridade de 0 a 3 anos (OR=1,67) e maes com escolaridade de 4 a 11 anos (OR=1,20), maes que nao possuiam uniao estavel (OR=1,11); maes que nao realizaram nenhuma consulta pre-natal (OR=3,48); que realizaram de 1 a 6 consultas pre-natais (OR=1,74) e NV que nasceram fora do hospital (OR=2,05); prematuros (OR=31,43); do sexo feminino (OR=1,45) e com anomalia genetica (OR=2,42). A prematuridade foi o principal fator de risco para a ocorrencia de BPN, seguido do numero de consultas pre-natais mostrando a importância de a mae ter um acompanhamento com qualidade durante a gestacao .

The paper proposes an energy consumption oriented optimization scheme for a demand driven machine tool working in a system context. The aim is optimize performance of manufacturing system engaging more than one organizational level, in this case the machine and the system levels. The paper exploits a former study on Pareto optimal Minimum Energy-Time functions, representing the best possible machine setups under varying cycle-time. The functions are used to model the productive state of the machine, whereas stochastic behaviours (failures, blocking, starvation) and inter-machine interaction are described using a Markovian General Threshold Model. Additionally, instead of using a constant power per machine state assumption, a functional relationship between processing rate and machine demand is used. A stand-by energy-saving policy, which exploits the flexibility in adopting a variable processing rate and a settable threshold level of the interoperational parts buffer as a trigger, is developed and benchmarked. The model is used to analyse an industrial case study of a three-station transfer machine. The study takes into account a number of cost contributing factors, apart from sole energy demand, such as tooling cost, operator cost, inventory and costs related to potentially undelivered throughput. The application of the proposed cross-level optimization scheme showed an improvement both in energy-efficiency and in profitability of the production system under investigation.

Human workers have a vital role in manufacturing given their adaptability to varying environmental conditions, their capability of judgment and understanding of the context. Nevertheless, the increasing complexity and variety of manufacturing operations ask for the exploitation of digital technologies to support human workers and/or facilitate their interaction with automation equipment. The proposed approach uses artificial intelligence for image processing to identify the actions of the workers and exploits the knowledge related to the processes through hidden-Markov models to identify possible errors, deviations from the planned execution or dangerous situations. An application case is provided for assembly operations to assess the viability of the proposed approach in realistic conditions.

Mission-oriented policies have been proposed for research and innovation in the European manufacturing industry to address grand challenges while fostering economic growth and employment. A mission is required to have clear goals that can be demonstrated also to a wide public, therefore research and innovation infrastructures play a key role to create the necessary conditions. Given the fundamental importance of public investment to promote innovation, possible funding mechanisms for industrial research and innovation are discussed. Furthermore, taking advantage of the experience gained during the Italian Flagship Project Factories of the Future, this chapter identifies three types of industrial research and innovation infrastructure that can support mission-oriented policies: lab-scale pilot plants, industrial-scale pilot plants, and lighthouse plants.

This book presents results relevant in the manufacturing research field, that are mainly aimed at closing the gap between the academic investigation and the industrial application, in collaboration with manufacturing companies. Several hardware and software prototypes represent the key outcome of the scientific contributions that can be grouped into five main areas, representing different perspectives of the factory domain: 1) Evolutionary and reconfigurable factories to cope with dynamic production contexts characterized by evolving demand and technologies, products and processes. 2) Factories for sustainable production, asking for energy efficiency, low environmental impact products and processes, new de-production logics, sustainable logistics. 3) Factories for the People who need new kinds of interactions between production processes, machines, and human beings to offer a more comfortable and stimulating working environment. 4) Factories for customized products that will be more and more tailored to the final user's needs and sold at cost-effective prices. 5) High performance factories to yield the due production while minimizing the inefficiencies caused by failures, management problems, maintenance.This books is primarily targeted to academic researchers and industrial practitioners in the manufacturing domain.

Manufacturing plays a key role both in advanced economies and developing countries because of the large contribution to the overall employment, value added, gross domestic product (GDP) and social welfare. Manufacturing is also a pillar for the tertiary sector, since manufacturing activities generate the need for services and in turn manufacturing provides products and technologies for the operation of the service sector. Furthermore, manufacturing is fundamental to guarantee national independence and security and to design the future of our societies. Continuously evolving grand challenges compel the manufacturing sector to innovate its processes, technologies and business models to continue sustaining the national economies and progress.

Research on bidirectional human-machine interfaces will enable the smooth interaction with robotic platforms in contexts ranging from industry to tele-medicine and rescue. This paper introduces a bidirectional communication system to achieve multisensory telepresence during the gestural control of an industrial robotic arm. We complement the gesture-based control by means of a tactile-feedback strategy grounding on a spiking artificial neuron model. Force and motion from the robot are converted in neuromorphic haptic stimuli delivered on the user’s hand through a vibro-tactile glove. Untrained personnel participated in an experimental task benchmarking a pick-and-place operation. The robot end-effector was used to sequentially press six buttons, illuminated according to a random sequence, and comparing the tasks executed without and with tactile feedback. The results demonstrated the reliability of the hand tracking strategy developed for controlling the robotic arm, and the effectiveness of a neuronal spiking model for encoding hand displacement and exerted forces in order to promote a fluid embodiment of the haptic interface and control strategy. The main contribution of this paper is in presenting a robotic arm under gesture-based remote control with multisensory telepresence, demonstrating for the first time that a spiking haptic interface can be used to effectively deliver on the skin surface a sequence of stimuli emulating the neural code of the mechanoreceptors beneath.

Submitted by MARCIA ROVADOSCHI (marciar@unifra.br) on 2018-08-22T12:07:03Z No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_PricilaTolioMuller.pdf: 1581572 bytes, checksum: 2ee45bab6500d240c98b9a12ad2e330d (MD5) Made available in DSpace on 2018-08-22T12:07:03Z (GMT). No. of bitstreams: 2 license_rdf: 0 bytes, checksum: d41d8cd98f00b204e9800998ecf8427e (MD5) Dissertacao_PricilaTolioMuller.pdf: 1581572 bytes, checksum: 2ee45bab6500d240c98b9a12ad2e330d (MD5) Previous issue date: 2018-04-20 Epilepsy is characterized by a cerebral disorder with interruptions, recurrent and unpredictable of normal brain function. Glutamate is the major excitatory neurotransmitter in the brain and is involved in the mechanism of status epilepticus - a prolonged and self-sustaining seizure. The drug N-methyl-D-aspartate (NMDA) is a synthetic excitotoxin that acts as a specific agonist for the NMDA receptor subtype of glutamate. Pre- and post-conditioning strategies provide a proposal for molecular mechanisms responsible for endogenous neuronal protection. The aim of the study is evaluating the effect of NMDA in different doses against damage following status epilepticus induced by pilocarpine in animal model of epilepsy. For this purpose, 210 adult male mice (60 days, 30-40 g) Swiss albino were treated intraperitoneally with pilocarpine (100 mg/kg every 20 min up to a maximum of 300 mg/kg) evoking status epilepticus. All animals were exposed to behavioral tasks for motor evaluation (locomotion, balance, motor coordination) and memory, followed by evaluation of cellular viability at 30 days post-pilocarpine. The pilocarpine death in approximately 40% of the mice during 24 hours. Treatment with lower doses of NMDA (18 mg/kg) prolonged survival time without change the outcome. The other NMDA doses also had no significant effect on the number of deaths. The status epilepticus caused reduction of the locomotor activity of the mice, an effect reversed by treatment with NMDA 37 mg/kg. The pilocarpine group mice did not show expressive cognitive deficit during acquisition of memory, however reduced evocation. Cellular viability assessed 30 days after status epilepticus indicated damage by MTT test, but not by propidium iodide. Only the 18 mg/kg NMDA reduced damage. It is concluded that the dose 18 mg/kg NMDA induced neuroprotection in surviving animals. The cellular mechanisms of NMDA-induced tolerance remain unknown, but the present study reinforces the dual NMDA effect, since the same dose that increased the mortality rate was able to reduce cellular damage. A epilepsia é caracterizada por uma desordem cerebral com interrupções, recorrentes e imprevisíveis da função cerebral normal. O glutamato é o principal neurotransmissor excitatório no cérebro e está envolvido no mecanismo de status epilepticus - estado de mal epiléptico, convulsões espontâneas. O fármaco N-metil-D-aspartato (NMDA) é uma excitotoxina sintética que age como agonista específico do subtipo de receptor NMDA do glutamato. As estratégias de pré- e pós-condicionamento fornecem uma nova proposta de mecanismos moleculares responsáveis pela proteção neuronal endógena. Diante do exposto, neste trabalho avaliamos o efeito do NMDA em diferentes doses contra danos decorrentes do status epilepticus induzido por pilocarpina em modelo animal de epilepsia. Para tal, foram utilizados 210 camundongos machos adultos (60 dias, 30-40g) da linhagem albino Swiss que foram tratados pela via intraperitoneal com pilocarpina (100 mg/kg a cada 20 min até o máximo de 300 mg/kg) para a indução do status epilepticus. Todos os animais foram submetidos a tarefas comportamentais para avaliação motora (locomoção, equilíbrio, coordenação motora) e memória, seguidas de avaliação de viabilidade celular em 30 dias pós-pilocarpina. O modelo de epilepsia induzido por pilocarpina induziu morte de aproximadamente 40% dos animais em 24 horas. O tratamento com a menor doses de NMDA (18 mg/kg) aumentou o período de sobrevivência dos animais, mas não modificou o desfecho. As demais doses de NMDA também não tiveram efeito significativo no número total de mortes. O status epilepticus causou redução da atividade locomotora dos camundongos, efeito revertido pelo tratamento com NMDA 37 mg/kg. O grupo pilocarpina não demonstrou expressivo déficit cognitivo na aquisição da memória, mas sim na evocação. A avaliação tardia, aos 30 dias, da viabilidade celular indicou efeito danoso da pilocarpina no teste do MTT, com proteção significativa de NMDA 18 mg/kg. Conclui-se que o NMDA na dose de 18 mg/kg nos animais sobreviventes induziu neuroproteção. Os mecanismos celulares da tolerância induzida por NMDA permanecem desconhecidos, mas o presente estudo reforça a função dual do NMDA, pois a mesma dose que aumentou a taxa de mortalidade foi capaz de reduzir o dano celular.

Co-creating integrated solutions with customers requires collaboration of different partners within a value network. In this emerging context, knowledge is considered as a foundation for value co-creation. Therefore, identifying different types of issues, with which value network actors in knowledge transfer are confronted, is conceived as a first step toward, on the one hand, the prevention of the failure of knowledge exchange initiatives in a network, and on the other hand, the enhancement of the collaborative process of knowledge sharing. This requires shifting the conventional approach on knowledge transfer issues from an intra-organizational to an inter-organizational network. This paper aims to systematically identify and classify knowledge transfer issues with both tacit and explicit knowledge considerations. In doing so, we have first conducted a systematic literature review to identify issues. Secondly, these issues have been classified into six main categories and 29 subcategories through a structured classification approach. The proposed classification framework provides a comprehensive and wide spectrum of possible issues related to knowledge transfer within a value network. It also presents a step towards an improved awareness of such issues in order to resolve problems in transferring knowledge in such contexts.