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Intelligent Manufacturing Systems in COVID-19 Pandemic and Beyond: Framework and Impact Assessment

ABSTRACT: Pandemics like COVID-19 have created a spreading and ever-higher healthy threat to the humans in the manufacturing system which incurs severe disruptions and complex issues to industrial networks. The intelligent manufacturing (IM) systems are promising to create a safe working environment by using the automated manufacturing assets which are monitored by the networked sensors and controlled by the intelligent decision-making algorithms. The relief of the production disruption by IM technologies facilitates the reconnection of the good and service flows in the network, which mitigates the severity of industrial chain disruption. In this study, we create a novel intelligent manufacturing framework for the production recovery under the pandemic and build an assessment model to evaluate the impacts of the IM technologies on industrial networks. Considering the constraints of the IM resources, we formulate an optimization model to schedule the allocation of IM resources according to the mutual market demands and the severity of the pandemic.

SUBMITTER: Li X

PROVIDER: S-EPMC7453363 | biostudies-literature | 2020 Jan

REPOSITORIES: biostudies-literature

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Project description:ContextThe COVID-19 pandemic has affected all sectors and human activities around the World.ObjectiveIn this article we present a first attempt to understand the immediate impact of COVID-19 and the sanitary measures taken by governments on farming systems in Central America and Mexico (CAM).MethodsThrough a review of information generated in these initial months of the COVID-19 pandemic (webinars, blogs, electronic publications, media) and 44 interviews with key informants across the region, we have identified the main impacts felt by different types of farming systems in the region.Results and conclusionsFrom corporate agricultural production systems, to small and medium scale entrepreneurs and smallholder subsistence farm households, all types of farming systems were impacted, more or less severely, by the different measures implemented by governments such as reduced mobility, closure of public and private venues and restrictions in borders. Larger corporate farming systems with vertical market integration and high level of control or coordination within the supply chain, and smallholder or subsistence farming systems with important focus on production for self-consumption and little external input use, were both relatively less impacted and showed greater adaptive capacity than the medium and small entrepreneurial farming systems dependent on agriculture as their primary income and with less control over the upstream and downstream parts of their supply chain. All types of farming systems implemented a series of mechanisms to cope with the COVID-19 pandemic including the development of alternative value chains, food and agricultural products delivery systems and the exponential use of digital means to communicate and maintain the viability of the different agricultural systems. Collective action and organization of farmers also proved to be an important coping mechanism that allowed some farmers to acquire inputs and deliver outputs in the context of restricted mobility, price volatility, and general uncertainty. Some features of the CAM region played an important role in mediating the impact of COVID-19 and associated sanitary measures. We identify as particularly relevant the nature of agricultural exports, the current structure of the agricultural sector, the diversified livelihood strategies of rural households, and the importance of mobility for rural livelihoods.SignificanceThe results presented focus only in the immediate effect of COVID-19 pandemic and the mechanisms implemented by farmers in the first months. Whether these impacts and response mechanisms will result in a transformation of the farming systems towards greater resilience and sustainability is still an open question.

Project description:Aims and objectivesThis study aimed to examine the psychosocial impact and identify risk factors for poor psychosocial outcomes in healthcare professionals during the Coronavirus disease 2019 (COVID-19) pandemic in Cyprus.BackgroundHealthcare professionals are in the forefront of the COVID-19 pandemic facing an unprecedented global health crisis, which can have consequences on their psychosocial health. There is a need to identify risk factors for poor psychosocial outcomes to inform the design of tailored psychological interventions.DesignCross-sectional online study.MethodsA total of 1071 healthcare professionals completed self-report questionnaires. Measures included sociodemographic information, COVID-19-related characteristics, quality of life (Brief World Health Organization Quality of Life; WHOQOL-Bref), anxiety (Generalized Anxiety Disorder-7; GAD-7), depression (Patient Health Questionnaire-8; PHQ-8), occupational burnout (Copenhagen Burnout Inventory; CBI), and coping (Brief Coping Orientation to Problems Experienced; Brief COPE). This article follows the STROBE reporting guidelines.ResultsThe prevalence of moderate to severe anxiety and clinically significant depression was 27.6% and 26.8%, respectively. Significant risk factors for poor psychological outcomes included being female, being a nurse or doctor (vs non-medical professional), working in frontline units (inpatient, intensive care), perceptions of inadequate workplace preparation to deal with the pandemic, and using avoidance coping. Depression and occupational burnout were significant risk factors for poor quality of life.ConclusionThe findings suggest several individual, psychosocial, and organisational risk factors for the adverse psychological outcomes observed in healthcare professionals during the COVID-19 pandemic.Relevance to clinical practiceThis study highlights the urgent need for screening for anxiety and depression and psychological interventions to combat an imminent mental health crisis in healthcare professionals during the COVID-19 pandemic. Pandemic response protocols and public health initiatives aiming to improve and prevent mental health problems in healthcare professionals during the current and future health crises, need to account for the various factors at play.

Project description:While emerging technology for self-driving automation in vehicles progresses rapidly, the transition to an era of roads full of fully connected and automated vehicles (CAVs) may take longer than expected. Until then, it is inevitable that CAVs should coexist and interact with drivers of non-autonomous vehicles (NAVs) in urban roads. During this period of transition, it is critical to provide road safety with the mixed vehicular traffic and uncertainty caused by human drivers. To investigate the issues caused by the coexistence and interaction with humans, we propose to build a component-based and interactive intelligent transportation cyber-physical systems (ITCPS) framework. Our design of the interactive ITCPS framework aims to provide a standardized structure for users by defining core components. The framework is specified by behavior models and interfaces for the desired ITCPS components and is implemented as a form of human and hardware-in-the-loop system. We developed an intersection crossing assistance service and an automatic emergency braking service as an example of practical applications using the framework. To evaluate the framework, we tested its performance to show how effectively it operates while supporting real-time processing. The results indicate that it satisfies the timing requirements of vehicle-to-vehicle (V2V) communication and the limited processing time required for performing the functions of behavior models, even though the traffic volume reaches the road capacity. A case study using statistical analysis is conducted to assess the practical value of the developed experimental environment. The results of the case study validate the reliability among the specified variables for the experiments involving human drivers. It has shown that V2V communication support has positive effects on road safety, including intersection safety, braking events, and perception-reaction time (PRT) of the drivers. Furthermore, V2V communication support and PRT are identified as the important indicators affecting road safety at an un-signalized intersection. The proposed interactive framework is expected to contribute in constructing a comprehensive environment for the urban ITCPS and providing experimental support for the analysis of human behavior in the coexistence environment.

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Intelligent Manufacturing Systems in COVID-19 Pandemic and Beyond: Framework and Impact Assessment

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