Using Industry 4.0 Tools for Increasing Competitiveness of Clusters in Western Paraná

Alves, Lucir Reinaldo; Andreica, Alina; Alcantara, Isabela Romanha de

doi:10.34117/bjdv6n8-179

Cited by 2 publications

(2 citation statements)

References 4 publications

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“…Large industrial hubs are also observed in this meso-region, such as the textile industry. In this sense, Campo Mourão is the municipality that most contributes to soybean and corn the other municipalities have characteristics of small rural properties (Alves et al, 2020).…”

Section: Forecasting Grain Production and Static Capacity Of Warehouses Using The Natural Neighbormentioning

confidence: 99%

Forecasting Grain Production and Static Capacity of Warehouses Using the Natural Neighbor and Multiquadric Equations

Cima

Rocha-Junior

Dalposso

et al. 2021

AOL

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The strategic logistics of agricultural production and storage aggregates information related to production and storage. In this sense, time, location, and distance from producer and consumer markets are considered, emphasizing the importance of grain storage and production logistics. The Natural Neighbor and multiquadric equation are spatial interpolation methods used to predict these variables value at non-sampled locations, for asymmetric and categorical data, respectively. This study investigated the spatial prediction of grain production (tons) (soybean, first crop corn, second-crop corn, and wheat) in the 2016/2017 growing season and qualitative data on the static capacity of warehouses in the 2017/2018 growing season. The result obtained through the spatial interpolation using the natural neighbor method was coherent, as it showed the high variability of grain production relative to the different meso-regions. Therefore, the method was appropriate because it allowed predicting the behavior of grain production in the 2016/2017 growing season in the state of Paraná-Brazil, making it possible to identify regions of higher or lower production. The result of the spatial interpolation using the multiquadric equations allowed identifying a higher predominance of storage units with a low static capacity of warehouses, but also enabled the detection of regions with a static capacity of warehouses that varied from the medium to the high category in the state of Paraná, Brazil.

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Section: Forecasting Grain Production and Static Capacity Of Warehouses Using The Natural Neighbormentioning

confidence: 99%

Forecasting Grain Production and Static Capacity of Warehouses Using the Natural Neighbor and Multiquadric Equations

Cima

Rocha-Junior

Dalposso

et al. 2021

AOL

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show abstract

“…Recently agricultural production has grown at significant annual rates. The locational indicators of economic growth reported lack clarity regarding the information they seek to explain, thus observing the need for greater knowledge in certain regions of the state of Paraná-Brazil (Alves et al, 2020). There is an increasing number of public policies and government programs (Federal and State) that value space and state initiatives (regions), because it is in these places that economic growth and development are triggered (Lima, 2020).…”

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confidence: 99%

Modelos Mistos Longitudinais Para O Valor Bruto Da Produção Agropecuária: Uma Apreciação Espacial E Regional No Estado Do Paraná-Brasil

Giron Cima,

Oliveira,

Rocha-Junior

et al. 2024

RBGDR

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Os modelos lineares mistos longitudinais são importantes por analisarem medições em frequências repetidas na evolução média no tempo. Neste trabalho foi realizada uma aplicação com modelos mistos longitudinais para investigar a relação entre o valor bruto da produção agropecuária expresso em reais associado às variáveis agropecuárias: quantidade de aves produzidas por cabeça, quantidade de suínos produzida por cabeça, quantidade de bovinos produzida por cabeça e produção de leite em mil litros produzida por municípios para os anos de 2018, 2019 e 2020 no estado do Paraná-Brasil. Os resultados mostraram que há um relacionamento entre a variável de interesse e as variáveis quantidades de aves produzidas por cabeça, quantidade de suínos e quantidade de bovino nos municípios que compõem o estado do Paraná estudada neste trabalho, e sendo possível identificar mesorregiões com as variáveis que explicam o valor bruto da produção agropecuária distintos para o modelo. Na análise de variância com os modelos, a variável produção de leite não foi significativa para explicar o valor bruto da produção agropecuária em cada ano, já as demais variáveis foram significativas ao nível de 5% de probabilidades. O modelo linear misto longitudinal forneceu informações necessárias sobre o relacionamento associado aos pesos que cada variável agropecuária forneceu no valor bruto da produção agropecuária que foi analisado no cenário econômico do estado do Paraná-Brasil.

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Using Industry 4.0 Tools for Increasing Competitiveness of Clusters in Western Paraná

Abstract: Using industry 4.0 tools for increasing competitiveness of Clusters in Western ParanáUsando ferramentas da indústria 4.0 para aumentar a competitividade dos Clusters no Oeste do Paraná

Cited by 2 publications

References 4 publications

Forecasting Grain Production and Static Capacity of Warehouses Using the Natural Neighbor and Multiquadric Equations

Forecasting Grain Production and Static Capacity of Warehouses Using the Natural Neighbor and Multiquadric Equations

Modelos Mistos Longitudinais Para O Valor Bruto Da Produção Agropecuária: Uma Apreciação Espacial E Regional No Estado Do Paraná-Brasil

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