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Presentation . 2023
License: CC BY
Data sources: Datacite
ZENODO
Presentation . 2023
License: CC BY
Data sources: Datacite
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Indústria 4.0 e Lean Manufacturing

Authors: Brandl, Edenilson;

Indústria 4.0 e Lean Manufacturing

Abstract

Na integração da Indústria 4.0 com os princípios Lean Manufacturing, é fundamental adotar uma abordagem estratégica e holística. Primeiramente, é crucial compreender a interligação dos objetivos de eficiência entre essas duas metodologias, reconhecendo que ambas visam eliminar desperdícios e otimizar processos. Ao alinhar esses objetivos, é essencial envolver os funcionários e gerenciar eficazmente as mudanças organizacionais, criando uma cultura de melhoria contínua. Identificar os processos-chave para digitalização e melhoria Lean é o próximo passo, permitindo a implementação de tecnologias como IoT e sensores para monitoramento em tempo real, bem como o uso de Big Data e análise preditiva para aprimorar processos operacionais. Investir em treinamento e desenvolvimento de habilidades digitais dos funcionários é crucial para capacitar a equipe a utilizar as tecnologias emergentes. Além disso, integrar robótica e automação colaborativa com os princípios Lean pode resultar em eficiência aprimorada. Finalmente, uma avaliação contínua dos resultados e uma adaptação constante das estratégias são necessárias para garantir o sucesso a longo prazo dessa integração, promovendo a excelência operacional e a competitividade no cenário industrial moderno.

Keywords

Treinamento de Habilidades Digitais, Automatização Colaborativa, Indústria 4.0, Avaliação Contínua, Cultura de Melhoria Contínua, Tecnologias Emergentes, Lean Manufacturing, Análise Preditiva, Integração de Processos, Eficiência Operacional

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average