Dissertações

URI permanente para esta coleçãohttps://rigalileo.itegam.org.br/handle/123456789/174

Dissertações produzidas oriundas de convênios

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2011 - 20152

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Tem arquivos: SimAssunto: search.filters.subject.Processos industriais

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Agora exibindo 1 - 2 de 2
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    UTILIZAÇÃO DO MÉTODO 10 M’s PARA DIAGNÓSTICAR PONTOS CRÍTICOS EM PROCESSOS INDUSTRIAIS
    (Universidade Federal do Pará, 2015) OLIVEIRA, Rosimeire Freires Pereira; LEITE, Jandecy Cabral
    The research presents the application of the 10 M’s method to diagnose critical points in industrial processes, aiming to assist in continuous improvement and organizational competitiveness. The study was conducted in a company from the Manaus Industrial Pole (PIM), using questionnaires, interviews, direct observation, and data collection. The results indicated that the critical areas were concentrated in management (Management) and methods, specifically in decision-making processes and flowcharts. The application of the method allowed the identification of strengths, weaknesses, and areas for improvement, enabling the development of an action plan to address the identified issues.
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    SIMULAÇÃO COMPUTACIONAL NO AUXÍLIO À TOMADA DE DECISÃO NOS PROCESSOS INDUSTRIAIS: UTILIZANDO A FERRAMENTA TECNOMATIX PLANT SIMULATION 9.0
    (Universidade Federal do Pará, 2011) SANTOS, Eliton Smith dos; QUARESMA, João Nazareno Nonato
    Currently, there are numerous automated production processes that are becoming increasingly complex due to the demands of the modern world. These processes require increasingly powerful engineering tools for efficient modeling and analysis. In this context, the computational tool Tecnomatix Plant Simulation 9.0 emerges as a means of optimizing industrial production. This study presents the application of this tool in modeling and simulating a production line, highlighting its relevance for production management by reducing costs and maximizing profits. The approach is demonstrated through a case study in the electronics industry, analyzing process efficiency and proposing improvements for time and resource optimization.