Estudo de caso sobre redes de precedência na indústria aeroespacial
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Data
2022-02-23
Autores
Guiachetto, Gabriel Baldin
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Editor
Universidade Estadual Paulista (Unesp)
Resumo
O seguinte estudo se dá dentro de uma das plantas de uma empresa do ramos aeroespacial, onde foi proposto o desenvolvimento de uma dashboard no software Power BI, com o intuito de atribuir a cada um dos centros de trabalho da empresa uma carga horária de trabalho e como essas cargas são passadas de um CT (centro de trabalho) para outro, mostrando assim as relações entre os mesmos. Os objetivos da dashboard são: encontrar gargalos na produção, avaliar impacto nas paradas de máquinas, mostrar refluxos de PNs (part numbers) nos CTs, permitindo ao planejamento da produção a tomada de decisões rápidas e precisas para o contorno de possíveis problemas. As colunas foram programadas utilizando a linguagem DAX (data analysis expressions) e testes na lógica foram feitos para comprovar a eficácia da mesma. Também foi desenvolvido um estudo de caso envolvendo a utilização da rede de precedência para descobrir refluxo (auto-alimentação) dos CTs fábrica, otimizar a sequência de operações de fabricação de um dos PNs da empresa era processado no CT 1400, melhorando o desempenho do centro de trabalho e também diminuindo o lead time do PN em 5,02 dias, de acordo com a cronoanálise realizada. Dessa forma, reduzindo custos, aumentando o desempenho dos processos e, consequentemente, a competitividade da empresa.
The following study takes place within one of the plants of an aerospace company, where the development of a dashboard in Power BI software was proposed, with the aim of assigning to each of the company's work centers a workload and how these charges are passed from one work center to another, thus showing the relationships between them. The objectives of the dashboard are: finding bottlenecks in production, evaluating the impact of machine stoppages, showing PN (part number) backflows in the work centers, allowing production planning to make quick and accurate decisions to overcome possible problems. Columns were programmed using the DAX (data analysis expressions) language and logic tests were made to prove its effectiveness. A case study was also developed involving the use of the precedence network to discover backflow (self-supply) of factory CTs (work centers), optimizing the sequence of manufacturing operations of one of the company's PNs that was processed in CT 1400, improving center performance and also reducing the PN lead time by 5.02 days, according to the time analysis. Thus, reducing costs, increasing process performance and, consequently, the company's competitiveness.
The following study takes place within one of the plants of an aerospace company, where the development of a dashboard in Power BI software was proposed, with the aim of assigning to each of the company's work centers a workload and how these charges are passed from one work center to another, thus showing the relationships between them. The objectives of the dashboard are: finding bottlenecks in production, evaluating the impact of machine stoppages, showing PN (part number) backflows in the work centers, allowing production planning to make quick and accurate decisions to overcome possible problems. Columns were programmed using the DAX (data analysis expressions) language and logic tests were made to prove its effectiveness. A case study was also developed involving the use of the precedence network to discover backflow (self-supply) of factory CTs (work centers), optimizing the sequence of manufacturing operations of one of the company's PNs that was processed in CT 1400, improving center performance and also reducing the PN lead time by 5.02 days, according to the time analysis. Thus, reducing costs, increasing process performance and, consequently, the company's competitiveness.
Descrição
Palavras-chave
Rede, Precedência, Produção, Otimização, Redução, Diagram, Precedence, Production, Optimization, Reduction, Indústria aeroespacial, Processo decisório, Sistema de informação gerencial