Publicação
Estudo do Indicador Overall Equipment Effectiveness na Indústria de Semicondutores
| Resumo: | The semiconductor industry involves lengthy and complex manufacturing processes that require expensive equipment. Therefore, it is of paramount importance to monitor equipment efficiency since competitive advantages in this business sector can only be achieved through the reduction of efficiency losses, a decrease in process cycle times, and meeting established delivery deadlines. This dissertation was carried out as part of the curricular internship conducted at Amkor Technology Portugal, with the objective of studying the Overall Equipment Effectiveness of a series of equipment integrated into the semiconductor manufacturing process, presenting, and interpreting the results of the equipment's OEE based on the developed model, and constructing a dashboard to facilitate the perception of the three components and the OEE. The study of this indicator began with an understanding of how the equipment operates, given that they possess certain characteristics to consider, such as the existence of subsystems within the equipment, the production of different recipes with varying cycle times and complexities, non-sequential production within the equipment, and the presence of multiple steps within the same equipment. In this way, an analysis of data from the company's database was conducted with the aim of building a model that considers the characteristics of the equipment under study, capable of calculating Availability, Performance, Quality, and consequently, OEE, to measure and quantify equipment efficiency. After the construction of the model, it became possible to present and interpret the results provided by the model, rectify the previously used OEE values within the company, and create a dashboard, developed using Microsoft Power BI. This dashboard thereby offers visual support for essential elements in decision-making and the achievement of all initially defined objectives. |
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| Autores principais: | Fonseca, Hugo Jose Campinho |
| Assunto: | Semiconductor Industry Data Analysis Overall Equipment Effectiveness Efficiency Losses Indústria de Semicondutores Análise de Dados Overall Equipment Effectiveness Perdas de Eficiência |
| Ano: | 2023 |
| País: | Portugal |
| Tipo de documento: | dissertação de mestrado |
| Tipo de acesso: | acesso aberto |
| Instituição associada: | Universidade de Coimbra |
| Idioma: | português |
| Origem: | Estudo Geral - Universidade de Coimbra |
| Resumo: | The semiconductor industry involves lengthy and complex manufacturing processes that require expensive equipment. Therefore, it is of paramount importance to monitor equipment efficiency since competitive advantages in this business sector can only be achieved through the reduction of efficiency losses, a decrease in process cycle times, and meeting established delivery deadlines. This dissertation was carried out as part of the curricular internship conducted at Amkor Technology Portugal, with the objective of studying the Overall Equipment Effectiveness of a series of equipment integrated into the semiconductor manufacturing process, presenting, and interpreting the results of the equipment's OEE based on the developed model, and constructing a dashboard to facilitate the perception of the three components and the OEE. The study of this indicator began with an understanding of how the equipment operates, given that they possess certain characteristics to consider, such as the existence of subsystems within the equipment, the production of different recipes with varying cycle times and complexities, non-sequential production within the equipment, and the presence of multiple steps within the same equipment. In this way, an analysis of data from the company's database was conducted with the aim of building a model that considers the characteristics of the equipment under study, capable of calculating Availability, Performance, Quality, and consequently, OEE, to measure and quantify equipment efficiency. After the construction of the model, it became possible to present and interpret the results provided by the model, rectify the previously used OEE values within the company, and create a dashboard, developed using Microsoft Power BI. This dashboard thereby offers visual support for essential elements in decision-making and the achievement of all initially defined objectives. |
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