Implementação de ações de melhoria contínua numa empresa de fabrico de produtos eletrónicos

O projeto desenvolvido teve como principal objetivo a implementação de ações de melhoria contínua numa empresa da indústria automóvel. A indústria automóvel insere-se num ambiente muito exigente e desenvolvido o que o torna, naturalmente, num ambiente muito competitivo. A crescente concorrência mundial e a revolução da tecnologia da informação acabaram por se tornar grandes desafios e, neste contexto, cada vez mais empresas e indivíduos veem a filosofia kaizen como sendo a solução. Esta filosofia implica melhoria contínua por todos, em todos os lugares e todos os dias. No sentido de melhorar o desempenho do setor produtivo da empresa onde foi desenvolvido este trabalho, foram propostas várias ações de melhoria contínua tais como: (i) a implementação de um sistema kanban para tornar mais ágil o processo de funcionamento da linha; (ii) uma alteração de layout com a criação de um armazenamento vertical para linhas que não trabalham de forma continuada; e (iii) um programa para facilitar a análise de defeitos de alguns produtos e consequentemente melhorar a qualidade dos mesmos. O presente relatório descreve essas ações e, quando possível, o impacto das mesmas no desempenho do sistema.

Characterization of the methanol recovery process at Prio Biocombustíveis S. A.

In a industrial environment, to know the process one is working with is crucial to ensure its good functioning. In the present work, developed at Prio Biocombustíveis S.A. facilities, using process data, collected during the present work, and historical process data, the methanol recovery process was characterized, having started with the characterization of key process streams. Based on the information retrieved from the stream characterization, Aspen Plus® process simulation software was used to replicate the process and perform a sensitivity analysis with the objective of accessing the relative importance of certain key process variables (reflux/feed ratio, reflux temperature, reboiler outlet temperature, methanol, glycerol and water feed compositions). The work proceeded with the application of a set of statistical tools, starting with the Principal Components Analysis (PCA) from which the interactions between process variables and their contribution to the process variability was studied. Next, the Design of Experiments (DoE) was used to acquire experimental data and, with it, create a model for the water amount in the distillate. However, the necessary conditions to perform this method were not met and so it was abandoned. The Multiple Linear Regression method (MLR) was then used with the available data, creating several empiric models for the water at distillate, the one with the highest fit having a R2 equal to 92.93% and AARD equal to 19.44%. Despite the AARD still being relatively high, the model is still adequate to make fast estimates of the distillate’s quality. As for fouling, its presence has been noticed many times during this work. Not being possible to directly measure the fouling, the reboiler inlet steam pressure was used as an indicator of the fouling growth and its growth variation with the amount of Used Cooking Oil incorporated in the whole process. Comparing the steam cost associated to the reboiler’s operation when fouling is low (1.5 bar of steam pressure) and when fouling is high (reboiler’s steam pressure of 3 bar), an increase of about 58% occurs when the fouling increases.