Balanceamento de linhas de montagem e aplicação de ferramentas Lean no contexto da Polisport

Cada vez mais, nos dias que correm, está presente em todas as organizações a metodologia lean, que assenta numa base de melhoria contínua, de forma a responder às necessidades do mercado e à satisfação do cliente, tendo como principal finalidade a criação de valor para o produto e a eliminação de desperdícios inerente aos processos de produção do mesmo. Um elemento essencial na gestão de qualquer organização com ênfase nos resultados é o uso de indicadores de desempenho no processo de tomada de decisão. Este projeto teve como objetivo principal a identificação e eliminação de desperdícios, melhorando os processos de montagem, através do estudo dos tempos de ciclo dos centros de trabalhos/produtos mais críticos, procedendo a um balanceamento adequado e posterior simulação dos resultados através do software Arena. Posteriormente foram analisados os resultados assim como o impacto que essas mudanças causaram na empresa, com base na implementação de ferramentas de melhoria, nomeadamente ferramentas lean. Essas mudanças tiveram um impacto positivo na produção final das cadeiras e dos porta-bebés, no que diz respeito à diminuição de filas de espera entre postos, diminuição dos tempos de processamento e aumento da produção para alguns dos modelos em estudo.

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.