32 resultados para Lean Methodology
em Universidade do Minho
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Companies from the motorcycles components branch are dealing with a dynamic environment, resulting from the introduction of new products and the increase of market demand. This dynamic environment requires frequent changes in production lines and requires flexibility in the processes, which can cause reductions in the level of quality and productivity. This paper presents a Lean Six Sigma improvement project performed in a production line of the company's machining sector, in order to eliminate losses that cause low productivity, affecting the fulfillment of the production plan and customer satisfaction. The use of Lean methodology following the DMAIC stages allowed analyzing the factors that influence the line productivity loss. The major problems and causes that contribute to a reduction on productivity and that were identified in this study are the lack of standardization in the setup activities and the excessive stoppages for adjustment of the processes that caused an increase of defects. Control charts, Pareto analysis and cause-and-effect diagrams were used to analyze the problem. On the improvement stage, the changes were based on the reconfiguration of the line layout as well as the modernization of the process. Overall, the project justified an investment in new equipment, the defective product units were reduced by 84% and an increase of 29% of line capacity was noticed.
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Dissertação de mestrado em Engenharia Industrial
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Dissertação de mestrado em Engenharia Industrial
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Dissertação de mestrado em Engenharia Mecatrónica (área de especialização de Tecnologia de Manufatura)
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Dissertação de mestrado integrado em Engenharia e Gestão Industrial
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Dissertação de mestrado integrado em Engenharia e Gestão Industrial
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Dissertação de mestrado integrado em Engenharia e Gestão Industrial
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Dissertação de mestrado integrado em Engenharia e Gestão Industrial
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Dissertação de mestrado em Engenharia e Gestão da Qualidade
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Dissertação de mestrado integrado em Engenharia Industrial
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Hospitals are nowadays collecting vast amounts of data related with patient records. All this data hold valuable knowledge that can be used to improve hospital decision making. Data mining techniques aim precisely at the extraction of useful knowledge from raw data. This work describes an implementation of a medical data mining project approach based on the CRISP-DM methodology. Recent real-world data, from 2000 to 2013, were collected from a Portuguese hospital and related with inpatient hospitalization. The goal was to predict generic hospital Length Of Stay based on indicators that are commonly available at the hospitalization process (e.g., gender, age, episode type, medical specialty). At the data preparation stage, the data were cleaned and variables were selected and transformed, leading to 14 inputs. Next, at the modeling stage, a regression approach was adopted, where six learning methods were compared: Average Prediction, Multiple Regression, Decision Tree, Artificial Neural Network ensemble, Support Vector Machine and Random Forest. The best learning model was obtained by the Random Forest method, which presents a high quality coefficient of determination value (0.81). This model was then opened by using a sensitivity analysis procedure that revealed three influential input attributes: the hospital episode type, the physical service where the patient is hospitalized and the associated medical specialty. Such extracted knowledge confirmed that the obtained predictive model is credible and with potential value for supporting decisions of hospital managers.
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BACKGROUND: Lean Production Systems (LPS) have become very popular among manufacturing industries, services and large commercial areas. A LPS must develop and consider a set of work features to bring compatibility with workplace ergonomics, namely at a muscular, cognitive and emotional demands level. OBJECTIVE: Identify the most relevant impacts of the adoption of LPS from the ergonomics point of view and summarizes some possible drawbacks for workplace ergonomics due to a flawed application of the LPS. The impacts identified are focused in four dimensions: work pace, intensity and load; worker motivation, satisfaction and stress; autonomy and participation; and health outcome. This paper also discusses the influence that the work organization model has on workplace ergonomics and on the waste elimination previewed by LPS. METHODS: Literature review focused LPS and its impact on occupational ergonomics conditions, as well as on the Health and Safety of workers. The main focus of this research is on LPS implementations in industrial environments and mainly in manufacturing industry workplaces. This is followed by a discussion including the authors’ experience (and previous research). RESULTS: From the reviewed literature it seems that there is no consensus on how Lean principles affect the workplace ergonomics since most authors found positive (advantages) and negative (disadvantages) impacts. CONCLUSIONS: The negative impacts or disadvantages of LPS implementations reviewed may result from the misunderstanding of the Lean principles. Possibly, they also happen due to partial Lean implementations (when only one or two tools were implemented) that may be effective in a specific work context but not suitable to all possible situations as the principles of LPS should not lead, by definition, to any of the reported drawbacks in terms of workplace ergonomics.
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Ramos, D., Arezes, P. M., & Afonso, P. (2015). A systematic approach for externalities in occupational safety through the use of the delphi methodology. Paper presented at the Occupational Safety and Hygiene III - Selected Extended and Revised Contributions from the International Symposium on Safety and Hygiene.
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Dissertação de mestrado integrado em Engenharia e Gestão Industrial
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The observational method in tunnel engineering allows the evaluation in real time of the actual conditions of the ground and to take measures if its behavior deviates considerably from predictions. However, it lacks a consistent and structured methodology to use the monitoring data to adapt the support system in real time. The definition of limit criteria above which adaptation is required are not defined and complex inverse analysis procedures (Rechea et al. 2008, Levasseur et al. 2010, Zentar et al. 2001, Lecampion et al. 2002, Finno and Calvello 2005, Goh 1999, Cui and Pan 2012, Deng et al. 2010, Mathew and Lehane 2013, Sharifzadeh et al. 2012, 2013) may be needed to consistently analyze the problem. In this paper a methodology for the real time adaptation of the support systems during tunneling is presented. In a first step limit criteria for displacements and stresses are proposed. The methodology uses graphics that are constructed during the project stage based on parametric calculations to assist in the process and when these graphics are not available, since it is not possible to predict every possible scenario, inverse analysis calculations are carried out. The methodology is applied to the “Bois de Peu” tunnel which is composed by two tubes with over 500 m long. High uncertainty levels existed concerning the heterogeneity of the soil and consequently in the geomechanical design parameters. The methodology was applied in four sections and the results focus on two of them. It is shown that the methodology has potential to be applied in real cases contributing for a consistent approach of a real time adaptation of the support system and highlight the importance of the existence of good quality and specific monitoring data to improve the inverse analysis procedure.