Workplace ergonomics in lean production environments: A literature review

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.

Implementation of a lean six sigma project in a production line

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.

Estudo do trabalho numa empresa de produção de pneus e implementação de ferramentas Lean

Dissertação de mestrado integrado em Engenharia e Gestão Industrial

Aplicação de metodologias Lean na secção de tecelagem de uma empresa têxtil

Dissertação de mestrado integrado em Engenharia e Gestão Industrial

Melhoria de processos numa indústria têxtil através da aplicação do paradigma Lean

Dissertação de mestrado em Engenharia Industrial

Aplicação de princípios e ferramentas Lean numa empresa de produção de cablagens

Dissertação de mestrado integrado em Engenharia e Gestão Industrial

Aplicação de princípios e ferramentas lean numa unidade de cirurgia de ambulatório de um hospital

Dissertação de mestrado integrado em Engenharia Industrial

Using data mining for prediction of hospital length of stay: an application of the CRISP-DM Methodology

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.

A systematic approach for externalities in occupational safety through the use of the delphi methodology

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.

Methodology for real-time adaptation of tunnels support using the observational method

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.

Impact performance prediction of injection-molded talc-filled polypropylene through thermomechanical environment assessment

Due to the fact that different injection molding conditions tailor the mechanical response of the thermoplastic material, such effect must be considered earlier in the product development process. The existing approaches implemented in different commercial software solutions are very limited in their capabilities to estimate the influence of processing conditions on the mechanical properties. Thus, the accuracy of predictive simulations could be improved. In this study, we demonstrate how to establish straightforward processing-impact property relationships of talc-filled injection-molded polypropylene disc-shaped parts by assessing the thermomechanical environment (TME). To investigate the relationship between impact properties and the key operative variables (flow rate, melt and mold temperature, and holding pressure), the design of experiments approach was applied to systematically vary the TME of molded samples. The TME is characterized on computer flow simulation outputsanddefined bytwo thermomechanical indices (TMI): the cooling index (CI; associated to the core features) and the thermo-stress index (TSI; related to the skin features). The TMI methodology coupled to an integrated simulation program has been developed as a tool to predict the impact response. The dynamic impact properties (peak force, peak energy, and puncture energy) were evaluated using instrumented falling weight impact tests and were all found to be similarly affected by the imposed TME. The most important molding parameters affecting the impact properties were found to be the processing temperatures (melt andmold). CI revealed greater importance for the impact response than TSI. The developed integrative tool provided truthful predictions for the envisaged impact properties.

Degradation of all-inkjet-printed organic thin-film transistors with TIPS-pentacene under processes applied in textile manufacturing

Printed electronics represent an alternative solution for the manufacturing of low-temperature and large area flexible electronics. The use of inkjet printing is showing major advantages when compared to other established printing technologies such as, gravure, screen or offset printing, allowing the reduction of manufacturing costs due to its efficient material usage and the direct-writing approach without requirement of any masks. However, several technological restrictions for printed electronics can hinder its application potential, e.g. the device stability under atmospheric or even more stringent conditions. Here, we study the influence of specific mechanical, chemical, and temperature treatments usually appearing in manufacturing processes for textiles on the electrical performance of all-inkjet-printed organic thin-film transistors (OTFTs). Therefore, OTFTs where manufactured with silver electrodes, a UV curable dielectric, and 6,13-bis(triisopropylsilylethynyl) pentance (TIPS-pentacene) as the active semiconductor layer. All the layers were deposited using inkjet printing. After electrical characterization of the printed OTFTs, a simple encapsulation method was applied followed by the degradation study allowing a comparison of the electrical performance of treated and not treated OTFTs. Industrial calendering, dyeing, washing and stentering were selected as typical textile processes and treatment methods for the printed OTFTs. It is shown that the all-inkjet-printed OTFTs fabricated in this work are functional after their submission to the textiles processes but with degradation in the electrical performance, exhibiting higher degradation in the OTFTs with shorter channel lengths (L=10 μm).

Aplicação da metodologia WID numa indústria de calçado

Dissertação de mestrado em Engenharia Industrial

The role of automatic shape and position recognitionin streamlining manufacturing

The main features of most components consist of simple basic functional geometries: planes, cylinders, spheres and cones. Shape and position recognition of these geometries is essential for dimensional characterization of components, and represent an important contribution in the life cycle of the product, concerning in particular the manufacturing and inspection processes of the final product. This work aims to establish an algorithm to automatically recognize such geometries, without operator intervention. Using differential geometry large volumes of data can be treated and the basic functional geometries to be dealt recognized. The original data can be obtained by rapid acquisition methods, such as 3D survey or photography, and then converted into Cartesian coordinates. The satisfaction of intrinsic decision conditions allows different geometries to be fast identified, without operator intervention. Since inspection is generally a time consuming task, this method reduces operator intervention in the process. The algorithm was first tested using geometric data generated in MATLAB and then through a set of data points acquired by measuring with a coordinate measuring machine and a 3D scan on real physical surfaces. Comparison time spent in measuring is presented to show the advantage of the method. The results validated the suitability and potential of the algorithm hereby proposed

Implementação de um novo processo produtivo adequado à introdução faseada de múltiplos produtos

Dissertação de mestrado integrado em Engenharia e Gestão Industrial