O IMPACTO FINANCEIRO DAS AUDITORIAS DA QUALIDADE NAS EMPRESAS PORTUGUESAS

This paper discusses the main theme the financial implications that Portuguese companies with the implementation and subsequent certification of the Quality System and respective Quality Audits. The literature review shows that companies do not publish financial results on the subject in question, making it necessary to acquire information through a questionnaire. About 126 questionnaires were sent. Our sample is however 32 validados.Pode to complete questionnaires that the top 5 overall benefits or indirect financial benefits for Portuguese companies were, respectively: improving internal organization; improving the company's image; increasing customer satisfaction; continuous improvement in customer service; improving competitive position. In terms of direct financial benefits the 3 main benefits obtained by the companies were: turnover increase; Performance (cost reduction); Increased business productivity. So it is expected to contribute to the knowledge of the impact, notably financial of Quality Management Systems and respective audits in Portuguese companies.

Improving fECG signal acquisition in the evaluation of fetal well-being

The ability to monitor fetal heart rate is vital during late pregnancy and labor in order to evaluate fetal well-being. Current monitoring practice is essentially based on external cardiotocography and, less frequently, during labor, invasive fetal scalp electrocardiography. Many current and envisaged applications could benefi t from simpler devices using a 3-lead ECG confi guration. We are designing a maternity support belt with an embedded wireless 3-lead ECG sensor, and have investigated the infl uence of the ground electrode position on signal quality. Data from over 100 pregnant women was collected with the ground electrode placed in 3 locations in order to determine optimum electrode placement and belt form factor.

Improving the environmental performance of bedding products by using life cycle assessment at the design stage

Improvement of the environmental performance of processes and products is a common objective in industry, and has been receiving increased attention in recent years. The main objective of this work is to evaluate the potential environmental impact of two bedding products, a polyurethane foam mattress (PFM) and a pocket spring mattress (PSM). These two types are the most common mattresses used in Europe. A Life Cycle Assessment (LCA) shows that the PFM has a higher environmental impact than the PSM. For both products the main cause of environmental impact is the manufacturing process, respectively the polyurethane foam block moulding process for the PFM, and the pocket spring nucleus process for the PSM. A scenario analysis shows the possibility of reducing the environmental impact of the products’ life cycle using an alternative End-of-Life scenario, resorting to incineration rather than landfill. Two strategies were also studied in order to reduce the environmental impact of the PFM: (1) reutilization of foam that was sent to the waste system management, and (2) a 20% weight reduction of the polyurethane foam. The second strategy has proven to be the most effective.

Improving FEM crash simulation accuracy through local thickness estimation based on CAD data

In this paper, we present a method for estimating local thickness distribution in nite element models, applied to injection molded and cast engineering parts. This method features considerable improved performance compared to two previously proposed approaches, and has been validated against thickness measured by di erent human operators. We also demonstrate that the use of this method for assigning a distribution of local thickness in FEM crash simulations results in a much more accurate prediction of the real part performance, thus increasing the bene ts of computer simulations in engineering design by enabling zero-prototyping and thus reducing product development costs. The simulation results have been compared to experimental tests, evidencing the advantage of the proposed method. Thus, the proposed approach to consider local thickness distribution in FEM crash simulations has high potential on the product development process of complex and highly demanding injection molded and casted parts and is currently being used by Ford Motor Company.

Application of Gage R&R methodology for improving the training and evaluation of automatic optical inspection machine operators

The current level of demand by customers in the electronics industry requires the production of parts with an extremely high level of reliability and quality to ensure complete confidence on the end customer. Automatic Optical Inspection (AOI) machines have an important role in the monitoring and detection of errors during the manufacturing process for printed circuit boards. These machines present images of products with probable assembly mistakes to an operator and him decide whether the product has a real defect or if in turn this was an automated false detection. Operator training is an important aspect for obtaining a lower rate of evaluation failure by the operator and consequently a lower rate of actual defects that slip through to the following processes. The Gage R&R methodology for attributes is part of a Six Sigma strategy to examine the repeatability and reproducibility of an evaluation system, thus giving important feedback on the suitability of each operator in classifying defects. This methodology was already applied in several industry sectors and services at different processes, with excellent results in the evaluation of subjective parameters. An application for training operators of AOI machines was developed, in order to be able to check their fitness and improve future evaluation performance. This application will provide a better understanding of the specific training needs for each operator, and also to accompany the evolution of the training program for new components which in turn present additional new difficulties for the operator evaluation. The use of this application will contribute to reduce the number of defects misclassified by the operators that are passed on to the following steps in the productive process. This defect reduction will also contribute to the continuous improvement of the operator evaluation performance, which is seen as a quality management goal.

Improving The Robustness Of Interventional 4D Ultrasound Segmentation Through The Use Of Personalized Shape Priors

While fluoroscopy is still the most widely used imaging modality to guide cardiac interventions, the fusion of pre-operative Magnetic Resonance Imaging (MRI) with real-time intra-operative ultrasound (US) is rapidly gaining clinical acceptance as a viable, radiation-free alternative. In order to improve the detection of the left ventricular (LV) surface in 4D ultrasound, we propose to take advantage of the pre-operative MRI scans to extract a realistic geometrical model representing the patients cardiac anatomy. This could serve as prior information in the interventional setting, allowing to increase the accuracy of the anatomy extraction step in US data. We have made use of a real-time 3D segmentation framework used in the recent past to solve the LV segmentation problem in MR and US data independently and we take advantage of this common link to introduce the prior information as a soft penalty term in the ultrasound segmentation algorithm. We tested the proposed algorithm in a clinical dataset of 38 patients undergoing both MR and US scans. The introduction of the personalized shape prior improves the accuracy and robustness of the LV segmentation, as supported by the error reduction when compared to core lab manual segmentation of the same US sequences.