Qualifound – a modular tool developed for quality improvement in foundries

Purpose – Castings defects are usually easy to characterize, but to eradicate them can be a difficult task. In many cases, defects are caused by the combined effect of different factors, whose identification is often difficult. Besides, the real non-quality costs are usually unknown, and even neglected. This paper aims to describe the development of a modular tool for quality improvement in foundries, and its main objective is to present the application potential and the foundry process areas that are covered and taken into account. Design/methodology/approach – The integrated model was conceived as an expert system, designated Qualifound, which performs both qualitative and quantitative analyses. For the qualitative analyses mode, the nomenclature and the description of defects are based on the classification suggested by the International Committee of the Foundry Technical Association. Thus, a database of defects was established, enabling one to associate the defects with the relevant process operations and the identification of their possible causes. The quantitative analysis mode deals with the number of produced and rejected castings and includes the calculation of the non-quality costs. Findings – The validation of Qualifound was carried out in a Portuguese foundry, whose quality system had been certified according to the ISO 9000 standards. Qualifound was used in every management area and it was concluded that the application had the required technological requisites to provide the necessary information for the foundry management to improve process quality. Originality/value – The paper presents a successful application of an informatics tool on quality improvement in foundries.

A Methodology for GUI Layer Redefinition Through Virtualization and Computer Vision

Nowadays despite improvements in usability and intuitiveness users have to adapt to the proposed systems to satisfy their needs. For instance, they must learn how to achieve tasks, how to interact with the system, and fulfill system's specifications. This paper proposes an approach to improve this situation enabling graphical user interface redefinition through virtualization and computer vision with the aim of increasing the system's usability. To achieve this goal the approach is based on enriched task models, virtualization and picture-driven computing.

Automation & control remote laboratory: evaluating a cooperative methodology

This paper presents a study carried out in order to evaluate the students' perception in the development and use of remote Control and Automation education kits developed by two Universities. Three projects, based on real world environments, were implemented, being local and remotely operated. Students implemented the kits using the theoretical and practical knowledge, being the teachers a catalyst in the learning process. When kits were operational, end-user students got acquainted to the kits in the course curricula units. It is the author's believe that successful results were achieved not only in the learning progress on the Automation and Control fields (hard skills) but also on the development of the students soft skills, leading to encouraging and rewarding goals, motivating their future decisions and promoting synergies in their work. The design of learning experimental kits by students, under teacher supervision, for future use in course curricula by enduser students is an advantageous and rewarding experience.

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.