Abstract
From lone to short term planning, the decision processes inherent to surgery theatre organization are often subject of empiricism. The current hospital information systems available on Portuguese public hospitals lack a decision support system component that could help achieve better planning solutions, thus better operational performance of the surgery theatre. Since the surgery theatre is the biggest hospital budget consumer, the use of surgery related resources and its intrinsic planning must be carefully studied. We developed a new decision support system for surgery planning conjointly with one of the largest hospitals in the north of Portugal. As for now, the goals of the DSS are to improve the planning process and increase policy compliance. We will enhance this framework by integrating data mining, optimization and simulation techniques in a way that enables a more accurate representation of the surgery theatre problems' stochastic nature, allowing the users to rind enhanced planning alternatives.

Abstract
Ambient Assisted Living environments projects arise as technological responses of the scientific community to problems associated with the population-ageing phenomenon. In theory, these environments should allow de-localization of healthcare services delivery and management to the home, thus containing the economic and social costs associated with old age. The VirtualECare project is one of those environments, enhanced with proactive techniques for a better user experience, focused on elderly chronic patients, through the ability of constant learning and adaption based in user interaction and its contexts. This learning and, consequently, adaption needs, however, unequivocally user identification, especially in multi-user environments. Traditional identification techniques and methodologies are not suitable for these scenario since, usually, require user interaction and wireless identification technique (e.g. RFID, Bluetooth) are very exposed to personification. In order to obtain the expected results we needed a more advanced technology. One possible, appropriate and already fairly developed technique is Facial Recognition. In this paper we present the VirtualECare project approach to Facial Recognition authentication techniques its advantages, disadvantages and possible implementations paths.

Abstract
The global industry is currently facing a growing increase in the competitiveness that forces companies to adopt and develop new strategies and methods of production. Therefore, one of the most relevant challenges in manufacturing engineering is innovatively integrating Product, Process and Factory dimensions and life cycles, in a holistic approach, from design to recycling/disposal and reuse. The challenge faced here is the synchronization and simultaneous generation of all three-domain models by integrating manufacturing engineering knowledge into the early stage of the modelling and planning processes. The next generation of factories has to be modular, scalable, flexible, open, agile and knowledge-based in order to be able to adapt, in real time, to the continuously changing market demands, technology options and regulations. Therefore, integration, flexibility and efficiency requirements and the ability to simulate the production life cycle of a factory play a crucial role in decreasing ramp-up and design times. Furthermore they play a crucial role in improving the performance in the evaluation and reconfiguration of new or existing facilities, in supporting management decisions and providing tools that can guarantee real-time performance monitoring. Therefore, it is necessary to research and implement the underlying models and ideas during the foundation stage of a new conceptual framework, which is designed to be implemented in the next generation of factories. This will be supported by suitable Information and Communication Technologies (ICT) and digital infrastructures and should lay down the foundations for future applications in this research area the industrial paradigm of "Factory as a Product". In line with the context presented here, we propose the development of factory templates to address the design and operation practices throughout the entire life cycle of the factory. Different dimensions of the factory templates are presented in this paper; they cover the design and creation of the factory, its remodelling and even the disassembly and recycling stages. This entire study takes into account relevant factors such as costs, quality, time, flexibility, environmental and social issues and energy efficiency. Throughout the article, different kinds of models are presented, which describe and adjust the structure of the analysis, design and development of a factory integration project that helps provide a formal analysis of the system. Furthermore, templates integrating the factory's response to internal and external disturbances will also be developed.

Abstract
[No abstract available]

Abstract
This paper proposes a heuristic with stochastic neighborhood structures (SNS) to solve two-stage and three-stage two-dimensional guillotine bin packing and cutting stock problems. A solution is represented as a sequence of items which are packed into existing or new stacks, shelves or bins according to previously defined criteria. Moreover, SNS comprises three random neighborhood structures based on modifying the current sequence of items. These are called cut-and-paste, split, and swap blocks and are applied one by one in a fixed order to try to improve the quality of the current solution. Both benchmark instances and real-world instances provided by furniture companies were utilized in the computational tests. Particularly, all benchmark instances are bin packing instances (i.e., the demand of each item type is small), and all real-world instances are classified into bin packing instances and cutting stock instances (i.e., the demand of each item type is large). The computational results obtained by the proposed method are compared with lower bounds and with the solutions obtained by a deterministic Variable Neighborhood Descent (VND) meta-heuristic. The SNS provide solutions within a small percentage of the optimal values, and generally make significant improvements in cutting stock instances and slight to moderate improvements in bin packing instances over the VND approach.

Abstract
The injection mold is a high precision tool responsible for the production of most plastic parts used everywhere. Its design is considered critically important for the quality of the product and efficient processing, as well as determinant for the economics of the entire injection molding process. However, typically, no formal engineering analysis is carried out during the mold design stage. In fact, traditionally, designers rely on their skills and intuition, following a set of general guidelines. This does not ensure that the final mold design is acceptable or the best option. At the same time, mold makers are now highly pressured to shorten both leading times and cost, as well as to accomplish higher levels of mold performance. For these reasons, it is imperative to adopt new methods and tools that allow for faster and higher integrated mold design. To that end, a new global approach, based on the integration of well-known quantitative techniques, such as Design for Six Sigma (DFSS), Structural Equation Modeling (SEM), Axiomatic Design (AD) and Multidisciplinary Design Optimization (MDO) is presented. Although some of these methods have been largely explored, individually or in combination with other methodologies, a quantitative integration of all aspects of design, in such a way that the whole process becomes logical and comprehensible, has not yet been considered. To that end, the DFSS methodology, through its IDOV roadmap, was adopted. It is based on the ICOV Yang and El-Haik proposal, establishing four stages for the design process: Identify, which aims to define customers' requirements/expectations; Design, where the creation of a product concept, and its system-level design, is performed; Optimization, in which all the detailed design, through product optimization, is handled; and finally, Validation, where all product design decisions are validated, in order to verify if the new designed entity indeed meets customer and other requirements. As a result, this approach tackles the design of an injection mold in a global and quantitative approach, starting with a full understanding of customer requirements and converting them into optimal mold solutions. In order to validate it, an integrated platform was developed, where all different analysis modules were inserted and optimized through an overseeing code system. The results attained highlight the great potential of the proposed framework to achieve mold design improvements, with consequent reduction of rework and time savings for the entire mold design process.