Abstract
This paper presents an analytical approach for the evaluation of multi-user safety critical systems presenting a failure delayed behavior pattern. As a consequence of a failure event, the performance of these systems worsens progressively due to the internal fault tolerance mechanisms or the complacency of the users regarding the temporary unavailability of the services. A distinctive feature of the approach is the ability to handle stochastic models containing multiple processes with generalized distributions. The approach is based on the determination of analytical expressions to measure reliability, for instance, frequency and probability of failure states, which may be evaluated using general purpose mathematical tools. The paper first reviews other well-established techniques employed in the assessment of non-Markovian systems, particularly those based on stochastic Petri nets. The rationale of the new approach and its fundamental algorithms are presented together with a set of illustrative examples which highlight the strengths of the approach, as well as its limitations. Copyright (c) 2012 John Wiley & Sons, Ltd.

Abstract
In the last years, several researchers from two different academic communities, the Operations Research and the Process Systems Engineering, have been developing mathematical formulations for the lot-sizing and scheduling of single-stage continuous processes with complex setup structures. This problem has been intensively studied due to its importance to a wide range of industries where a single-stage approach is suitable for production planning. This is the case of the glass container, beer, and dairy production. Recent works have been performed by both mentioned communities, however, no intense communication between these research efforts has been observed. This work attempts a systematic analysis on recent formulation developments of both communities. Based on the result of this comparison, a reformulation is proposed that outperforms in the majority of the cases the previous existent formulations for a set of systematically generated random instances.

Abstract
This paper aims to provide an assessment of urban quality of life (QoL) of European cities from the perspective of qualified human resources. The competitiveness of cities relies increasingly in their capacity to attract highly educated workers, as they are important assets for firms when choosing a location. Qualified human resources, on the other hand, tend to value QoL over other urban features. This is why policymakers and urban planners need to evaluate QoL of cities and be provided with tools that can guide action to improvements in this area. We assess urban QoL by means of a composite indicator constructed using data envelopment analysis, based on Urban Audit data and Mercer's framework of analysis, to give account of 246 European cities. Besides presenting a ranking of the best and the worst scores of QoL, this methodology allows benchmarking strategies.

Abstract
In many manufacturing systems human resources are essential in some cognitive intensive tasks while the more repetitive ones are assigned to automatic systems. If on the one hand, automation has a deterministic pace; humans are known by a flexible and variable work manner. Therefore, a reliable description of both hardware and human components is required for designing such manufacturing systems. The purpose of this paper is to investigate the impact of the variable throughput of a manual process in a production flow that contains automatic processes upstream and downstream. With regard to the description of human behavior, two sources of variability were considered: natural and abnormal variability. Natural variability refers to the differences in terms of processing times that can be found among individuals. Organizational aspects such delays in shift changing and breaks along the shift, are referred as abnormal variability, and were also investigated by means of an analytical and simulation models.

Abstract
In fashion business, consumer needs and expectations of specific target groups—such as elderly, obese, disabled, or diabetic persons—are arising as challenging opportunities for European companies that are asked to supply small series of innovative and fashionable goods of high quality, affordable price and eco-compatible. This paper aims at proposing a reference model to support collaborative supply networks in addressing the need for Fashionable and Healthy Clothing and Footwear products. In particular this work describes the implementation of the model in a real case highlighting the developments and changes implied at network level. © Springer International Publishing Switzerland 2013.

Abstract
Due to the increasing globalization process and the current economic situation, the power has shifted from the producer to the costumer, forcing companies to become more aware of the market needs. In order to become more customer-oriented, companies have been enhancing their management capabilities by shifting from a functional oriented approach to a process centered strategy, where core inter-firms processes can be seamlessly monitored and controlled. Since it is not possible to manage a system if its performance cannot be measured continuously during its entire life cycle, it is necessary to explore flexible and agile performance measurement and management systems as they are important tools capable of supporting the achievement of the strategic goals on the operational side. In the recent years several research projects have developed techniques and tools that support the collaboration. However they are restricted to the business level. In order to achieve the goals with the best performance, innovative and appropriate process monitoring and control mechanisms are needed. Consequently, this research provides an innovative solution that facilitates not only the gathering of operational and strategic information but also the assessment of collaborative manufacturing processes behavior following a fuzzy approach. © Springer International Publishing Switzerland 2013.