Abstract
The present invention is directed to manufacturing, wherein each component of the outsourced process and system can be remotely controlled in decentralized manufacturing process, integrating resources and stakeholders in a global chain, that utilizes ubiquitous computing systems virtual and networked enterprises concepts, for anywhere-anytime control. Experiment involved 68 subjects, Serbian students that have used the interface for remote collaborative control to control CNC machine located in Portugal. Usability evaluation measures of the distributed remote user controlled manufacturing system, such as percentage of task completed, its accuracy and time to complete task, are measured on two types of "client" user interface ("Wall" and "Window"), in two modes of presentation (desktop and video beam), working individually or in small collaborative group consisted of two persons, results were statistically tested. Percentage of task completed is equal for both types of interfaces, while accuracy of task is significantly better for "Wall" interface. Time of task execution is longer for individuals when desktop is used comparing to video beam. There exist significant differences when work is conducted in groups via video beam and time is longer when desktop is used. Also, work time is longer with "Wall" interface. When working in group, work time is shorter than the time when working individually, whereby the working time on desktop is longer than on the video beam. Also, the time is longer when working individually using video beam, using "Wall" interface on desktop, and "Window" interface on video beam. These results show that group work consumes less time in most working options, giving the best results when working in collaborative small group on "Wall" interface via video beam. (C) 2015 The Authors. Published by Elsevier B.V.

Abstract
In this paper, smart objects embedded production and quality management functions are proposed, to promote accurately support decision-making processes, from the shop floor level up to higher decision-making levels. The proposed functions contribute for different kind of problems solving in production and quality management, such as production planning and control, scheduling, factory supervision, real-time data acquisition and processing, and real-time decision making. The web access at different middleware devices and tools, at different decision levels, along with the use of integrated algorithms and tools, embedded in smart objects, promotes conditions for better decision-making for optimized use of knowledge and resources in production systems. The relevance of the proposed smart objects embedded production and quality management functions has been validated positively in a manufacturing company.

Abstract
This paper presents a framework for simulator development for fixed horizon, rolling horizon and real time management models for their modelling and evaluation in ubiquitous production networks under conditions of dynamic environments for economic and environmental sustainability.

Abstract
In this paper, we present Social Network-based Education (SNE) and Learning Factory (LF) as emergent forms of education and training, including their application for the field of Quality Management. This novel learning method has some features of education 3.0 paradigm since participants have freedom to choose what, how and when to learn, as well with whom they coloborate. The actors, students and teachers, form a network, in which the network structure, communication, learning process and behavior exibit features of a social network. The training program content consists of a set of assignments (tasks) that are launched and realized in a crowdsourcing manner. The SNE and LF methodology was applied at the University of Minho in the Integrated Master on Industrial Engineering and Management course for different curricular units, including Quality Management. Within the concepts refered above, the set of assignments implemented for education and training for the field of Quality Management is also presented.

Abstract
For the project of an Agile/Virtual Enterprise (A/V E) the resources selection is a key factor. The resources systems (output of the selection process) should be prepared to guarantee quality, efficiency and cost-attractiveness, in order to ensure the agility and integrability of the A/V E. This is a difficult matter because it can be a combinatorial and multi-criteria problem. Despite the potential of Value Analysis (VA), none of the resources selection models found in the literature incorporates the evaluation of the resources value. They approach mainly the factors cost and/or time. So, our model constitutes an innovative approach because it gives the highest importance to the value of the resources systems, through the incorporation of VA. The main objective is to quantify the selection process performance with VA integrated into the pre-selection of resources in accordance with the developed model. The paper contribution is the positive confirmation, through the simulation results analysis, of the benefits of VA integration in the resources selection process: greater applicability domain for candidate resources and number of tasks; and reduction of the selection time. In conclusion, the increased efficiency and the superior applicability domain of the model are demonstrated.

Abstract
A Shopping Centre (SC) is a "shop open to the public", installed in a building, which include parking, several shops, technical, management, and shopping arcade. In the current economic climate, the maintenance of complex buildings, like shopping centres, is performed under a tight budget context, and is essentially based on systems conditions. A maintenance model, to be effective, requires that maintenance service performance, covering the different building systems and components, is measured. This paper presents a methodology to measure the performance of SCs maintenance management through two major performance indicators: the Building Performance Indicator (BPI); and the Maintenance Efficiency Indicator (MEI). The results of its implementation to seven shopping centres, in Portugal, show that the general condition of the facilities is good (overall BPI= 86,45%) but the low MEI values (<0,37) indicates that insufficient resources are allocated to maintenance activities and this can compromise the future condition of the facilities.