Abstract
Today, the variety of complex products, low volume and decreasing life cycles require a combination of multiple skills that, often, do not exist in a single organization. This raises the need to extend the traditional organization towards the extended virtual enterprise. During the last decade several research projects developed concepts, methods and tools to support the design and operation of the virtual enterprises. However, the impact in industry remains low mainly due to the lack of vertical and horizontal integration, both at business and technical level. Industry 4.0 may be the missing enabler for effective virtual enterprises, once it integrates both business entities and technical entities into a single concept - the Industry 4.0 component - thus enabling enhanced interoperability. This paper presents innovative Industry 4.0 approaches, concepts, methods and tools applied to real manufacturing environments, showing how they enable the creation of cyber-physical production systems leading to a flexible, efficient and seamlessly virtual enterprise.

Abstract
This paper presents a novel approach on flexible and knowledge intensive process management, driven by a large automotive industry case study. The automotive company in analysis requires a very dynamic behaviour, based on high flexibility of both people and equipment. Market has been imposing a decreasing of automotive products life cycles, increasing the number of line adaptations during the entire value chain, resulting in an increased complexity from product design to production. To handle this complexity, new knowledge-based methods and technologies to model, simulate, optimize and monitor planned and existing manufacturing systems are required. Existing large Enterprise Information Systems impose totally structured and predictable workflow, while knowledge intensive processes are flexible and unpredictable, involving high amount of human-decision and interaction. This lead to the need of development of highly specialized applications. This paper presents a novel hybrid approach, including work, information and communication management, to support knowledge intensive processes. The application of the new solution in the automotive engineering process management proved to be very effective and efficient, leading to significant savings.

Abstract
The rise of a new digital industrial paradigm known as industry 4.0, powered by several enabling technologies such as flexible and collaborative robots, autonomous vehicles, internet of things, cloud and manufacturing servitization, is seen as the key enabler for the fourth industrial revolution: the digital manufacturing. However, there are still several challenges related to the effective adoption of these technologies and to enterprise level interoperability so that an entire cyber physical production system can work seamlessly. Besides the set of challenges faced by industrialists, this research work presents innovative results towards a plug and play seamlessly integration of technologies, from the shop floor to the enterprise management layers, ensuring a total integrated architecture supporting the full product lifecycle management.

Abstract
Today, manufacturing is moving towards customer-driven and knowledge-based proactive production. Shorter product life cycles lead to increased complexity in areas such as product and process design, factory deployment and production operations. To handle this complexity, new knowledge-based methods and technologies are needed to model, simulate, optimize and monitor manufacturing systems. Existing large Enterprise Information Systems (EIS) impose structured and predictable workflow, while processes "on the ground" are often unpredictable and involve a large number of human based decisions and collaboration. This is leading to a major shift on EIS paradigm and leading to development of a set of specialized small applications, each one with fewer features, but highly specialized, flexible, cross linked and easy to use. This paper presents a hybrid management solution intended to support collaboration and decision in the scope of automotive engineering and planning. The solution, labelled as HPM - Hybrid Process Manager, encompasses a set of tools for work, information and communication management fully integrated with knowledge based engineering processes. Its overall aim is to ease the flow of information between all the partners, making it more reliable and actual, allowing a closer control and faster reaction to upcoming events. The adoption of HPM approach proves to be quite effective and efficient, leading to significant results in terms of cost and time saving. When using the solution, managers no longer need to constantly ask for reporting, leading to a significant reduction on email and paperwork. It is relevant to underline that the proposed approach allowed planners to concentrate in important issues improving the product and avoid non-value added efforts and time on collateral activities. Another main advantage stays on the experience retrieval module built in top of the solution, allowing easy access to expertise, knowledge and best practices generated by previous projects, so that they can be readily incorporated in the design of new processes as a factor of knowledge sustainability. (C) 2016 Published by Elsevier B.V.

Abstract
Nowadays, it has been observed an increasing awareness and understanding on the subject of sustainable companies and business models, addressing multi-disciplinary approaches that cover not only economical problems, but also social and environmental challenges. Supply chains and especially collaborative networks managers are increasingly aware of these sustainability issues, continuously seeking to meet current human needs while preserving environmental safety. Only this way, focusing on its sustainable growing, it is possible to preserve companies' steadiness. In order to achieve this goal, sustainable networks must ensure that each partner is fully aligned and committed with economic, environmental and social axes that rule the network operational behaviour. Nevertheless, in order to achieve this level of maturity within such complex and turbulent environments, organisations need to improve the quality of their performance assessment approaches, integrating the different sustainability perspectives. To accomplish this, it is critical to establish specific indicators responsible to formalise and evaluate partners' behaviour, according to well-identified objectives, as well as fuse this information in a comprehensive and user-friendly way. This paper presents a new approach, based on a fuzzy logic-based algorithm, for sustainable network performance and risk assessment. © 2016 Inderscience Enterprises Ltd.

Abstract
Complexity in manufacturing systems appears under a variety of aspects, namely product, processes and operations and systems. Considering that the manufacturing environment is rapidly and constantly changing, with higher levels of customization and complexity, there is higher demand for flexibility and adaptability from companies. In this context, it seems essential to explore new approaches that can support decision-makers to take better decisions concerning the action plans that they need to launch to achieve the expected strategic and operational performance and alignment goals. Companies should become able to analyse their performance drivers, understand their meaning and the feedback loops that affect them. Therefore, decision makers can look into the future, and act even before these causes affect the transformation systems efficiency and effectiveness. This paper presents an approach oriented to multi-performance measurement in complex manufacturing environments. With this approach it is expected to overcome the gap between the operational and strategic layers of a manufacturing system, in order to reduce time when measuring performance and reacting to unexpected behaviours, as well as reduce errors when taking decisions. Moreover, it is expected to decrease the time necessary to calculate an indicator or to introduce a new one into performance management process, reducing the operational costs.