Abstract
Empowering distributed entities with decisional and adaptation capabilities is the current trend in control systems operating in highly changing environments. Cyber-Physical Systems (CPS) is a paradigm addressing this challenge as it allows the integration of both physical and decisional parts. By acting in highly changing environments, these complex control systems must be resilient. This paper proposes a trust and risk management mechanism to be deployed in CPS for resilience improvement. This mechanism, inspired by social and biological behaviour, is deployed in a smart-grid demonstrator. The preliminary results show that embedding this mechanism into distributed entities can lead to an increase of the system stability and efficiency dealing with system uncertainty and perturbations, and consequently improving the system resilience.

Abstract
This paper discusses the methodology for the development of a strategic planning tool, and particularly the architectural solution to be adopted, within an integrated ICT solution for the improvement of planning and scheduling systems for the manufacturing of small production lots of complex products. After the analysis of different possible architectural solutions, the paper proposes a hybrid solution that combines existing solvers with the multi-agent system principles. The proposed approach introduces several benefits, namely in terms of flexibility, robustness, and achievement of exploratory alternative solutions, playing interactive what-if simulation supporting decision-makers to take strategic decisions.

Abstract
Micro grids play an important role in the context of smart grids, improving the system reliability, resilience and stability. In case of micro grids disconnected from the main grid, due to geographical reasons or failure in the service provider, the self-sustainability management is a key issue. This paper discusses agent-based automation and control approaches to handle the self-sustainability in electrical stand-alone micro grids. The proposed agent-based model is applied to a case study and simulated using the Netlogo agent-based modelling platform, allowing to analyze different control and prediction strategies to improve their self-sustainability.

Abstract
Cyber-Physical Systems (CPS) is an emergent approach that focuses on the integration of computational applications with physical devices, being designed as a network of interacting cyber and physical elements. CPS control and monitor real-world physical infrastructures and thus is starting having a high impact in industrial automation. As such design, implementation and operation of CPS and management of the resulting automation infrastructure is of key importance for the industry. In this work, an overview of key aspects of industrial CPS, their technologies and emerging directions, as well as challenges for their implementation is presented. Based on the hands-on experiences gathered from four European, innovation projects over the last decade (i.e. SOCRADES, IMC-AESOP, GRACE and ARUM), a key challenges have been identified and a prioritization and timeline are pointed out with the aim to increase Technology Readiness Levels and lead to their usage in industrial automation environments.

Abstract
Micro grid represents an emergent paradigm to address the challenges of recent smart electrical grid visions, where several small-scale and distributed electrical units cooperate to achieve higher levels of energy self-sustainability, by reducing the main grid dependence. Nevertheless, the realization of this paradigm requires advanced intelligent approaches that are able to effectively manage the micro grid infrastructure and its elements. Multi-agent systems provide a suitable framework to support the development of such systems, where autonomous agents endowed with predictive data analysis capabilities take advantage of the large amount of data produced to predict the renewable energy production and consumption. In this context, this paper presents a predictive data analysis driven multi-agent system for the management of micro grids renewable energy production. The proposed approach was applied to an experimental case study, considering different predictive algorithms and data sources for the short and midterm forecasting of the production of wind and photovoltaic energy-based units.

Abstract
The present paper deals with the questions how product quality can be influenced within product manufacturing and how production control can be optimized for increasing product quality. It focuses on discrete manufacturing processes and presents a methodology to gather and analyze relevant influences on product quality and a multi-agent architecture for flexible and quality focused production control. It will be shown how both approaches can be implemented to achieve a flexible, adaptable and quality focused production process control. © IFAC.