Abstract
Nowadays, many organizations intend to convert their existing production systems towards ones that are terized by adaptability, openness, flexibility and modularity. This requires a redesign of existing information processing systems especially related to control, leading possibly to cyber-physical production systems (CPPS). However, the implementation of new control technologies will have a direct impact on the normal operational status of production while engineers will also face several challenges and obstacles in adopting intelligent automation systems. New step-wise migration strategies are required to holistically support industries in their journey towards CPPS taking into account technical, economic and social aspects. This paper discusses the migration state-of-the-art strategies, analyzing them and providing a first attempt to define a migration approach for innovative production systems. © 2017 IEEE.

Abstract
On the verge of Cyber-Physical Systems (CPS), companies will need, sooner or later, to adapt their systems in order to follow the emergent visions of Industrie 4.0 and Industrial Internet demanding the digitalization of their processes, preventing the losing of their competiveness levels. The engineering of such innovative manufacturing control systems assumes a crucial challenge without which becomes hard to convince researchers and, primarily, practitioners of the proposed architecture potentials. This paper describes the engineering aspects of deploying an ADACOR (ADAptive holonic COntrol aRchitecture for distributed manufacturing systems) based CPS for a real small-scale production system. Since the solution is using agent technology, a special attention is devoted to the interface from the agent control layer to the physical resources using the industrially adopted OPC-UA (OPC Unified Architecture). At the end, some lessons learned in engineering this CPS are drawn. © 2016 IEEE.

Abstract
The world is assisting to the fourth industrial revolution, with several domains of science and technology being strongly developed and, specially, being integrated with each other, allowing to build evolvable complex systems. Data digitization, big-data analysis, distributed control, Industrial Internet of Things, Cyber-Physical Systems and self-organization, amongst others, are playing an important role in this journey. This paper considers the best practices from previous successful European projects addressing distributed control systems to develop an innovative architecture that can be industrially deployed. For this purpose, a particular design process has to be addressed in order to consider the requirements and functionalities from various use cases. To investigate the known practices, four use cases are enlighted in this paper, which cover a wide spectrum of the European industrial force, as well as industrial standards to support a smooth migration from traditional systems to the emergent distributed systems. © 2016 IEEE.

Abstract
The PERFoRM project, an innovation action promoted within the scope of the EU Horizon 2020 program, advocates the use of an Industrie 4.0 compliant system architecture for the seamless reconfiguration of robots and machinery. The system architecture re-uses the innovative results from previous successful R&D projects on distributed control systems domain, such as SOCRADES, IMC-AESOP, GRACE and IDEAS. This paper, after describing the main pillars of the PERFoRM system architecture, focuses on mapping the system architecture into four industrial use cases aiming to validate the system architecture design before its deployment in the real environments. © Springer International Publishing AG 2017.

Abstract
Multi-stage manufacturing, typical in important industrial sectors, is inherently a complex process. The application of the zero defect manufacturing (ZDM) philosophy, together with recent technological advances in cyber-physical systems (CPS), presents significant challenges and opportunities for the implementation of new methodologies towards the continuous system improvement. This paper introduces the main principles of a multi-agent CPS aiming the application of ZDM in multi-stage production systems, which is being developed under the EU H2020 GO0D MAN project. In particular, this paper describes the MAS architecture that allows the distributed data collection and the balancing of the data analysis for monitoring and adaptation among cloud and edge layers, to enable the earlier detection of process and product variability, and the generation of new optimized knowledge by correlating the aggregated data. © 2018, Springer International Publishing AG.