Extensive digitization and interconnection through networks have ushered in a number of new paradigms over the last years: Internet of Things, cyber–physical systems, Industry 4.0, etc. These challenging systems rely on an effective information communication between distributed components. Therefore, the heterogeneity of entities, both hardware and software, must be handled to achieve an operative interoperability and a proper behavior. However, there is also a heterogeneous availability of solutions; different technologies, protocols, and architectures aim to achieve a seamless interconnection. Henceforth, the standardization still requires great efforts from industrial and scientific environments. In this sense, the interface of the open platform communications (OPC) has supported connectivity for automation and supervision infrastructures for more than two decades. The OPC comprises the so-called classic OPC, the original protocol, as well as the last specification, unified architecture (UA). The widespread utilization of the classic OPC together with the powerful functionalities of OPC UA, make the latter one of the main candidates to lead the standardization and systems integration. This paper presents a survey of recent OPC-based systems reported in scientific literature for different domains as well as research projects. The goal of this paper is to provide a broad perspective about the OPC’ applicability and capabilities in order to support the decision about communication interfaces. The results are analyzed and discussed putting special attention on the aforementioned new paradigms. Finally, the main conclusions and open research directions are highlighted.

The simultaneous integration of information from sensors with business data and how to acquire valuable information can be challenging. This paper proposes the simultaneous integration of information from sensors and business data. The proposal is supported by an industrial implementation, which integrates intelligent sensors and real-time decision-making, using a combination of PLC and PC Platforms in a three-level architecture: cloud-fog-edge. Automatic identification intelligent sensors are used to improve the decision-making of a dynamic scheduling tool. The proposed platform is applied to an industrial use-case in analytical Quality Control (QC) laboratories. The regulatory complexity, the personalized production, and traceability requirements make QC laboratories an interesting use case. We use intelligent sensors for automatic identification to improve the decision-making of a dynamic scheduling tool. Results show how the integration of intelligent sensors can improve the online scheduling of tasks. Estimations from system processing times decreased by over 30%. The proposed solution can be extended to other applications such as predictive maintenance, chemical industry, and other industries where scheduling and rescheduling are critical factors for the production.

This paper develops a new mathematical model, for pancake resolvers, that is dependent on a set of variables controlled by a resolver manufacturer-the winding parameters. This model allows a resolver manufacturer to manipulate certain in-process controllable variables in order to readjust already assembled resolvers that, without any action, would be scrapped for the production line. The developed model follows a two-step strategy where, on a first step, a traditional transformer's model computes the resolver nominal conditions and, on a second step, a linear model computes the corrections on the controllable variables, in order to compensate small deviations in design assumptions, caused by the variability of the manufacturing process. An experimental methodology for parameter identification is presented. The linearized model develops a complete new approach to simulate the product characteristics of a pancake resolver from the knowledge of manufacturer controllable variables (winding parameters). This model had been simulated and experimentally tested in a resolver manufacturing plant. The performed tests prove the efficiency of the developed model, stabilizing the product specifications in a dynamic environment with high variability of the production processes. All experiments had been led at the resolver manufacturer Tyco Electronics-Évora plant.

This paper develops an energy management system with integration of smart meters for electricity consumers in a smart grid context. The integration of two types of smart meters (SM) are developed: (i) consumer owned SM and (ii) distributor owned SM. The consumer owned SM runs over a wireless platform–ZigBee protocol and the distributor owned SM uses the wired environment–ModBus protocol. The SM are connected to a SCADA system (Supervisory Control And Data Acquisition) that supervises a network of Programmable Logic Controllers (PLC). The SCADA system/PLC network integrates different types of information coming from several technologies present in modern buildings.The developed control strategy implements a hierarchical cascade controller where inner loops are performed by local PLCs, and the outer loop is managed by a centralized SCADA system, which interacts with the entire local PLC network.In order to implement advanced controllers, a communication channel was developed to allow the communication between the SCADA system and the MATLAB software