The digital twin (DT) is a virtual representation of a physical object, which has been proposed as one of the key concepts for Industry 4.0. The DT provides a virtual representation of products along their lifecycle that enables the prediction and optimization of the behavior of a production system and its components. A methodology design using model-driven engineering (MDE) is proposed that strives toward being both flexible and generic. This approach is presented at two levels: first, a DT is modeled as a composition of basic components that provide basic functionalities, such as identification, storage, communication, security, data management, human-machine interface (HMI), and simulation; second, an aggregated DT is defined as a hierarchical composition of other DTs. A generic reference architecture based on these concepts and a concrete implementation methodology are proposed using AutomationML. This methodology follows an MDE approach that supports most of the DT features currently proposed in the literature. A case study has been developed, the proposed ideas are being evaluated with industrial case studies, and some of the preliminary results are described in this article. With the case study, it is possible to verify that the proposed methodology supports the creation and the deployment process of a DT.

Urban mobility is one of the main problems faced by big cities. The electric multiple unit (EMU) is the best alternative since it transports a high volume of people at a low cost. Failures during operation cause delays and inconvenience for passengers and operators. This article deals with failures in DC traction motors and their control systems in a transport company operating urban trains. The study focuses on identifying the main causes and consequences of these failures through a statistical analysis. Initially, the study proposes multidimensional scaling to analyze these observations and concludes with the use of neural networks. The acquired results are useful for actions in traction motors during preventive maintenance and in corrective maintenance.

This article extends previous work, presenting a novel polyurethane based compliant spring system designed to be attached to a conventional robotics servo motor, turning it into a series elastic actuator (SEA). The new system is composed by only two mechanical parts: a torsional polyurethane spring and a round aluminum support for link attachment. The polyurethane spring, had its design derived from a iterative FEM-based optimization process. We present also some system identification and practical results using a PID controller for robust position holding.

This study intends to consider the operator skill and the environment conditions as variables of Intelligent Maintenance Systems (IMS). In this sense maintenance operations associated with the technical skills and environment factors through sensory perception can represent important strategy to improve the IMS. This approach considers the Cyber-Physical Systems (or CPS) paradigm to acquire human and context factors once that CPS system combines coordinates physical and computational elements. Thus this study proposes the CPS use for taking account the operator's skill and environment conditions for maintenance strategies. This proposal aims the developing of Advanced Human Computer Interface for Intelligent Maintenance Systems that consider the operator's skill and environment. The validation will be accomplished by interface named Toogle where two case studies will be tested.