Circular Production and Maintenance of Automotive Parts:An Internet of Things (IoT) Data Framework and Practice Review

The adoption of the Circular Economy paradigm by industry leads to increased responsibility of manufacturing to ensure a holistic awareness of the environmental impact of its operations. In mitigating negative effects in the environment, current maintenance practice must be considered for its potential contribution to a more sustainable lifecycle for the manufacturing operation, its products and related services. Focusing on the matching of digital technologies to maintenance practice in the automotive sector, this paper outlines a framework for organisations pursuing the integration of environmentally aware solutions in their production systems. This research sets out an agenda and framework for digital maintenance practice within the Circular Economy and the utilisation of Industry 4.0 technologies for this purpose

MOBANA: A distributed stream-based information system for public transit

Abstract: Public transit generates a wide range of diverse data, which include static data and high-velocity data streams from sensors. Integrating and processing this big real-time data is a challenge in developing analytical systems for public transit. We here propose MOBANA (MOBility ANAlyzer), a distributed stream-based system, which provides real-time information to a wide range of users for monitoring and analyzing the performance of public transit. To do so, MOBANA integrates the diverse data sources of public transit, and converts them into standard and exchangeable data formats. In order to manage such diverse data, we propose a layered architecture, where each layer handles a specific kind of data. MOBANA is designed to be efficient. e.g., it identifies the real time position of vehicles by adjusting planned position with real-time data as needed, thus dropping network load. MOBANA is implemented by Distributed Stream Processing Engine (DSPE) and Distributed Messaging System (DMS), which pursue scalable, efficient and reliable real-time processing and analytics. MOBANA was deployed as pilot in Pavia, and tested with real data

An Optimized, Data Distribution Service-Based Solution for Reliable Data Exchange Among Autonomous Underwater Vehicles

Major challenges are presented when managing a large number of heterogeneous vehicles that have to communicate underwater in order to complete a global mission in a cooperative manner. In this kind of application domain, sending data through the environment presents issues that surpass the ones found in other overwater, distributed, cyber-physical systems (i.e., low bandwidth, unreliable transport medium, data representation and hardware high heterogeneity). This manuscript presents a Publish/Subscribe-based semantic middleware solution for unreliable scenarios and vehicle interoperability across cooperative and heterogeneous autonomous vehicles. The middleware relies on different iterations of the Data Distribution Service (DDS) software standard and their combined work between autonomous maritime vehicles and a control entity. It also uses several components with different functionalities deemed as mandatory for a semantic middleware architecture oriented to maritime operations (device and service registration, context awareness, access to the application layer) where other technologies are also interweaved with middleware (wireless communications, acoustic networks). Implementation details and test results, both in a laboratory and a deployment scenario, have been provided as a way to assess the quality of the system and its satisfactory performanceEuropean Commission H2020. SWARMs European project (Smart and Networking Underwater Robots in Cooperation Meshes), under Grant Agreement No. 662107-SWARMs-ECSEL-2014-1, partially supported by the ECSEL JU, the Spanish Ministry of Economy and Competitiveness (Ref: PCIN-2014-022-C02-02)

Context classification for service robots

This dissertation presents a solution for environment sensing using sensor fusion techniques and a context/environment classification of the surroundings in a service robot, so it could change his behavior according to the different rea-soning outputs. As an example, if a robot knows he is outdoors, in a field environment, there can be a sandy ground, in which it should slow down. Contrariwise in indoor environments, that situation is statistically unlikely to happen (sandy ground). This simple assumption denotes the importance of context-aware in automated guided vehicles

Mobile geographic range prediction for electric vehicles

Electric Vehicle (EV) requires new driver information systems because drivers need more information. The spread of mobile devices and communications cost reductions gives new business opportunities. Our work proposal is taking into account the range anxiety problem of drivers of EV and using GIS systems, we represent in a map the charging state range based on a predicting driving distance based on driving style, temperature, and charge level. All this information transferred and represented in a mobile device with a information integration of EV and public transportation.Fundação para a Ciência e a Tecnologia (FCT

Symbiotic service composition in distributed sensor networks

To cope with the evergrowing number of colocated networks and the density they exhibit, we introduce symbiotic networks-networks that intelligently share resources and autonomously adapt to the dynamicity thereof. By allowing the software services provided in such networks to operate in an equally symbiotic manner, new opportunities for the so-called service compositions arise, which take advantage of the multitude of services and combine them to achieve goals set out by the individual networks. To accommodate services in large-scale symbiotic networks, including wireless sensor networks, we propose a software platform which autonomously constructs and orchestrates such compositions. Furthermore, upon changes in the infrastructure, the platform responds by adapting compositions to reflect the changed context. To enable the interaction between services offered by arbitrary partners, the platform deploys ontologies to achieve a common vocabulary and semantic rules to express the policies imposed by the networks involved. By applying the platform to typical scenarios from the field of sensor-augmented cargo transportation and logistics, we illustrate its applicability and, through performance evaluation, show a significant increase in process efficiency. Additionally, by means of a generic problem generator, we quantify the scalability of our platform and show the importance of an appropriate priority function, one of the core constituents of our service composition approach

USE OF DIGITAL TWINS TO MITIGATE COMMUNICATION FAILURES IN MICROGRIDS

This work investigates digital twin (DT) applications for electric power system (EPS) resilience. A novel DT architecture is proposed consisting of a physical twin, a virtual twin, an intelligent agent, and data communications. Requirements for the virtual twin are identified. Guidelines are provided for generating, capturing, and storing data to train the intelligent agent. The relationship between the DT development process and an existing controller hardware-in-the-loop (CHIL) process is discussed. To demonstrate the proposed DT architecture and development process, a DT for a battery energy storage system (BESS) is created based on the simulation of an industrial nanogrid. The creation and validation of the BESS DT virtual twin and intelligent agent are emphasized, including a discussion of the design choices made during the process. The use of data communication for nanogrid coordination is introduced, including the possible detrimental effects of degraded or failed communication. The BESS DT is demonstrated during nominal and off-nominal events in the nanogrid, highlighting the DT’s ability to make decisions using only local measurements rather than relying on a data communication network for coordination. The results show that the BESS DT can increase nanogrid resilience by recommending actions in response to transient events in the nanogrid, even while the data communication network has degraded or failed