An Analysis of the Requirement for Energy Management Systems in India for Electric Vehicles

Conventional fuels used in combustion engines are the main sources of carbon dioxide emissions, which affect the environment. If energy is available from renewable sources compared to conventional sources, electric vehicles (EVs) offer efficient and cost-effective solutions to the above issue. However, EVs employ batteries for energy storage, which presents a number of issues. For example, overheating produced by chemical reactions during the charging and discharging process in high temperatures can result in the battery's fatal destruction. Hence, an effective energy management system (EMS) is in need of the technology required for the accomplishment of EVs in the long term. Monitoring and optimizing electricity use is the aim of energy management, which aims to cut costs and emissions without interfering with operations. When lifetime CO2 emissions are taken into consideration, EVs will be far more environmentally friendly than regular fuel vehicles because of the incorporation of sustainable power. Distributed solar energy will help reduce the distribution and transmission losses, which will further lower the lifetime CO2 emissions and operating costs of EVs and hasten their commercial viability. This paper presents a review of energy management challenges and their necessity. EV energy management is very important as it helps to minimize EV charging costs

Industry 4.0 Competencies as the Core of Online Engineering Laboratories

Online laboratories are widely used in higher engineering education and due to the COVID-19 pandemic, they have taken on an even greater relevance. At Tecnologico de Monterrey, Mexico, well-established techniques such as Problem-Based Learning (PBL), Project-Oriented Learning (POL) and Research-Based Learning (RBL) have been implemented over the years, and over the past year, have been successfully incorporated into the students’ learning process within online and remote laboratories. Nevertheless, these learning techniques do not include an element which is crucial in today’s industrialized world: Industry 4.0 competencies. Therefore, this work aims to describe a pedagogical approach in which the development of Industry based competencies complements the aforementioned learning techniques. The use and creation of virtual environments and products is merged with the understanding of fundamental engineering concepts. Further, a measurement of the students’ perceived self-efficacy related to this pedagogical approach is carried out, focusing on the physiological states and mastery experiences of the students. An analysis of its results is presented as well as a discussion on these findings, coupled with the perspectives from different key stakeholders on the importance of the educational institutions’ involvement in developing Industry 4.0 competencies in engineering students. Finally, comments regarding additional factors which play a role in the educational process, but were not studied at this time, as well as additional areas of interest are given

TRENDS AND PROSPECTS OF DIGITAL TWIN TECHNOLOGIES: A REVIEW

© Quantum Journal of Engineering, Science and Technology (QJOEST). This is an open access article under the CC BY-NC-ND licence, https://creativecommons.org/licenses/by-nc-nd/4.0/The plethora of technologically developed software and digital types of machinery are widely applied for industrial production and the digitalization of building technologies. The fourth industrial revolution and the underlying digital transformation, known as Industry 4.0 is reshaping the way individuals live and work fundamentally. However, the advent of Industry 5.0 remodels the representation of industrial data for digitalization. As a result, massive data of different types are being produced. However, these data are hysteretic and isolated from each other, leading to low efficiency and low utilization of these valuable data. Simulation based on the theoretical and static model has been a conventional and powerful tool for the verification, validation, and optimization of a system in its early planning stage, but no attention is paid to the simulation application during system run-time. Dynamic simulation of various systems and the digitalization of the same is made possible using the framework available with Digital Twin. After a complete search of several databases and careful selection according to the proposed criteria, 63 academic publications about digital twin are identified and classified. This paper conducts a comprehensive and in-depth review of this literature to analyze the digital twin from the perspective of concepts, technologies, and industrial applicationsPeer reviewe

Digital Twin Fidelity Requirements Model for Manufacturing

The Digital Twin (DT), including its sub-categories Digital Model (DM) and Digital Shadow (DS), is a promising concept in the context of Smart Manufacturing and Industry 4.0. With ongoing maturation of its fundamental technologies like Simulation, Internet of Things (IoT), Cyber-Physical Systems (CPS), Artificial Intelligence (AI) and Big Data, DT has experienced a substantial increase in scholarly publications and industrial applications. According to academia, DT is considered as an ultra-realistic, high-fidelity virtual model of a physical entity, mirroring all of its properties most accurately. Furthermore, the DT is capable of altering this physical entity based on virtual modifications. Fidelity thereby refers to the number of parameters, their accuracy and level of abstraction. In practice, it is questionable whether the highest fidelity is required to achieve desired benefits. A literary analysis of 77 recent DT application articles reveals that there is currently no structured method supporting scholars and practitioners by elaborating appropriate fidelity levels. Hence, this article proposes the Digital Twin Fidelity Requirements Model (DT-FRM) as a possible solution. It has been developed by using concepts from Design Science Research methodology. Based on an initial problem definition, DT-FRM guides through problem breakdown, identifying problem centric dependent target variables (1), deriving (2) and prioritizing underlying independent variables (3), and defining the required fidelity level for each variable (4). This way, DT-FRM enables its users to efficiently solve their initial problem while minimizing DT implementation and recurring costs. It is shown that assessing the appropriate level of DT fidelity is crucial to realize benefits and reduce implementation complexity in manufacturing

A detection and configuration method for welding completeness in the automotive body-in-white panel based on digital twin

To address the problems of poor welding completeness and inefficient configuration for defective automotive body-in-white panels, we propose a method for detecting and configuring the welding completeness of automotive body-in-white panels based on digital twin (DT) and mixed reality (MR). The method uses DT to build an MR-oriented DT framework for the detections and configuration of body-in-white panel welding completeness. We propose a method to build a DT knowledge base for panels, a Yolov4-based welding completeness detection method, and a MR-based configuration method for the welding completeness in panels. Our team develop a panel welding completeness detection and configuration system to fully validate the effectiveness of the method

Concept study of a Digital Twin of a Precision Agricultural Robot

When designing a digital twin, different properties are needed to be implemented so that the physical twin can be able to interact with the environment and fulfil the tasks that the physical asset was developed for. The methodology proposed in this thesis is of highly relevance when designing a digital twin solution, being simple to adapt to different necessities and with a clear architecture to utilize or to adjust to digital assets in different applications. The digital twin developed in the case study, on which this thesis is based, is the foundation of the development and creation of an innovative table grape harvesting robot. The main objective of this research is to review and identify potential methodologies that can be used in the design stage of a digital twin and to validate how the processes in the methodologies can support the system to fulfill the objectives of the project. The system involves the interactions between the robot, the environment, and the agronomical tasks that the robot needs to perform. This thesis creates the methodologies that will assist different stakeholders in easily identifying the processes that streamline the testing procedure of different algorithms in the digital twin, saving time and resources by doing the development in the digital twin and not in the physical object. The thesis assessed the challenges of limited testing time and transporting equipment and personnel difficulties to a fixed location, in this case, a vineyard located in Italy, defined later as the physical asset. It is of highly importance to incorporate the research structure to the digital twin development team early in the project's timeline. Based on the literature and discussion between stakeholders, the basic architecture was created, and from there, the cases defined in this thesis will allow the users and clients to test in a seamless way their products in the digital twin. The process gave the option to the users to select and use from a basic environment to a more complex and challenging one. The purpose of the thesis was to present and document certain architecture and methodologies used in the research and present them as a base for future developments in the area. This method can be used for projects when physical assets need to be created and tested, when time periods for testing are part of the challenges of the project, and the availability to allocate and integrate resources is complex. The main results and conclusion of this thesis is the methodology proposed, on how a simple processes and methodologies can be easily adapted to the necessities of any digital twin solution, and how the architecture proposed can have the ability to modify different cases for specific objectives. And finally, how it is possible to use, prepper and export the information needed to train the Machine learning (ML) algorithms, and to add noise specific to allow the evolution of the algorithms. The methodology proposed in this thesis can increase the quality and usability of any digital twin by proving how it can be successfully implemented during the planning developing process of a project. Furthermore, the methodology demonstrate that it can be easily adapted to the necessities of any digital twin solution and streamlined the progress in the future use of digital twins in any area. In the case study, the methodology helped all different stakeholders to utilize the digital twin to develop, test, and improve different algorithms from different locations through Europe without the need to build the physical robot, or being in one particular place, and without the restrictions of seasonal harvesting periods

Digital twin integration in multi-agent cyber physical manufacturing systems

Complex manufacturing and supply chain systems consist of concurrent labour-intensive processes and procedures with repetitive time-consuming tasks and multiple quality checks. These features may pose challenges for the efficient operation and management, while manual tasks may significantly increase human errors or near misses, having impact on the propagation of effects and parallel interactions within these systems. In order to handle the aforementioned challenges, a digital twin (DT) integrated in a multi-agent cyber-physical manufacturing system (CPMS) with the help of RFID technology is proposed. The proposed reference architecture tends to improve the trackability and traceability of complex manufacturing processes. In this research work, the interactions occurring both within a single complex manufacturing system and between multiple sites within a supply chain are considered. For the implementation of the integrated DT-CPMS, a simulation model employing the agent-based modelling technique is developed. A case study from a cryogenic supply chain in the UK is also selected to show the application and validity of the proposed digital solution. The results prove that the DT-CPMS architecture can improve system’s performance in terms of human, equipment and space utilisations

Digital twin-enabled smart industrial systems: a bibliometric review

The aim of this study is to investigate the body of literature on digital twins, exploring, in particular, their role in enabling smart industrial systems. This review adopts a dynamic and quantitative bibliometric method including works citations, keywords co-occurrence networks and keywords burst detection with the aim of clarifying the main contributions to this research area and highlighting prevalent topics and trends over time. The analysis performed on citations traces the backbone of contributions to the topic, visible within the main path. Keywords co-occurrence networks depict the prevalent issues addressed, tools implemented and application areas. The burst detection completes the analysis identifying the trends and most recent research areas characterizing research on the digital twin topic. Decision-making, process design and life cycle as well as the enabling role in the adoption of the latest industrial paradigms emerge as the prevalent issues addressed by the body of literature on digital twins. In particular, the up-to-date issues of real-time systems and industry 4.0 technologies, closely related to the concept of smart industrial systems, characterize the latest research trajectories identified in the literature on digital twins. In this context, the digital twin can find new opportunities for application in manufacturing, control and services