Various Levels Of Automation Research Articles

Risk Assessment for Inland Vessels with Various Levels of Automation: a Hazard Identification Study

Abstract The future viability of inland navigation is closely linked to the automation of inland vessels. This will make their use more attractive and efficient. Potential solutions for automation in the scope of this paper include remotely controlled inland vessels that do not require a boatmaster to be on board but are controlled from shore. The implementation of such new technologies involves unknown risks. It is therefore necessary to assess the safety and classify the risks associated with inland vessels of varying degrees of automation. To identify these risks, a Hazard Identification (HAZID) study has been conducted. The outcomes of the study may serve as a basis for adapting regulations and introducing novel technologies, which would facilitate increased automation of inland navigation

Fundamental diagram of mixed traffic flow of CAVs with different connectivity and automation levels

This paper proposes the fundamental diagram model for a mixed traffic flow environment that considers different car-following modes under various levels of automation and connectivity. First, the SAE classification of vehicle automation levels, from L0 to L5, has been further divided into connectivity and automation levels. Second, the car-following modes that affect car-following characteristics are analyzed in mixed traffic flow with different levels of connectivity and automation. Different car-following models are used to describe the car-following characteristics of different types of modes. Third, the fundamental diagram model of mixed traffic flow is further derived based on the different levels of automation and connectivity. Finally, a numerical experiment is designed to evaluate the impact of different penetration rates (PRs) of the car-following modes on the traffic capacity of the mixed traffic flow. The results show that (1) with a higher PR of the automation level of the vehicle, the greater the traffic capacity. At the same time, as the automation levels increase, the change in the penetration rate of high automation levels has a more and more significant impact on traffic capacity. (2) Traffic capacity increases with increased PR of higher automation levels, representing an increase of approximately 11.1 % (3) Compared with connectivity, the PR of automation levels significantly impacts traffic capacity, which is approximately 52.6 %.

Audience evaluations of news videos made with various levels of automation: A population-based survey experiment

The use of automation in news content creation is expanding from the written to the audio-visual medium with news organizations including Reuters turning to video automation services provided by companies such as Wibbitz. Although researchers have explored audience perceptions of text-based news automation, to date no published study has examined how news consumers perceive automated news videos. We conducted a between-subjects online survey experiment to compare how a socio-demographically representative sample ( n = 4200) of online news consumers in the UK perceived human-made, partly automated, and highly automated short-form online news videos on 14 different story topics. Our findings show that human-made videos received on average more favourable responses on some evaluation variables, although the differences were not large. We also found some significant differences in the relative evaluation of automated and human-made news videos across different individual stories. For practitioners our results suggest partly automated news videos with post-automation human editing can be well received. For researchers our results show the need to use reasonably large sets of experimental stimuli, and suggest that ensuring socio-demographic variation within samples of respondents is worthwhile.

A Method for Mapping V2X Communication Requirements to Highly Automated and Autonomous Vehicle Functions

The significance of V2X (Vehicle-to-Everything) technology in the context of highly automated and autonomous vehicles can hardly be overestimated. While V2X is not considered a standalone technology for achieving high automation, it is recognized as a safety-redundant component in automated driving systems. This article aims to systematically assess the requirements towards V2X input data to highly automated and autonomous systems that can individually, or in combination with other sensors, enable certain levels of autonomy. It addresses the assessment of V2X input data requirements for different levels of autonomy defined by SAE International, regulatory challenges, scalability issues in hybrid environments, and the potential impact of Internet of Things (IoT)-based information in non-automotive technical fields. A method is proposed for assessing the applicability of V2X at various levels of automation based on system complexity. The findings provide valuable insights for the development, deployment and regulation of V2X-enabled automated systems, ultimately contributing to enhanced road safety and efficient mobility.

АВТОМАТИЗАЦИЯ ПРОИЗВОДСТВА И ЕЕ ВЛИЯНИЕ НА МЕЖДУНАРОДНУЮ КОНКУРЕНТОСПОСОБНОСТЬ ПРЕДПРИЯТИЙ

Automation of production is becoming one of the key factors determining the interna-tional competitiveness of enterprises in the global economy. This article examines the various levels of automation and its impact on the productivity, efficiency and flexibility of production processes. The role of automation in reducing labor costs, improving product quality and accelerating the adaptation of en-terprises to changing market conditions is assessed. The article also analyzes the challenges and barriers that companies face when implementing automated systems and discusses the prospects for the devel-opment of automation in the context of further digitalization and integration of innovative technologies.

ЭКОНОМИЧЕСКАЯ ЭФФЕКТИВНОСТЬ АВТОМАТИЗАЦИИ ПРОИЗВОДСТВЕННЫХ ПРЕДПРИЯТИЙ

The article is devoted to the study of economic efficiency of automation of manufacturing enterprises. Key aspects such as the advantages of automation, the costs of its implementation, and the impact on production processes and management structures are considered. Economic modeling and comparative analysis of various levels of automation are carried out, which allows identifying optimal strategies for increasing profitability. In conclusion, recommendations are offered for the successful implementation of automation in the context of modern challenges and opportunities.

ПРИМЕНЕНИЕ МЕТОДОВ ТЕОРИИ ВАЖНОСТИ КРИТЕРИЕВ ДЛЯ ОПРЕДЕЛЕНИЯ ОПТИМАЛЬНЫХ ВИДОВ ДЕЯТЕЛЬНОСТИ ПРИ УПРАВЛЕНИИ ВОЗДУШНЫМ СУДНОМ

The formalization of the activities of pilots in the controlling of the latest generation aircraft (AC) is experiencing difficulties due to significant changes in the structure of human activity - the operator. For the most complete analysis of the procedure for controlling the activities of pilots when using various levels of automation, it turns out to be not enough to use only the mathematical apparatus of probability theory and decision-making methods in vague conditions. The article presents the result of applying the methods of the theory of the importance of criteria in order to determine the most rational choice of crew members' activity at various stages of flight and piloting modes of the latest generation aircraft.

Optimizing Control of Waste Incineration Plants Using Reinforcement Learning and Digital Twins

More than 60 waste incineration plants (WIPs) are active across Germany. WIPs have various levels of automation, but they still rely on manual operations by human operators. Human operators tend to rely on a few operational levers and infrequent interventions to manage the complex combustion process. Consequently, the combustion process is managed rather inefficiently, and steam outputs and emission levels are not optimal. This article investigates how reinforcement learning (RL) can help enhance process automation and, thus, optimize the combustion process, e.g., by making more frequent and diverse interventions. An RL agent is trained via trial and error with a reward function that includes the optimization criteria. Since the actual equipment, i.e., the real WIP, cannot be used as the training environment, a digital twin is built using original plant data and a neural network. The RL agent is then trained in this offline environment with the deep Q-network algorithm. First, our work demonstrates that a digital twin of a WIP can be built in a data-driven way. Second, we show that the RL agent outperforms the human operator. Thus, the application of RL might benefit the plant operator in financial terms and the environment in terms of reduced emission levels.

Building a Flexible and Resource-Light Monitoring Platform for a WLCG-Tier2

Software development projects at Edinburgh identified a desire to build and manage our own monitoring platform. This better allows us to support the developing and varied physics and computing interests of our Experimental Particle Physics group. This production platform enables oversight of international experimental data management, local software development projects and active monitoring of lab facilities within our research group. Larger sites such as CERN have access to many resources to support generalpurpose centralised monitoring solutions such as MONIT. At a WLCG Tier2 we only have access to a fraction of these resources and manpower. Recycling nodes from grid storage and borrowed capacity from our Tier2 Hypervisors has enabled us to build a reliable monitoring infrastructure. This also contributes back to our Tier2 management improving our operational and security monitoring. Shared experiences from larger sites gave us a head-start in building our own service monitoring (FluentD) and multi-protocol (AMQP/STOMP/UDP datagram) messaging frameworks atop both our Elasticsearch and OpenSearch clusters. This has been built with minimal hardware and software complexity, maximising maintainability, and reducing manpower costs. A secondary design goal has also been the ability to migrate and upgrade individual components with minimal service interruption. To achieve this, we made heavy use of different layers of containerisation (Podman/Docker), virtualization and NGINX web proxies. This presentation details our experiences in developing this platform from scratch with a focus on minimal resource use. This includes lessons learnt in deploying and comparing both an Elasticsearch and OpenSearch clusters, as well as designing various levels of automation and resiliency for our monitoring framework. This has culminated in us effectively indexing, parsing and storing >200GB of logging and monitoring data per day.

Managing Transitions to Autonomous and Electric Vehicles: Scientometric and Bibliometric Review

This paper presents a scientometric and bibliometric literature review of the research on transitions to autonomous and electric vehicles. We discuss the main characteristics, evolution, and various transitional issues, identifying potential trends for future research. The Scopus and WoS search for relevant research articles generated a corpus of 4693 articles, which we analyzed using VOSviewer visualization software. This result shows that the transition research is interdisciplinary, with 54 scientific areas identified. Analysis requires an understanding of the broader aspects of the automotive industry, trends related to sustainability, environment protection, road safety, public policies, market factors and other business, and legal and management issues. This study highlights the need for more research to address the challenges of this global transition in the automotive industry. Topics for future research are constant improvements in AI algorithms used in AVs, innovations in green energy sources, and storage solutions for EVs. This is leading to new innovative business models and platforms. Further to that, the conclusion is that the impact of the transition to a shared economy, the emergency of mobility as a service, and public acceptance of the technology have to be comprehensively considered. The vehicle of the future is seen as a smart electric car, running on green energy, and utilizing various levels of automation up to full autonomy.

Guest Editorial Introduction to the Special Issue on Deployment of Connected and Automated Vehicles in Mixed Traffic Environment and the Implications on Traffic Safety and Efficiency

The gradual deployment of Connected and Automated Vehicles (CAV) in traffic will result in a transition period in which vehicles with various levels of automation and connectivity will have to co-exist with non-connected and non-automated road users for quite some time. Consequently, new types of interactions will emerge (and old types of interactions are likely to become more complicated) between vehicles at different levels of automation and other road users which could have significant implications on traffic safety and efficiency. Understanding the nature of these interactions, how humans might adapt their behavior, how connectivity can be utilized to proactively enhance drivers char63 driving performance, and how automated vehicles can be programmed to behave in different driving situations to guarantee safety and efficiency remain among the key knowledge gaps that require scientific research. This knowledge is crucial for the development of adequate integration policies of connected and automated vehicles in mixed traffic environment, for updating and improving automated vehicles char63 algorithms and software, for designing the physical and digital road infrastructure, and for operating and managing traffic on the road network.

Audience Evaluations of News Videos Made with Various Levels of Automation: A Population-Based Survey Experiment

Audience Evaluations of News Videos Made with Various Levels of Automation: A Population-Based Survey Experiment

Shared Autonomy to Reduce Sedentary Behavior Among Sit-Stand Desk Users in the United States and India: Web-Based Study.

Fitness technologies such as wearables and sit-stand desks are increasingly being used to fight sedentary lifestyles by encouraging physical activity. However, adherence to such technologies decreases over time because of apathy and increased dismissal of behavioral nudges. To address this problem, we introduced shared autonomy in the context of sit-stand desks, where user input is integrated with robot autonomy to control the desk and reduce sedentary behavior and investigated user reactions and preferences for levels of automation with a sit-stand desk. As demographics affect user acceptance of robotic technology, we also studied how perceptions of nonvolitional behavior change differ across cultures (United States and India), sex, familiarity, dispositional factors, and health priming messages. We conducted a web-based vignette study in the United States and India where a total of 279 participants watched video vignettes of a person interacting with sit-stand desks of various levels of automation and answered questions about their perceptions of the desks such as ranking of the different levels of automation. Participants generally preferred either manual or semiautonomous desks over the fully autonomous option (P<.001). However, participants in India were generally more amenable to the idea of nonvolitional interventions from the desk than participants in the United States (P<.001). Male participants had a stronger desire for having control over the desk than female participants (P=.01). Participants who were more familiar with sit-stand desks were more likely to adopt autonomous sit-stand desks (P=.001). No effects of health priming messages were observed. We estimated the projected health outcome by combining ranking data and hazard ratios from previous work and found that the semiautonomous desk led to the highest projected health outcome. These results suggest that the shared autonomy desk is the optimal level of automation in terms of both user preferences and estimated projected health outcomes. Demographics such as culture and sex had significant effects on how receptive users were to autonomous intervention. As familiarity improves the likelihood of adoption, we propose a gradual behavior change intervention to increase acceptance and adherence, especially for populations with a high desire for control.

ОРГАНИЗАЦИЯ ПРОИЗВОДСТВЕННОГО МОНИТОРИНГА ЖИЗНЕННОГО ЦИКЛА ПРОИЗВОДСТВА СОПОЛИМЕРА С ИСПОЛЬЗОВАНИЕМ ТЕХНОЛОГИЙ LCA

The article is devoted to the actual problem of organizing industrial environmental monitoring of the life cycle of production using information technology. In order to provide Russian enterprises with methodological recommendations for organizing a system of production control and monitoring in order to comply with legislation on maximum environmental standards and waste turnover, it is necessary to study and develop possible options for accumulating data and converting them automatically. The purpose of the article is to develop solutions for organizing a system for monitoring the impact of the stages of the life cycle of petrochemical production on the external environment using tools for continuous information support. To design information modules for assessing the impact of production processes on the ecosystem, sequential procedures of the LCA method were used. To optimize the parameters of environmental friendliness of the production of styrene-butadiene copolymer, the article solves the problem of linear programming; the database for solving the linear programming problem is based on materials from information and technical reference books on the best available technologies, reference books on standards for maximum permissible concentrations of pollutants. The use of the method of information support of the life cycle of LCA products for the organization of automated industrial environmental control and monitoring is scientifically substantiated. A model of the production chain is formed and a block diagram is presented for assessing the impact of the life cycle of chemical production on the ecosystem using the LCA method in the absence of a standardized technology for the accumulation and exchange of environmental data, various levels of automation and digitalization of production processes in petrochemical industries. The flows at the boundary of the chemical-technological system for the production of styrene-butadiene copolymer are investigated and a possible variant of their mathematical optimization is proposed. By solving the linear programming problem, the optimal values of resource consumption for the production of butadiene-styrene copolymer were obtained, at which the minimum indicators of pollutant emissions into the ecosystem are possible: butadiene - 725 kg/t; styrene – 313 kg/t; electricity – 830 kWh/t; water steam - 9.0 Gcal / t. Examples of chemical-technological systems have been identified, where the use of butadiene and styrene relative to the obtained optimal parameter leads to overexpenditure of resources. The research materials can be used in the development of programs and the choice of tools for automated industrial environmental control and monitoring in chemical-technological systems.

Digital Twin-Driven Process and Equipment FMECA Generation for Smart Manufacturing Applications

Qualtech Systems, Inc. (QSI)’s integrated tool set, consisting of TEAMS-Designer® and TEAMS-RDS® provides a comprehensive digital twin-driven and model-based systems engineering approach that can be deployed for fault management throughout the equipment life-cycle – from its design for fault management to condition-based maintenance of the deployed equipment. In this paper, we present QSI’s approach towards adapting and enhancing their existing model-based systems engineering (MBSE) approach towards a comprehensive digital twin that incorporates constructs necessary for development of a Process Failure Modes and Criticality Analysis (P-FMECA) and integrates that with an Equipment FMECA. The paper will discuss the various levels of automation towards incorporation of these model constructs and their reuse towards automation of the development of the different digital twins and subsequently the automatic generation of the combined Process and Equipment FMECA. This automated ability to develop the integrated FMECA that incorporates both Process-level Failure Modes and Equipment-level Failure Modes allows the system designer and operators to correlate and identify process failures down to their root causes at the equipment-level and thereby producing a comprehensive actionable systems-level view of the entire Smart Manufacturing facility from a fault management design and operations perspective. The paper will present the application of this novel technology for the Advanced Metal Finishing Facility (AMFF) at the Warner-Robins Air Logistics Complex (WR-ALC) in Robins Air Force Base, Georgia, as part of WR-ALC’s initiative towards model-based enterprise (MBE) and smart manufacturing.

Computerized Manufacturing Automation: Special Issue of Design and Applications in Robotics

Robotics & Automation have made great strides in the last two decades and are being successfully deployed in Indian manufacturing Industries especially in Automobile Sector. This paper tries to high light the major issues, critical to successful implementation of Automation and a few thrust areas of activities that need to be looked upon in the immediate future. The paper further lists out the various levels of automation for the efficient CAD/CAM implementation and analyses the thrust areas of Robotics and its application that utilize the manpower efficiently: Of late, manufacturing Industry in India has demonstrated their capabilities to deliver quality but there are areas with scope for improvement. This paper is an attempt to highlight various issues during design, development and application of Robotics. The challenge before the Indian Industry is to rise to expectations of their customers by adopting the business practices that can deliver quality.

A Review of UTDrive Studies: Learning Driver Behavior From Naturalistic Driving Data

Intelligent vehicles and Advanced Driver Assistance Systems (ADAS) are being developed rapidly over the past few years. Many applications such as vehicle localization, environment perception, and path planning have shown promising potentialities. While there is great interest in migrating from complete human-controlled vehicles towards fully autonomous vehicles, it is natural that researchers spending more effort trying to understand the interaction between vehicles with various levels of automation in large-scale traffic scenarios. Next-generation vehicles are expected to have the capacity of evaluating driver conditions, vehicle capabilities, surrounding traffic contexts, and take advantage of such knowledge to ensure safe and efficient driving. Three general research questions are raised to achieve this goal, which are (i) how can we acquire sufficient data, (ii) how to evaluate and understand driving behavior, and (iii) how to deliver information effectively to drivers. In this article, we present a review of previous studies from the UTDrive project attempts to answer above questions.

Experimental Design, Instrumentation, and Testing of a Laboratory-Scale Test Rig for Torsional Vibrations—The Next Generation

Drilling technology and specially drilling equipment has dramatically changed in the last 10 years through intensive and innovative technologies, both in terms of hardware and software. While engineers are focusing on safer, faster, and more reliable than ever technologies, big data and automation are currently considered the way forward to achieve these goals. Especially when automation concepts are proposed, the prior testing and qualification under a laboratory-controlled environment are mandatory. Drilling simulators have been hugely successful in training industry personnel and academic professionals. A big reason for its success lies in the seamless integration of hardware and software to include an interactive user interface. Physical experimental simulators have the advantage of exposing the user with visual and auditive aids to better understand the real process. This paper provides an insight into the construction and results obtained using a dedicated laboratory setup, which is also configured to various levels of automation. The setup is capable of safely recreating drilling vibrations that occur in wells, including stick-slip vibrations, which are detrimental in nature. With advanced sensor capabilities, the impact of proper sampling rates on the diagnosis of stick-slip vibrations has been analyzed in the paper. The results show that these vibrations are not only dependent on drilling parameters, such as rotational speed (RPM), torque, and weight on bit, but also on stick-slip parameters, such as bit sticking time period and frequency.

A FRAMEWORK FOR AN INDUSTRIAL ENGINEERING LEARNING FACILITY PARADIGM TOWARD INDUSTRY 4.0

As the industrial world inches ever closer to adopting the Industry 4.0 paradigm, it becomes necessary to evolve a model industrial engineering (IE) learning facility framework that is comprehensive enough to accommodate the full range of exposures required to give students a total practical learning experience. This paper formulates a description model (morphology) and classification scheme for an IE learning facility that considers various levels of automation, including Industry 4.0, to support holistic IE education and training in South Africa. The literature is searched to investigate the state of the art in IE practical learning infrastructure. A questionnaire survey then determines the current status and practices among universities offering industrial engineering. This is followed by the construction of a learning facility framework embodying a mix of facility types, along with a delineation of their relevant characteristics, niches, and strengths that can be customised and deployed to maximise the practical experiences of students.

Evaluation of a model‐based testing platform for Java applications

Model-based testing (MBT) automates the design and generation of test cases from a model. This process includes model building, test selection criteria, test case generation, and test case execution stages. Current tools support this process at various levels of automation, most of them supporting three out of four stages. Among them is MBT4J, a platform that extends ModelJUnit with several techniques, offering a high level of automation for testing Java applications. In this study, the authors evaluate the efficacy of the MBT4J platform, in terms of the number of test cases generated, errors detected, and coverage metrics. A case study is conducted using two open-source Java systems from public repositories, and 15 different configurations. MBT4J was able to automatically generate five models from the source code. It was also able to generate up to 2025 unique test cases for one system and up to 1044 for the other, resulting in 167 and 349 failed tests, respectively. Transition and transition pair coverage reached 100% for all models. Code coverage ranged between 72 and 84% for the one system and between 59 and 76% for the other. The study found that Greedy and Random were the most effective testers for finding errors.