State-of-the-Art Review and Synthesis: A Requirement-based Roadmap for Standardized Predictive Maintenance Automation Using Digital Twin Technologies

Recent digital advances have popularized predictive maintenance (PMx), offering enhanced efficiency, automation, accuracy, cost savings, and independence in maintenance. Yet, it continues to face numerous limitations such as poor explainability, sample inefficiency of data-driven methods, complexity of physics-based methods, and limited generalizability and scalability of knowledge-based methods. This paper proposes leveraging Digital Twins (DTs) to address these challenges and enable automated PMx adoption at larger scales. While we argue that DTs have this transformative potential, they have not yet reached the level of maturity needed to bridge these gaps in a standardized way. Without a standard definition for such evolution, this transformation lacks a solid foundation upon which to base its development. This paper provides a requirement-based roadmap supporting standardized PMx automation using DT technologies. A systematic approach comprising two primary stages is presented. First, we methodically identify the Informational Requirements (IRs) and Functional Requirements (FRs) for PMx, which serve as a foundation from which any unified framework must emerge. Our approach to defining and using IRs and FRs to form the backbone of any PMx DT is supported by the track record of IRs and FRs being successfully used as blueprints in other areas, such as for product development within the software industry. Second, we conduct a thorough literature review spanning fields to determine the ways in which these IRs and FRs are currently being used within DTs, enabling us to point to the specific areas where further research is warranted to support the progress and maturation of requirement-based PMx DTs.Comment: (1)This work has been submitted to the IEEE for possible publication. Copyright may be transferred without notice, after which this version may no longer be accessibl

Aerospace medicine and biology: A continuing bibliography with indexes (supplement 320)

This bibliography lists 125 reports, articles and other documents introduced into the NASA Scientific and Technical Information System during January, 1989. Subject coverage includes: aerospace medicine and psychology, life support systems and controlled environments, safety equipment, exobiology and extraterrestrial life, and flight crew behavior and performance

System configuration and executive requirements specifications for reusable shuttle and space station/base

System configuration and executive requirements specifications for reusable shuttle and space station/bas

Digital twins: a survey on enabling technologies, challenges, trends and future prospects

Digital Twin (DT) is an emerging technology surrounded by many promises, and potentials to reshape the future of industries and society overall. A DT is a system-of-systems which goes far beyond the traditional computer-based simulations and analysis. It is a replication of all the elements, processes, dynamics, and firmware of a physical system into a digital counterpart. The two systems (physical and digital) exist side by side, sharing all the inputs and operations using real-time data communications and information transfer. With the incorporation of Internet of Things (IoT), Artificial Intelligence (AI), 3D models, next generation mobile communications (5G/6G), Augmented Reality (AR), Virtual Reality (VR), distributed computing, Transfer Learning (TL), and electronic sensors, the digital/virtual counterpart of the real-world system is able to provide seamless monitoring, analysis, evaluation and predictions. The DT offers a platform for the testing and analysing of complex systems, which would be impossible in traditional simulations and modular evaluations. However, the development of this technology faces many challenges including the complexities in effective communication and data accumulation, data unavailability to train Machine Learning (ML) models, lack of processing power to support high fidelity twins, the high need for interdisciplinary collaboration, and the absence of standardized development methodologies and validation measures. Being in the early stages of development, DTs lack sufficient documentation. In this context, this survey paper aims to cover the important aspects in realization of the technology. The key enabling technologies, challenges and prospects of DTs are highlighted. The paper provides a deep insight into the technology, lists design goals and objectives, highlights design challenges and limitations across industries, discusses research and commercial developments, provides its applications and use cases, offers case studies in industry, infrastructure and healthcare, lists main service providers and stakeholders, and covers developments to date, as well as viable research dimensions for future developments in DTs

Technology for the Future: In-Space Technology Experiments Program, part 2

The purpose of the Office of Aeronautics and Space Technology (OAST) In-Space Technology Experiments Program In-STEP 1988 Workshop was to identify and prioritize technologies that are critical for future national space programs and require validation in the space environment, and review current NASA (In-Reach) and industry/ university (Out-Reach) experiments. A prioritized list of the critical technology needs was developed for the following eight disciplines: structures; environmental effects; power systems and thermal management; fluid management and propulsion systems; automation and robotics; sensors and information systems; in-space systems; and humans in space. This is part two of two parts and contains the critical technology presentations for the eight theme elements and a summary listing of critical space technology needs for each theme

Proceedings of the 2nd Annual SMACC Research Seminar 2017

The Annual SMACC Research Seminar is a forum for researchers from VTT Technical Research Centre of Finland Ltd, Tampere University of Technology (TUT) and industry to present their research in the area of smart machines and manufacturing. The 2nd seminar is held in 7th of November 2017 in Tampere, Finland. The objective of the seminar is to publish results of the research to wider audiences and to offer researchers a forum to discuss their research and to find common research interests and new research ideas. Smart Machines and Manufacturing Competence Centre - SMACC is joint strategic alliance of VTT Ltd and TUT in the area of intelligent machines and manufacturing. SMACC offers unique services for SME`s in the field of machinery and manufacturing - key features are rapid solutions, cutting-edge research expertise and extensive partnership networks. SMACC is promoting digitalization in mechanical engineering and making scientific research with domestic and international partners in several different topics (www.smacc.fi)

Technology, Science and Culture

From the success of the first and second volume of this series, we are enthusiastic to continue our discussions on research topics related to the fields of Food Science, Intelligent Systems, Molecular Biomedicine, Water Science, and Creation and Theories of Culture. Our aims are to discuss the newest topics, theories, and research methods in each of the mentioned fields, to promote debates among top researchers and graduate students and to generate collaborative works among them

Modeling, Simulation, and Analysis of Lithium-Ion Batteries for Grid-Scale Applications

Lithium-ion batteries have become universally present in daily life, being used across a wide range of portable consumer electronics. These batteries are advantageous compared to other forms of energy storage due to their high energy density and long cycle life. These characteristics make lithium-ion batteries advantageous for many new and developing applications that require large scale energy storage such as electric vehicles and the utility grid. Typical uses for lithium-ion batteries require consistent cycling patterns that are predictable and easy to approximate across all uses, but new large scale applications will have much more dynamic demands. The cycling patterns for electric vehicles will vary based on each individuals driving patterns and batteries used for energy storage in the grid must be flexible enough to account for continuous fluctuations in demand and generation with little advanced notice. Along with these requirements, large scale applications do not want to sacrifice on cycle life and need to know that adding batteries will make operational and economic sense in specific cases. It is not possible to experimentally validate every possible driving pattern or grid storage need because of the great expense of these large systems and the long timescale required for testing. Therefore modeling of these systems is advantageous to help study specific application constraints and understand how lithium-ion batteries operate under those constraints. A systems level model is developed to study lithium-ion battery systems for use with solar energy (in a solar-battery hybrid system) and electric vehicles. Electrochemical based battery models are used as a component within larger systems. To facilitate fast simulation a single step perturbation and switch method is outlined for increasing the speed and robustness of solving the systems of DAEs that result from the systems level model. Operational characteristics are studied for lithium-ion batteries used to store solar energy within the electric grid. Different grid demands are tested against the system model to better understand the best uses for the solar-battery hybrid system. Both generic site studies and site specific studies were conducted. Solar irradiance data from 2010-2014 was obtained from 10 US based sites and used as an input to the system model to understand how the same system will operate differently at various locations. Technological benefits such as system autonomy were simulated for each site as well as economic benefits based on a time-of-use pricing scenario. These models included the growth of the solid-electrolyte interface layer on the battery electrodes to measure capacity fade during operation. This capacity fade mechanism allowed tracking of the site specific effects on battery life. A systems level model for an electric vehicle was also developed to simulate the growth of the SEI layer caused from different types of driving cycles and charging patterns. Results from both system models are presented along with an optimization method for the solar-battery hybrid model. In addition to modeling, experimental tests of LiFePO4 lithium-ion battery cells were conducted to measure capacity fade associated with different types of cycling throughout a batterys life. Cycling protocols were tested to study traditional capacity fade and also to focus on increasing a cells lifetime benefit through application switching