Digital Twin Approach for Operation and Maintenance of Transportation System-Systematic Review.

There is a growing need to implement modern technologies, such as digital twinning, to improve the efficiency of transport fleet maintenance processes and maintain company operational capacity at the required level. A comprehensive review of the existing literature is conducted to address this, offering an up-to-date analysis of relevant content in this field. The methodology employed is a systematic literature review using the Primo multi-search tool, adhering to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The selection criteria focused on English studies published between 2012 and 2024, resulting in 201 highly relevant papers. These papers were categorized into seven groups: (a) air transportation, (b) railway transportation, (c) land transportation (road), (d) in-house logistics, (e) water and intermodal transportation, (f) supply chain operation, and (g) other applications. A notable strength of this study is its use of diverse scientific databases facilitated by the multi-search tool. Additionally, a bibliometric analysis was performed, revealing the evolution of DT applications over the past decade and identifying key areas such as predictive maintenance, condition monitoring, and decision-making processes. This study highlights the varied levels of adoption across different transport sectors and underscores promising areas for future development, particularly in underrepresented domains like supply chains and water transport. Additionally, this paper identifies significant research gaps, including integration challenges, real-time data processing, and standardization needs. Future research directions are proposed, focusing on enhancing predictive diagnostics, automating maintenance processes, and optimizing inventory management. This study also outlines a framework for DT in transportation systems, detailing key components and functionalities essential for effective maintenance management. The findings provide a roadmap for future innovations and improvements in DT applications within the transportation industry. This study ends with conclusions and future research directions.

Maintenance Performance in the Age of Industry 4.0: A Bibliometric Performance Analysis and a Systematic Literature Review.

Recently, there has been a growing interest in issues related to maintenance performance management, which is confirmed by a significant number of publications and reports devoted to these problems. However, theoretical and application studies indicate a lack of research on the systematic literature reviews and surveys of studies that would focus on the evolution of Industry 4.0 technologies used in the maintenance area in a cross-sectional manner. Therefore, the paper reviews the existing literature to present an up-to-date and content-relevant analysis in this field. The proposed methodology includes bibliometric performance analysis and a review of the systematic literature. First, the general bibliometric analysis was conducted based on the literature in Scopus and Web of Science databases. Later, the systematic search was performed using the Primo multi-search tool following Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. The main inclusion criteria included the publication dates (studies published from 2012-2022), studies published in English, and studies found in the selected databases. In addition, the authors focused on research work within the scope of the Maintenance 4.0 study. Therefore, papers within the following research fields were selected: (a) augmented reality, (b) virtual reality, (c) system architecture, (d) data-driven decision, (e) Operator 4.0, and (f) cybersecurity. This resulted in the selection of the 214 most relevant papers in the investigated area. Finally, the selected articles in this review were categorized into five groups: (1) Data-driven decision-making in Maintenance 4.0, (2) Operator 4.0, (3) Virtual and Augmented reality in maintenance, (4) Maintenance system architecture, and (5) Cybersecurity in maintenance. The obtained results have led the authors to specify the main research problems and trends related to the analyzed area and to identify the main research gaps for future investigation from academic and engineering perspectives.

Fuzzy Risk-Based Maintenance Strategy with Safety Considerations for the Mining Industry.

Enterprises today are increasingly seeking maintenance management strategies to ensure that their machines run faultlessly. This problem is particularly relevant in the mining sector, due to the demanding working conditions of underground mines and machines and equipment-operating regimes. Therefore, in this article, the authors proposed a new approach to mining machinery maintenance management, based on the concept of risk-based maintenance (RBM) and taking into account safety issues. The proposed method includes five levels of analysis, of which the first level focuses on hazard analysis, while the next three are connected with a risk evaluation. The final level relates to determining the RBM recommendations. The recommendations are defined in relation to the three main improvement areas: maintenance, safety, and resource availability/allocation. The proposed approach is based on the use of fuzzy logic. To present the possibilities of implementing our method, a case study covering the operation of selected mining machinery in a selected Polish underground mine is presented. In the case of mining machinery, fourteen adverse-event scenarios were identified and investigated; general recommendations were also given. The authors have also indicated further directions of research work to optimize system maintenance strategies, based on the concept of risk-based maintenance. Additionally, the discussion about the implementation possibilities of the approach developed herein is provided.

Cyber-Attacks Risk Analysis Method for Different Levels of Automation of Mining Processes in Mines Based on Fuzzy Theory Use.

The rising automation level and development of the Industry 4.0 concept in the mining sector increase the risk of cyber-attacks. As a result, this article focuses on developing a risk analysis method that integrates Kaplan's and Garrick's approach and fuzzy theory. The proposed approach takes into account the level of automation of the operating mining processes. Moreover, it follows five main steps, including identifying the automation level in a selected mine, definition of cyber-attack targets, identification of cyber-attack techniques, definition of cyber-attack consequences, and risk ratio assessment. The proposed risk assessment procedure was performed according to three cyber-attack targets (databases, internal networks, machinery) and seven selected types of cyber-attack techniques. The fuzzy theory is implemented in risk parameter estimation for cyber-attack scenario occurrence in the mining industry. To illustrate the given method's applicability, seven scenarios for three levels of mine automation are analyzed. The proposed method may be used to reveal the current cybersecurity status of the mine. Moreover, it will be a valuable guide for mines in which automation is planned in the near future.

Store-operated calcium entry contributes to abnormal Ca²âº signalling in dystrophic mdx mouse myoblasts.

Sarcolemma damage and activation of various calcium channels are implicated in altered Ca(2+) homeostasis in muscle fibres of both Duchenne muscular dystrophy (DMD) sufferers and in the mdx mouse model of DMD. Previously we have demonstrated that also in mdx myoblasts extracellular nucleotides trigger elevated cytoplasmic Ca(2+) concentrations due to alterations of both ionotropic and metabotropic purinergic receptors. Here we extend these findings to show that the mdx mutation is associated with enhanced store-operated calcium entry (SOCE). Substantially increased rate of SOCE in mdx myoblasts in comparison to that in control cells correlated with significantly elevated STIM1 protein levels. These results reveal that mutation in the dystrophin-encoding Dmd gene may significantly impact cellular calcium response to metabotropic stimulation involving depletion of the intracellular calcium stores followed by activation of the store-operated calcium entry, as early as in undifferentiated myoblasts. These data are in agreement with the increasing number of reports showing that the dystrophic pathology resulting from dystrophin mutations may be developmentally regulated. Moreover, our results showing that aberrant responses to extracellular stimuli may contribute to DMD pathogenesis suggest that treatments inhibiting such responses might alter progression of this lethal disease.

Potassium channel openers prevent palmitate-induced insulin resistance in C2C12 myotubes.

Insulin resistance (IR) of muscle cells is an early symptom of type 2 diabetes. It often results from excessive lipid accumulation in muscle fibers which under in vitro experimental conditions may be induced by incubation of muscle cells with palmitate. IR is manifested as a reduced response of cells to insulin expressed by lowered Akt kinase phosphorylation and decreased insulin-dependent glucose uptake. Stimulation of mitochondrial oxidative metabolism by mild dissipation of the mitochondrial potential is thought to increase fatty acid utilization and thereby prevent insulin resistance. Here it is shown that nicorandil and NS1619, which are openers of two different mitochondrial potassium channels, protect C2C12 myotubes from palmitate-induced insulin resistance. Preincubation of myotubes with 5-hydroxydecanoate abolishes the protective effect of nicorandil. The efficient concentrations of both openers are far below those commonly applied for cytoprotection. This is probably why their effects on the mitochondrial energy metabolism are small. These data suggest that opening of mitochondrial potassium channels could be a promising approach in prevention and therapy of insulin resistance related to dyslipidemia and obesity.

Mutation in dystrophin-encoding gene affects energy metabolism in mouse myoblasts.

Duchenne Muscular Dystrophy is characterized by severe defects in differentiated muscle fibers, including abnormal calcium homeostasis and impaired cellular energy metabolism. Here we demonstrate that myoblasts derived from dystrophic (mdx) mouse exhibit reduced oxygen consumption, increased mitochondrial membrane potential, enhanced reactive oxygen species formation, stimulated glycolysis but unaffected total cellular ATP content. Moreover, reduced amounts of specific subunits of the mitochondrial respiratory complexes and ATP-synthase as well as disorganized mitochondrial network were observed. Both the dystrophic and control myoblasts used were derived from a common inbred mouse strain and the only difference between them is a point mutation in the dystrophin-encoding gene, thus these data indicate that this mutation results in multiple phenotypic alterations demonstrating as early as in undifferentiated myoblasts. This finding sheds new light on the molecular mechanisms of Duchenne Muscular Dystrophy pathogenesis.