This research paper investigates the integration of Explainable Artificial Intelligence (XAI) into Predictive Maintenance (PdM) systems, aiming to enhance transparency, interpretability, and reliability in industrial applications. The primary contribution is the introduction of the Explainability Parameters (XPA) framework, which offers a structured methodology for evaluating and applying XAI in PdM. The study systematically reviews recent advancements and challenges in the literature, categorising explanations into pre-modelling, in-modelling, and post-modelling processes. It presents and analyses significant case studies across various industrial sectors to illustrate the practical implications and hurdles of XAI methodologies. Key findings indicate that while XAI significantly improves the effectiveness and trustworthiness of PdM by clarifying model predictions, its implementation is hindered by the complexity of industrial data and the absence of standardised evaluation methods. The XPA framework addresses these challenges by providing tailored metrics for specific applications and advocating for a multi-phase approach to convert technical outputs into actionable maintenance recommendations. The originality of this paper lies in its comprehensive review and the establishment of rigorous standards for assessing XAI methodologies, thereby bridging the gap between theoretical frameworks and practical applications. By promoting adaptable XAI frameworks that cater to real-world industrial needs, this study fosters trust in automated decision-making processes. It enhances the overall understanding of XAI's role in PdM.

Hybrid laminated composites, integrating High Strength (HS) carbon and glass fibers (E, S) within an epoxy matrix, deliver an optimal compromise between lightweight design, mechanical strength, and cost-effectiveness for applications in industrial, aerospace, automotive, and civil engineering sectors. This study presents a three-dimensional optimization of mechanical performance through a multi-objective genetic algorithm (MOGA) under static loading conditions. The design variables encompass the number of plies (6 to 12), fiber orientation angles (-90°≤ θ ≤90°), and ply materials: HS-Carbon/Epoxy (CF-EP), E-Glass/Epoxy (EG-EP) and S-Glass/Epoxy (SG-EP). A constraint mandating 25% CF-EP placement at the core to maximize stiffness while minimizing stresses. The objectives are to enhance the longitudinal modulus (Ex) and reduce von-Mises stress, while ensuring compliance with the Tsai-Wu failure criterion. An analytical model, implemented in MATLAB, incorporates stiffness matrices, Tsai-Wu failure indices, and von-Mises stress calculations, demonstrating a 30% increase in stiffness and effective mitigation of stress concentrations through centralized CF-EP placement. These findings are corroborated by finite element method (FEM) simulations conducted in ANSYS, which exhibit strong agreement with analytical predictions. This hybrid methodology offers a strong framework for developing high-performance laminated composites, significantly impacting applications requiring structural reliability and efficiency.

This study investigates the fracture behavior of bimaterials, specifically focusing on the Alumina/Silver interface under mechanical, thermal, and thermo-mechanical loading conditions. Through the analysis of Stress Intensity Factors (SIFs) across various crack lengths, temperatures, and along multiple regions and fronts of the crack, we provide valuable insights into the distribution and the nature of stresses, shedding light on how different loading conditions influence crack propagation. Our findings show that, under mechanical loading, the tensile mode SIF (KI) exhibits a straightforward relationship with applied stress, increasing with crack length. In contrast, under thermal loading, KI generally decreases on the surface as the temperature rises, while it increases within the interface, highlighting the complex interplay of thermal expansion and the mismatch of material properties. The thermo-mechanical case combines these effects, further amplifying the role of residual stresses from manufacturing processes and thermal stresses, significantly affecting SIFs and crack growth, especially in bimaterial interfaces. These results contribute to a deeper understanding of fracture mechanisms in hybrid materials.

The purpose of this study is to investigate the direct effects of environmental sustainability orientation (ESO) on green supply chain management (GSCM), ESO on sustainable performance (SP), and GSCM on sustainable performance (SP). It also examines the indirect effect of GSCM on SP through the mediating role of GSCM. Moreover, it tests the moderating role of environmental collaboration (EC) between GSCM and SP. A total of 155 survey questionnaires were collected from firms with ISO 14000 certification in the manufacturing sector in Algeria. The gathered data was examined using (PLS-SEM) model. The findings showed positive effects between ESO, GSCM, and SP. However, no such effect was detected for the moderating role of environmental collaboration on the links between GSCM and SP. The limitation of this study was the use of only firms with ISO 14000 certification, so future studies should consider a wider range of firms and different scales. Regarding environmental problems, firms in Algeria can apply ESO and GSCM to achieve sustainable performance.

This article aims to study technological intelligence in innovative startups in Algeria using Kerr’s model. Technological intelligence consists of four main dimensions: intelligent systems, competitive intelligence, market intelligence, and intelligent processes. To collect data, a questionnaire was distributed to a sample of 255 innovative startups in Algeria, and the data were analyzed using confirmatory factor analysis (CFA) with Smart PLS software. The results indicated that the two-dimensional model combining intelligent systems and competitive intelligence provided the best fit, with a relationship value of 0.605 between these two dimensions. On the other hand, the relationship between market intelligence and competitive intelligence was weak, with a value of 0.281, reflecting the limited use of analytical methods by startups to monitor competitors. Based on these findings, the study recommends that innovative startups in Algeria enhance their use of competitive intelligence and intelligent systems to improve decision-making processes. Additionally, these startups should make better use of available market technologies to develop their products and services, while focusing on continuous competitor analysis and identifying opportunities. In conclusion, technological intelligence is a strategic element for startups, helping them improve their performance and achieve a competitive edge in the changing business environment in Algeria.

Buckminsterfullerene fragments are interesting to use in hydrogen adsorption because of the suitable properties possessed by their concave structure. In the present paper, adsorption of hydrogen on the bowl-shaped corannulene and its derivatives is investigated. Both electron donor and electron acceptor are explored in the substitution and 28 derivatives are generated. DFT calculations are performed by means of WB97XD functional. The substitution number and the substitution nature of corannulene derivatives are analyzed through results based on several parameters. Besides bowl depth and equilibrium distance, also charge distribution and some reactivity indices, based on MEDT, are reported. Results show that a newly created charge distribution contributes to a better binding process.

A pressurized liquid extraction (PLE) technique was evaluated in this study and optimized using response surface methodology (RSM) for the determination of polycyclic aromatic hydrocarbons and their nitro derivatives from diesel particulate matter. A central composite design (CCD) was applied for the study of three parameters (temperature, nature of solvent and static time) and the optimal conditions were determined for a time of 9 min and a temperature of 145 °C and dichloromethane as extraction solvent. With the GC/MS analytical technique, the limits of detection (LOD) obtained range from 0.3 to 1.5 µg.L-1 for PAHs and from 4.6 to 8 µg.L-1 for nitrated PAHs. Also, this method allowed excellent recoveries of NPAH adsorbed on diesel soot particles (R ≥ 90%) using a mixture of solvents (1% acetic acid in pyridine). The PLE process developed in this research is quantitative and reproducible while using much less solvent than conventional extraction methods.

This study examines the impact of indentations on the strength of float glass. Using the Vickers indentation method with loads of 1N and 10N, we created defects at varying distances from the point of contact. Biaxial flexure tests revealed that indentations with 1N at 18mm decreased the strength, while those with 10N and shorter distances from the point of contact increased the strength. Weibull distribution analyses showed a correlation between the load, distance, and the Weibull modulus, highlighting the influence of defect size on the probability of rupture.

The increasing complexities posed by green organizational challenges and technological advancements require a thorough grasp of the vital capabilities needed to maintain the firm’s sustainable performance. This study aims to explore the associations of green technological innovation and management innovation to sustainable performance and estimate to what extent digital leadership moderates these associations. The resource-based view (RBV) and socio-technical system theory (STS) are leveraged to conceptualize the research model. By adopting a survey-based approach on data gathered from 419 manufacturing and service firms, the PLS-SEM is the statistical approach conducted to test the validity of predictions The outcomes demonstrated that green technological innovation, green management innovation, and digital leadership are positively linked to sustainable performance. Furthermore, higher digital leadership strengthens the linkage of green technology and management innovation to sustainable performance. The outcomes made a powerful contribution to the current literature on green innovations and digital transformation, and substantial recommendations were inferred for organizations aiming to achieve environmental, social, and economic performance.

This study investigates the tensile behavior and crack repair of aluminum using fiberglass-reinforced composite patches. Tensile testing compared uncracked, pre-cracked, and repaired aluminum specimens. Pre-cracking by hole drilling decreased strength and ductility from stress concentrations. Composite patching recovered strength, with 4-ply laminates optimal. Uncracked samples failed by necking, pre-cracked by crack growth, and repaired by adhesive detachment. Results demonstrate composite patching effectively restores strength to cracked aluminum by mitigating stress concentrations when appropriately designed. Finite element modeling simulated stress reduction after patching. This work provides experimental data on composite patch performance for metal crack repair and confirms the approach as an effective strengthening technique, although further optimization is needed.