Search Results (11)

This study investigates the integration of customization and personalization approaches in aviation maintenance through Aviation Technical Support as a Service (ATSaaS) platform. Through a comprehensive survey of 86 small and medium-sized airlines, combined with mathematical modeling of fault detection systems, the study develops and validates a hybrid framework that integrates traditional maintenance approaches with AI-driven solutions. The comparative analysis demonstrates that the hybrid model significantly outperforms both pure customization and pure personalization approaches, achieving a 95% fault detection rate compared to 75% for customization-only and 88% for personalization-only models. The hybrid approach also showed superior performance in predictive maintenance effectiveness (96%), operational downtime reduction (92%), and cost optimization (90%). The research presents three architectural frameworks for ATSaaS implementation—customization-based, personalization-based, and hybrid—providing a structured approach for different airline categories. Large airlines, with their extensive technical expertise and complex operational requirements, benefit from enhancing their customized maintenance programs with personalization tools, improving overall maintenance efficiency by 23%. Simultaneously, smaller operators, often constrained by limited resources, can use ATSaaS platforms to access sophisticated maintenance capabilities without extensive in-house expertise, reducing operational costs by 35% compared to traditional approaches. The study concludes that the successful integration of customization and personalization through ATSaaS platforms represents a promising direction for optimizing aviation maintenance operations, supporting the industry’s movement toward data-driven, adaptive maintenance solutions. Full article

Urban sprawl has resulted in great losses of vegetation areas, an increase in impervious surfaces, and consequently the direct flow of stormwater into stream channels (i.e., the immediate flow of stormwater into stream channels, in comparison to the indirect flow that is represented by practices aiming to retain stormwater for a certain period of time and treat the polluted stormwater prior to flowing into the stream channels such as detention/retention basins, among others). Stormwater management systems such as catch basins (CBs) are needed to reduce the effect of stormwater runoff. Preventative maintenance, repair, and replacement of CBs are critical to achieve stormwater management best practices. Those practices prevent the blockage of the stormwater system, limit the pollutants in storm sewers, and reduce the risk of flooding. However, no preceding research studies have been conducted to model and simulate the serviceability of CBs and to determine optimal strategies for operating CBs. To that extent, this study establishes a framework to develop and validate an optimal and adaptive maintenance, repair, and overhaul (MRO) strategy for CBs. In relation to that, an agent-based model (ABM) integrated with Monte Carlo simulation was developed for all 560 CBs in New York City’s District 5 and was statistically validated using 99% confidence intervals. The MRO parameters were optimized to minimize the total cost of the system and attain the desired level of serviceability of CBs. Sensitivity analysis was conducted to guide the maintenance planning process of CBs and reveal the effect of the input parameters on the model’s behavior. In addition, ten thousand Monte Carlo iterations were simulated to derive the distributions of the defined parameters. The results proved that in order to minimize the overall cost of repair, maintenance, and replacement of CBs and attain a minimum serviceability threshold of 80%, the following optimal MRO policy needs to be implemented: having seven service crews (where service crews are human resources (i.e., MRO teams) needed to perform the required maintenance, repair, and replacement work), implementing a replacing policy, and replacing CBs after five maintenance periods. The findings revealed that the service crews represent the most critical parameter in affecting the total cost and serviceability of CBs. This research contributes to the existing literature by offering a better knowledge of the management process of CBs and devising optimal MRO strategies for properly operating them. Ultimately, this research helps decision-makers and engineers increase the lifespan of CBs and limit their risks of breakdown, increase their efficiency, and avoid unnecessary costs. The proposed model is flexible and can be implemented to any geographical area and with other model/system parameters, which makes it adaptive for any scenario and area presented by the user. Finally, maintaining stormwater management practices helps in protecting the environment by decreasing the demand on stormwater systems, reducing flooding, protecting people and properties, promoting healthier rivers, and consequently creating more sustainable communities. Full article

Hydrogen is one of the most promising power sources for meeting the aviation sector’s long-term decarbonization goals. Although on-board hydrogen systems, namely, fuel cells, are extensively researched, the maintenance, repair and overhaul (MRO) perspective remains mostly unaddressed. This paper analyzes fuel cells from an MRO standpoint, based on a literature review and comparison with the automotive sector. It also examines how well the business models and key resources of MRO providers are currently suited to provide future MRO services. It is shown that fuel cells require extensive MRO activities and that these are needed to meet the aviation sector’s requirements for price, safety and, especially, durability. To some extent, experience from the automotive sector can be built upon, particularly with respect to facility requirements and qualification of personnel. Yet, MRO providers’ existing resources only partially allow them to provide these services. MRO providers’ underlying business models must adapt to the implementation of fuel cells in the aviation sector. MRO providers and services should, therefore, be considered and act as enablers for the introduction of fuel cells in the aviation industry. Full article

In this study, a deep learning model (deepPLM) is shown to automatically detect periodic limb movement syndrome (PLMS) based on electrocardiogram (ECG) signals. The designed deepPLM model consists of four 1D convolutional layers, two long short-term memory units, and a fully connected layer. The Osteoporotic Fractures in Men sleep (MrOS) study dataset was used to construct the model, including training, validating, and testing the model. A single-lead ECG signal of the polysomnographic recording was used for each of the 52 subjects (26 controls and 26 patients) in the MrOS dataset. The ECG signal was normalized and segmented (10 s duration), and it was divided into a training set (66,560 episodes), a validation set (16,640 episodes), and a test set (20,800 episodes). The performance evaluation of the deepPLM model resulted in an F1-score of 92.0%, a precision score of 90.0%, and a recall score of 93.0% for the control set, and 92.0%, 93.0%, and 90.0%, respectively, for the patient set. The results demonstrate the possibility of automatic PLMS detection in patients by using the deepPLM model based on a single-lead ECG. This could be an alternative method for PLMS screening and a helpful tool for home healthcare services for the elderly population. Full article

Mobility management is an essential process in mobile networks to ensure a high quality of service (QoS) for mobile user equipment (UE) during their movements. In fifth generation (5G) and beyond (B5G) mobile networks, mobility management becomes more critical due to several key factors, such as the use of Millimeter Wave (mmWave) and Terahertz, a higher number of deployed small cells, massive growth of connected devices, the requirements of a higher data rate, and the necessities for ultra-low latency with high reliability. Therefore, providing robust mobility techniques that enable seamless connections through the UE’s mobility has become critical and challenging. One of the crucial handover (HO) techniques is known as mobility robustness optimization (MRO), which mainly aims to adjust HO control parameters (HCPs) (time-to-trigger (TTT) and handover margin (HOM)). Although this function has been introduced in 4G and developed further in 5G, it must be more efficient with future mobile networks due to several key challenges, as previously illustrated. This paper proposes a Robust Handover Optimization Technique with a Fuzzy Logic Controller (RHOT-FLC). The proposed technique aims to automatically configure HCPs by exploiting the information on Reference Signal Received Power (RSRP), Reference Signal Received Quality (RSRQ), and UE velocity as input parameters for the proposed technique. The technique is validated through various mobility scenarios in B5G networks. Additionally, it is evaluated using a number of major HO performance metrics, such as HO probability (HOP), HO failure (HOF), HO ping-pong (HOPP), HO latency (HOL), and HO interruption time (HIT). The obtained results have also been compared with other competitive algorithms from the literature. The results show that RHOT-FLC has achieved considerably better performance than other techniques. Furthermore, the RHOT-FLC technique obtains up to 95% HOP reduction, 95.8% in HOF, 97% in HOPP, 94.7% in HOL, and 95% in HIT compared to the competitive algorithms. Overall, RHOT-FLC obtained a substantial improvement of up to 95.5% using the considered HO performance metrics. Full article

Under the framework of Industry 4.0, machines and machine tools have evolved to smart and connected things, comprising the Internet of Things (IoT) and leading to the Mass Personalization (MP) paradigm, which enables the production of uniquely made products at scale. MP, fueled by individualization trends and enabled by increasing digitalization, has the potential to go beyond current mass customization. Although this evolution has enabled engineers to gain useful insight for the production, the machine status, the quality of products, etc., machines have become more complex. Thus, Maintenance Repair and Overhaul (MRO) operations should be undertaken by specialized personnel. Additionally, Augmented Reality (AR) can support remote maintenance assistance to handle unexpected malfunctions. Moreover, due to advances regarding Product Service Systems (PSS), manufacturing companies are offering many services to improve user experience. Consequently, in this manuscript the design and development of a method based on the principles of servitization for the provision of an intelligent and adaptable maintenance service assisted by AR are presented. The contribution of the manuscript extends to the provision of an optimization algorithm for adapting the schedules of the stakeholders based on the energy supplier predictions. The developed method was tested and validated on an industrial case study of injection mold maintenance, achieving 11% energy reduction, 50% less time for mold inspection, and a 20% rise in on-time mold deliveries. Full article

Getting to know the price that users assign to maintenance, repair and operations (MRO) has arisen as an essential consideration in gathering financial sustainability for metro public transport systems. The current research reveals customer reservation price for MRO in the main metro stations in Qatar. The purpose of the present work is to assess the willingness to pay for MRO services in eight metro stations in Doha in order to have a better understanding of user preferences. Qualitative research was carried out employing primary and secondary source of information. Primary data was collected by means of a mixture of data accumulation approaches: key informant meetings and focus-group conversations. Secondary data was collected from the account books, contracts, recordings of trans-actions, statements of work and activity reports given by the local rail committees. A stated preference investigation was applied through open text format questions to more than 1000 customers, and a Poisson regression model was used to evaluate the considerations affecting every higher value. Outputs reveal normal customer reservation prices per month and per train journey. The results also indicate a significant willingness to pay differential among the studied railway stations. The study of the decisive considerations elicits that the degree to which the MRO service can exclude paying consumers, the attending of rail conferences and the possibility of using another rail station are related with the customer reservation price. The outputs of this research are significant for railway public authorities willing to set up reasonable, adequate and realistic fares that support fund competent railway systems in Qatar. Full article

This study proposes a methodology for the oil and gas businesses to keep their production plant productive with a minimum investment in carrying maintenance, repair, and operating inventory planning. The goal is to assist the exploration and production companies in minimizing the investment in keeping maintenance, repair, and operating (MRO) inventory for improving production plant uptime. The MRO inventory is the most expensive asset and it requires substantial investment. It helps in keeping the oil and gas production plant productive by performing planned and unplanned maintenance activities. A (Q, r) model with a stock-out and backorder cost approach is combined with a continuous inventory review policy for the analysis of class A items of oil and gas production plant MRO inventory. The class A items are identified through popular ABC analysis based on annual dollar volume. The demand for the inventory is modeled through Poisson distribution with consideration of constant lead time. The (Q, r) model in both stock-out cost and backorder cost approaches assigned higher order frequency and lower service level to low annual demand and highly expensive items. The stock-out cost approach shows an 8.88% increase in the average service level and a 56.9% decrease in the company average inventory investment. The backorder cost approach results in a 7.77% increase in average service level and a 57% decrease in average inventory investment in contrast to the company’s existing inventory management system. The results have a direct impact on increasing plant uptime and productivity and reducing company maintenance cost through properly managing maintenance stock. The analysis is carried out on the oil and gas production plant’s MRO inventory data, but it can be applied to other companies’ inventory data as well. All the results reflected in this research are based on the inventory ordering policy of two orders per year. The inventory ordering frequency per year may be other than two orders per year depending on the type of organization. Full article

The UK is home to several major air commercial and transport hubs. As a result, there is a high demand for Maintenance, Repair, and Overhaul (MRO) services to ensure that fleets of aircraft are in airworthy conditions. MRO services currently involve heavy manual labor. This creates bottlenecks, low repeatability, and low productivity. Presented in this paper is an investigation to create an automation cell for the fan-blade reconditioning component of MRO. The design and prototype of the automation cell is presented. Furthermore, a digital twin of the grinding process is developed and used as a tool to explore the required grinding force parameters needed to effectively remove surface material. An integration of a 6-DoF industrial robot with an end-effector grinder and a computer vision system was undertaken. The computer vision system was used for the digitization of the fan-blade surface as well as tracking and guidance of material removal. Our findings reveal that our proposed system can perform material removal, track the state of the fan blade during the reconditioning process and do so within a closed-loop automated robotic work cell. Full article

Improving processes in a company starts from a deep knowledge of the current context, of the needs for improvement and of the objectives to be satisfied. Sometimes, traditional processes can benefit from a techno-organizational innovation that changes the way of work by introducing new routines and solutions. The service industry related to maintenance, repair and overhaul (MRO) is characterized by performance linked with the knowledge about the components involved. The emerging technologies and the need for enhanced competitiveness has led to transform and innovate this kind of industry, introducing changes in organizational and technological aspects. MRO processes are characterized by high variability, caused by the uncertainty about the arrival status of a part to be maintained and the intervention needed. The management of MRO processes is, thus, one of the most important challenges for the research community. This paper aims to describe the result of a study carried out by university researchers and industrial engineers of an aerospace company. The proposed solution, the applied approach and expected impacts and benefits are described in the paper in order to lead future activities in the managerial and academic fields. Full article

Customer-oriented management of manufacturing systems is crucial in service-oriented production and product service systems. This paper develops the selection of dispatching rules in combination with alternative process flow designs and demand mix, for a maintenance, repair and overhaul center (MRO) of turbo shaft engines, both for complete engines and engine modules. After an initial systematic screening of priority dispatching rules, the design of experiments and discrete-event simulation allows a quantitative analysis of the better rules for the alternative process flows with internal and service metrics. Next, the design of experiments with analysis of variance and the Taguchi approach enables a search for the optimal combination of process flow and dispatching rules. The consideration of extra costs for overdue work orders into the costing breakdown provides a quantitative evaluation of the optimum range of load for the facility. This facilitates the discussion of the significant trade-offs of cost, service, and flexibility in the production system and the operational management alternatives for decision-making. Full article