Maintenance Components Research Articles

Waiting for the next new ride at Disney world? Understanding the determinants of capital expenditures among theme parks

PurposeThe purpose of this paper is to investigate the determinants of capital expenditures (CAPEX) in the theme park industry, particularly following the financial stresses induced by the COVID-19 pandemic. CAPEX drivers are poorly understood due to the idiosyncratic nature of this industry, which is dominated by a few large players. It also aims to identify the variables influencing both the growth and maintenance components of CAPEX among U.S. theme park operators.Design/methodology/approachThe paper uses contingency theory to analyze both financial and nonfinancial data from U.S. theme park operators between 2009 and 2021. The paper also uses partial least squares structural equation modeling to manage issues of multicollinearity and to ensure robustness in the findings.FindingsThe analysis identifies several key determinants of CAPEX. Resources and the presence of competing theme parks in proximity to an operator’s parks positively affect CAPEX. Conversely, higher leverage, dividend payouts, intellectual property (IP) dominance and population density in areas with their active parks correlate with reduced CAPEX. The paper also notes distinct trends in maintenance versus growth CAPEX post-COVID-19, with maintenance CAPEX increasing as operators invest in existing assets while growth CAPEX trending downwards.Research limitations/implicationsThe study’s scope is confined to U.S.-based theme park operators, limiting the generalizability of the findings internationally. Moreover, data limitations restrict the sample size due to the consolidation of the industry players, potentially affecting the statistical power of the analysis.Practical implicationsThis research offers significant insights for theme park operators, industry analysts and policymakers. Understanding the factors influencing CAPEX can aid operators in strategic planning and investment decisions, especially in a post-pandemic economic environment where efficient capital allocation will be crucial for recovery and growth. A major contribution of this research is the development of a new measure for IP dominance, which allows theme park operators to quantify the impact of IP on their investment strategies.Originality/valueThis study contributes uniquely by incorporating both financial and nonfinancial determinants in analyzing CAPEX within the theme park industry, a sector significantly impacted by the pandemic. It introduces novel metrics for assessing the impact of IP on CAPEX and differentiates between the factors driving maintenance and growth expenditures. The findings enrich the existing literature on hospitality management and provide actionable insights that could guide the strategic financial decisions of theme park operators.

Can Standard Setters Improve Cash Flow Reporting of Capital Expenditures?

SYNOPSIS We evaluate whether current capital expenditures (capex) reporting in the cash flows statement can be improved via disaggregation and/or reclassification of some capex as operating activities. FASB Concept Statement No. 5 suggests recurrence and risk as useful characteristics for determining disaggregation and classification in financial statements. Using a novel German dataset that provides disaggregated capex information, we examine whether these characteristics differ across capex components and provide evidence of up to five economically distinct components. These results support disaggregating capex into maintenance, expansion, rationalization, restructuring, and environmental components. Our findings, however, do not support reclassifying any capex component as operating activities, although evidence suggests capex and capex components are misclassified as investing activities. As a first step toward improving capex reporting guidance, our evidence suggests standard setters consider disaggregating and presenting capex components as supplemental information in the cash flow statement, the footnotes, or MD&A. Data Availability: FactSet data are publicly available. The disaggregated capital expenditures data are available from the ifo Institute. JEL Classifications: G31; M41; M48.

Cost optimization and reliability analysis of fault tolerant system with service interruption and reboot

Due to widespread usage in many real time systems, reliability modeling and cost optimization of fault tolerance system have drawn attention of the practitioners. The fault tolerance in these systems can be provided by the support of maintenance and redundant components that help in smooth operation of the system in spite of failure of some active components. This investigation deals with the performance modeling of a fault-tolerant system consisting of a finite number of active (online) and standby components. During the switching from active to standby, the recovery procedure is performed, which may be imperfect. In case of imperfect recovery, the system reboot takes place. The maintenance of all the components is managed by a repairman (server) which is subject to failure. When the server is interrupted for rendering the service, functioning does not get stopped due to the system switch-over from perfect working to working breakdown mode. The system works even when the server is on working vacation and performs repair jobs of the failed components. The machine repair model based on Markovian process is developed to derive the transient probabilities and other performance indices of the fault tolerant system using Laplace transforms and matrix analytical method. Using the direct search strategy and particle swarm optimization, the cost-benefit analysis is done. The optimal design of the control parameters for the fault-tolerant system are presented by framing a cost-effective ratio function. The model is examined computationally by performing the numerical simulation and cost optimization.

Hypertension Impacts the Oscillatory Dynamics Serving the Encoding Phase of Verbal Working Memory.

Chronic hypertension is known to be a major contributor to cognitive decline, with executive function and working memory being among the domains most commonly affected. Despite the growing literature on such dysfunction in patients with hypertension, the underlying neural processes are poorly understood. In this cross-sectional study, we examine these neural processes by having participants with controlled hypertension, uncontrolled hypertension, and healthy controls perform a verbal working memory task during magnetoencephalography. Neural oscillations associated with the encoding and maintenance components of the working memory task were imaged and statistically evaluated among the 3 groups. Differences related to hypertension emerged during the encoding phase, where the hypertension groups exhibited weaker α-β oscillatory responses compared with controls in the left parietal cortices, whereas such oscillatory activity differed between the 2 hypertension groups in the right prefrontal regions. Importantly, these neural responses in the prefrontal and parietal cortices during encoding were also significantly associated with behavioral performance across all participants. Overall, our data suggest that hypertension is associated with neurophysiological abnormalities during working memory encoding, whereas the neural processes serving maintenance seem to be preserved. The right hemispheric neural responses likely reflected compensatory processing, which patients with controlled hypertension may use to achieve verbal working memory function at the level of controls, as opposed to the uncontrolled hypertension group where diminished resources may have limited such additional recruitment.

An OBB Detection Algorithm of Maintenance Components Based on YOLOv5-OBB-CR

By detecting the position of maintenance components in real-time, maintenance guidance information can be superimposed and important operational guidance can be provided for maintenance personnel. The YOLOv5-OBB-CR real-time detection algorithm is proposed for maintenance component with orientation bounding box based on improved YOLOv5-OBB. The C3 module in the original network is improved to CReToNeXt, which can more effectively enhance the network's ability to learn image features. Considering that the network learning is the labeled rotation box information, the original Loss function CIoU is improved to SIoU with angle loss information, and the improved Loss function can more effectively describe the regression of the target box. The demonstration shows that the mAP@.5 0.95 of YOLOv5-OBB-CR-s (SIoU) is 85.6%, which is 6.7% higher than the original YOLOv5 OBB algorithm.

Cellular senescence: Neither irreversible nor reversible.

Cellular senescence is a critical stress response program implicated in embryonic development, wound healing, aging, and immunity, and it backs up apoptosis as an ultimate cell-cycle exit mechanism. In analogy to replicative exhaustion of telomere-eroded cells, premature types of senescence-referring to oncogene-, therapy-, or virus-induced senescence-are widely considered irreversible growth arrest states as well. We discuss here that entry into full-featured senescence is not necessarily a permanent endpoint, but dependent on essential maintenance components, potentially transient. Unlike a binary state switch, we view senescence with its extensive epigenomic reorganization, profound cytomorphological remodeling, and distinctive metabolic rewiring rather as a journey toward a full-featured arrest condition of variable strength and depth. Senescence-underlying maintenance-essential molecular mechanisms may allow cell-cycle reentry if not continuously provided. Importantly, senescent cells that resumed proliferation fundamentally differ from those that never entered senescence, and hence would not reflect a reversion but a dynamic progression to a post-senescent state that comes with distinct functional and clinically relevant ramifications.

Fault Analysis and Preventive Maintenance of Rocket Vertical Assembly and Test Plant System

Complex industrial systems often consist of many components whose degradation and failure affect the condition and performance of the entire system. To improve system reliability and minimize total system costs, preventive maintenance (PM) of other components is required while the system’s failed components are being repaired. In this paper, a maintenance cost index is proposed for the Rocket Vertical Assembly and Test Plant (RVATP) system considering various types of costs that affect the total expected cost of the system. Based on this index, a maintenance strategy analysis is performed for the RVATP. The sequence of preventive maintenance of components under two maintenance strategies is studied, and the number of preventive maintenance components under cost constraint is discussed. Finally, the RVATP is analyzed as an example. The results show that the maintenance cost index is not only related to the location of components in the system and associated costs, but also to the importance of preventive maintenance components. Simulation results also show the applicability of the maintenance cost index.

Principles of transport means maintenance optimization: equipment cost calculation

Purpose. Justification of principles and methodology for effective calculation of the equipment costs and optimization of transport means maintenance. Methodology. The results of the presented scientific research were obtained using general and special methods of cognition: abstract and logical analysis, systematization and combination, method of theoretical generalization, method of dialectical cognition, deduction and induction, and statistical analysis. This paper analyzes the relationship between the probability of failure prevention by the maintenance system and the associated costs. The research investigates how the variation in the technical condition change rate influences the length of the operation cycle and the rate of its decline. The study’s outcomes are analyzed, including the formation of points of minimum unit costs, the effect of spare parts’ cost, and the practical importance of the conclusions drawn. Findings. This paper outlines the economic methodology for determining the specific expenses of maintaining means of transport. The methodology considers the distribution of expenses for spare parts, labor, and other components. Using this methodology, it is possible to estimate the total costs of maintenance and make informed decisions about the efficient use of resources. It has been determined that the cost of spare parts impacts the efficiency of the maintenance system. Therefore, it is imperative to balance the cost for spare parts and safety, while considering the probability of failure. The method outlined in this work is versatile, which allows its adaptation and application to the specialized road transport. Originality. The paper further develops the methodological approach to calculating equipment costs for transport maintenance, which is used to improve service efficiency and reduce expenses. The approach enables a comprehensive evaluation of the outcomes of enhancing failure prevention probability through the maintenance system. It also aids in managing unused parts’ resources, particularly during short operating cycles. Practical value. The study’s findings can optimize the maintenance system, increase operational efficiency, and enhance the safety and reliability of means of transport, while reducing the costs associated with spare parts, labor, and other maintenance components. This approach aids in conserving resources, reducing operating costs, and is crucial for the financial stability and profitability of management companies.

Equipment Disassembly and Maintenance in an Uncertain Environment Based on a Peafowl Optimization Algorithm

Disassembly sequence planning (DSP) is a key approach for optimizing various industrial equipment-maintenance processes. Finding fast and effective DSP solutions plays an important role in improving maintenance efficiency and quality. However, when disassembling industrial equipment, there are many uncertainties that can have a detrimental impact on the disassembly and subsequent maintenance work. Therefore, this paper proposes a multi-objective DSP problem in an uncertain environment that addresses the uncertainties in the disassembly process through stochastic planning, with the objectives of minimizing disassembly time and enhancing responsiveness to priority maintenance components. Due to the complexity of the problem, an improved peafowl optimization algorithm (IPOA) is proposed for efficient problem-solving. The algorithm is specifically designed and incorporates four customized optimization mechanisms: peafowls’ courtship behavior, the adaptive behavior of female peafowls in proximity, the adaptive search behavior of peafowl chicks, and interactive behavior among male peafowls. These mechanisms enable effective search for optimal or near-optimal solutions. Through comparisons with a real-world industrial case and other advanced algorithms, the superiority of the IPOA in solving DSP problems is demonstrated. This research contributes to improving maintenance efficiency and quality, bringing positive impacts to industrial equipment maintenance.

Analisis Pengendalian Kualitas Pada Proses Produksi Komponen Kursi Susun Menggunakan Metode SPC(Statistical Process Control)


 Metalindo Perkasa is a company engaged in the field of furniture that produces chairs. In the production process of stacking chair components, there are problems encountered, namely the number of defects that exceed 1% of the standard determination. It can be a maximum lack of opinion on the company.The research was conducted with the aim of finding solutions to the factors that cause disability and finding action solutions to minimize disability. The method used in this research is Statistical Process Control (SPC). The results showed that the types of defects found were hollow, bent and curly.Factors that cause defects are human factors, machine factors, method factors, action solutions to eliminate defects by training operators, carrying out machine maintenance and checking machine components regularly and increasing supervision when setting degrees. 

Wind Turbine Optimal Preventive Maintenance Scheduling Using Fibonacci Search and Genetic Algorithm

Maintenance scheduling is essential and crucial for wind turbines to avoid breakdowns and reduce maintenance costs. Many maintenance models have been developed for wind turbines' maintenance planning, such as corrective, preventive and predictive maintenance. Due to communities' dependence on wind turbines for electricity needs, preventative maintenance is the most widely used method for maintenance scheduling. The downside to using this approach is that preventive maintenance is often done in fixed intervals, which is inefficient. In this paper, a more detailed maintenance plan for a 2MW wind turbine has been developed. The paper's focus is to minimize a wind turbine's maintenance cost based on a wind turbine's reliability model. This study uses a two-layer optimization framework: Fibonacci and Genetic Algorithm (GA). The first layer in the optimization method (Fibonacci) finds the optimal number of preventive maintenance required for the system. In the second layer, the optimal times for preventative maintenance and optimal components to maintain have been determined to minimize maintenance costs. The Monte Carlo simulation estimates wind turbine component failure times using their lifetime distributions from the reliability model. The estimated failure times are then used to determine the overall corrective and preventive maintenance costs during the system's lifetime. Finally, an optimal preventive maintenance schedule is proposed for a 2MW wind turbine using the presented method. The method used in this paper can be expanded to a wind farm or similar engineering systems.

A railway track reconstruction method using robotic vision on a mobile manipulator: A proposed strategy

Autonomous robot integration in railways infrastructure maintenance accelerates the digitization and intelligence of infrastructure survey & maintenance, providing high-efficiency and low-cost execution. This paper proposes a health assessment based on 3D reconstruction technology for railway track maintenance using a mobile robotic sensing platform. By combining multiple sensing and taking advantage of a robotic manipulator, a digital model of the target track components is built by a robot-actuated vision system which provides better 3D structural and surface condition reconstruction. Global geo-location and surrounding laser scanning are integrated to reinforce the digital completeness of the model for intelligent management. The new method consists of the following steps: First, according to scheduled maintenance tasks, a Robotics Inspection and Repair System (RIRS) navigates to the task location and uses the onboard depth camera for positioning. Then robot-mounted vision system is guided with an automated trajectory to build the 3D reconstruction of the track or repair object using the vision modeling technique. Finally, the 3D reconstructed model is fused with surrounding mapping of depth vision and Lidar scanning. Both laboratory tests and a realistic track test validated the feasibility of the proposed method by creating an accurate 3D reconstructed model. The modeled rail steel section size is quantitively compared with the ground truth in dimension, demonstrating good accuracy with a size error of less than 0.3 cm. The main contribution includes: (1) unmanned automatic 3D reconstruction by a robotic mobile manipulator, (2) the technique trims the reconstruction details & data to the specific maintenance goal or components, which supports the infrastructure maintenance towards the high-detailed & target-oriented digital management. This combination strategy of robotic automation and sensor fusion lies down a promising foundation for automated digital twin establishment for railway maintenance with autonomous RIRS, and upgrades technology readiness and digital intelligence for maintenance management

Effective HRM Practices for MSME Sector Success: An Empirical Study

Any organization's success strongly correlates with its workforce and employee engagement. Finding the correct human resource personnel can take much work for small and medium-sized businesses. Human resources significantly influence the success of the nation's small and medium-sized enterprises. Small and medium-sized companies are crucial to the nation's economic development and generate many job possibilities. Small and medium-sized businesses use human resources in various ways, including recruitment, performance evaluation, and compensation management. The success of human resource management in a company is greatly aided by the human resource-based system, which is very important for every firm. Although there are some parallels in H.R. methods, significant enterprises' H.R. groups are more focused on strategic business challenges and have succeeded in using information technology to a more considerable extent for the mundane file maintenance components of H.R.'s job. Contrarily, H.R. informants at mid-sized businesses are more operationally oriented, seem to be more content with the abilities and expertise of their noticeably smaller H.R. staffs, and give their H.R. organizations higher ratings on performance across a variety of parameters.

Partitioning of root respiration into growth, maintenance, and ion uptake components in a young larch-dominated forest

Partitioning of root respiration into growth, maintenance, and ion uptake components in a young larch-dominated forest

ASSESSMENT OF OPERATION AND MAINTENANCE PRACTICES IN FACILITIES MANAGEMENT OF OFFICE BUILDINGS IN LAGOS, NIGERIA

The development of facility management (FM) in Nigeria is relatively new and limited in scope although it has been introduced for more than four decades. This study attempts to assess the operation and maintenance practices in the FM of office buildings from the Nigeria context, aimed to address issues concerning activities of operation and maintenance. It also intends to reveal the adoption of FM techniques and associated challenges in the office buildings in Lagos., Nigeria. A total of 216 members of the Nigerian Institution of Estate Surveyors and Valuers (NIESV) were sampled using purposive sampling techniques and their responses were analysed by descriptive statistics such as weighted mean score (WMS), severity index (S.I), and Kruskal-Wallis H test (KWT). The study found that the major FM activities that are mostly engaged include space management, power plant/electricity maintenance, waste management, lift maintenance, general cleaning services, routine maintenance, and water management. While the preferred FM technique is a blended approach (both the preventive and the corrective methods). The prominent challenges in their respective categories were design flaws and poor installation of equipment (technical); inconsistency in financing maintenance, and high cost of maintenance components (finance); weak standards and poor enforcement (administrative), indifferent attitude towards maintenance issues, wrong perception and lack of foresight (top management). The study concluded that the operations of the FM practice are still in their infancy stage and characterised by prominent challenges of technical, administrative, and finance. However, being a multi-disciplinary profession, the study suggests efficient collaborative effort can be strengthened by an institutional framework that encourages human capacity development and enhanced technology to foster sustainable facilities management practice in the country.

Changes in cardiac proteome and metabolome following exposure to the PAHs retene and fluoranthene and their mixture in developing rainbow trout alevins

Exposure to polycyclic aromatic hydrocarbons (PAHs) is known to affect developing organisms. Utilization of different omics-based technologies and approaches could therefore provide a base for the discovery of novel mechanisms of PAH induced development of toxicity. To this aim, we investigated how exposure towards two PAHs with different toxicity mechanisms: retene (an aryl hydrocarbon receptor 2 (Ahr2) agonist), and fluoranthene (a weak Ahr2 agonist and cytochrome P450 inhibitor (Cyp1a)), either alone or as a mixture, affected the cardiac proteome and metabolome in newly hatched rainbow trout alevins (Oncorhynchus mykiss). In total, we identified 65 and 82 differently expressed proteins (DEPs) across all treatments compared to control (DMSO) after 7 and 14 days of exposure. Exposure to fluoranthene altered the expression of 11 and 19 proteins, retene 29 and 23, while the mixture affected 44 and 82 DEPs by Days 7 and 14, respectively. In contrast, only 5 significantly affected metabolites were identified. Pathway over-representation analysis identified exposure-specific activation of phase II metabolic processes, which were accompanied with exposure-specific body burden profiles. The proteomic data highlights that exposure to the mixture increased oxidative stress, altered iron metabolism and impaired coagulation capacity. Additionally, depletion of several mini-chromosome maintenance components, in combination with depletion of several intermediate filaments and microtubules, among alevins exposed to the mixture, suggests compromised cellular integrity and reduced rate of mitosis, whereby affecting heart growth and development. Furthermore, the combination of proteomic and metabolomic data indicates altered energy metabolism, as per amino acid catabolism among mixture exposed alevins; plausibly compensatory mechanisms as to counteract reduced absorption and consumption of yolk. When considered as a whole, proteomic and metabolomic data, in relation to apical effects on the whole organism, provides additional insight into PAH toxicity and the effects of exposure on heart structure and molecular processes.

Identification of Influencing Variables on Improving Resilience of High-Speed Railway System

In recent years, frequent natural disasters have brought great challenges to the stable operation of the high-speed railway (HSR). Improving the resilience of the HSR system is an urgent problem to be solved. This study aims to explore how to improve the resilience of the HSR system. Based on an in-depth literature review and case study, 11 variables and 15 hypothetical paths were proposed. Then the questionnaires were distributed to professionals from academia and industry. A total of 270 valid responses were received. Finally, the structural equation model was used to evaluate these variables’ influence degree and their influence path. The results indicated that the infrastructure components (i.e., quality control and equipment operation and maintenance) play a positive role in the persistence ability. The organizational operation and maintenance components (i.e., organizational structure and organizational efficiency) promote the speed of function restoration. The interactive system components (i.e., technical system and system operation and maintenance) also have a positive effect on adaptability and transformability. The three components of HSR system play a positive role in different resilience attributes (i.e., persistence ability, function restoration, adaptability, and transformability), which further positively impacts the effectiveness of improving resilience. Based on the accepted hypothetical paths, five strategies for improving resilience were discussed, such as a certain degree redundancy of key organizations or members, encouragement of self-organized decision-making, and establishment of the “health records” of each HSR line. This study would enrich the theoretical system of resilience and help practitioners better understand the influencing variables and influencing paths of the resilience of the HSR system.

Importance measure-based maintenance strategy considering maintenance costs

Maintenance is an important way to ensure the best performance of repairable systems. This paper considers how to reduce system maintenance cost while ensuring consistent system performance. Due to budget constraints, preventive maintenance (PM) can be done on only some of the system components. Also, different selections of components to be maintained can have markedly different effects on system performance. On the basis of the above issues, this paper proposes an importance-based maintenance priority (IBMP) model to guide the selection of PM components. Then the model is extended to find the degree of correlation between two components to be maintained and a joint importance-based maintenance priority (JIBMP) model to guide the selection of opportunistic maintenance (OM) components is proposed. Also, optimization strategies under various conditions are proposed. Finally, a case of 2H2E architecture is used to demonstrate the proposed method. The results show that generators in the 2E layout have the highest maintenance priority, which further explains the difference in the importance of each component in PM.

Conflict Resolution and Goal Maintenance Components of Executive Attention are Impaired in Persons With Aphasia

Purpose : An understanding of the relationship between attentional deficits and language processing can provide insight into the language disorders in persons with aphasia (PWA). Especially, executive attention is a critical component of the attentional system. However, the relationships among executive attention, language processing and aphasia have not been studied extensively. The purpose of this study was to investigate the role of goal maintenance and conflict resolution in word-level processing in persons with aphasia (PWA).<BR>Methods : Picture-Word Interference (PWI) tasks were used whereby written words were superimposed on pictures in congruent, neutral or incongruent conditions. Ten PWA and 20 normal individuals (NI) categorized words into animal or non-animal. Button press response times (RT) and error rates were measured.<BR>Results : The results revealed that PWA took significantly (p<.05) longer RTs than NI for the incongruent and neutral conditions, but there was no significant group difference for the congruent conditions. The NI committed significantly more errors on the lower proportion of the incongruent trial, however, the PWA showed no significant difference between two proportions of the PWI tasks.<BR>Conclusions : The PWA group evidenced impaired conflict resolution and goal maintenance under the PWI tasks. The fact that the PWA group was vulnerable to both demands of conflict resolution and goal maintenance suggests that the PWA group demonstrated impaired executive attention compared to the NI.

Multi-state Risk-Based Maintenance Analysis of Redundant Safety Systems Using the Markov Model and Fault Tree Method

The risk-based maintenance strategy has received special attention in the safe operation of nuclear power plants. Simultaneous quantification of the positive and negative effects of maintenance activities and components degradation effect makes it possible to accurately evaluate the risk criterion for safety systems of nuclear power plants. However, it is difficult to integrate the effects of maintenance and components degradation into the standard reliability approaches. A straightforward approach for considering components degradation and different maintenance policies is to make use of Markov maintenance models. In this article, the effectiveness of maintenance activities (including changes in the surveillance test intervals and alteration in the different maintenance policies) on the components unavailability with considering aging effects is quantified using Markov maintenance models and then by coupling these models and the fault tree method, the risk measure is upgraded from the component level to the system level. The proposed models are applied to evaluate the unavailability of two safety systems of VVER-1000/V446 nuclear power plants as case studies. The results show that the Markov method due to its multi-state nature is effective in the conservative evaluation of risk measures so that the unavailability computed by the coupling process is higher than the original unavailability (calculated by system fault tree using PSA data of nuclear power plants) for all maintenance policies. In addition, this study illustrates that the developed Markov maintenance models could be applied to the large-scale whole plant level and provides a proper transition from the classical PSA methods to new techniques. This approach integrates the effects of maintenance strategies and components degradation. Also, it provides a practical and a more accurate tool to determine the technical specification of a real nuclear power plant from the risk point of view.