System Maintenance Costs Research Articles

Report on a new remote collaborative medical care system -construction and operation of a remote collaborative medical care network for inflammatory bowel disease using information and communication technology in Hokkaido

Inflammatory bowel disease (IBD) comprises 2 major types-ulcerative colitis (UC) and Crohn's disease (CD). A remote collaborative medical care fee has been established for patients with suspected intractable diseases since 2020. Remote collaborative medical care is a type of telemedicine wherein a hospital specialist for intractable diseases, the patient, and an attending physician at a community hospital communicate via video calls. In IBD cases, however, treating patients who have already been diagnosed with severe or intractable diseases is difficult. As a part of the Hokkaido Intractable Disease Medical Care System Development Project, we have started providing free remote collaborative medical care services for all IBD patients, including those with a confirmed diagnosis and attending regional hospitals. We set up the telemedicine system using Microsoft365, a commercial cloud, and Nextcloud, a PaaS, to ensure robust security and enable rapid and massive sharing of medical details by information and communication technology. Since April 2021, we have examined 27 patients (36 times). Among these patients, 5 patients from regional hospitals were undiagnosed (1 patient of suspected CD, 3 patients of suspected IBD unclassified (IBD-U), and 1 patient of undiagnosed enteritis). Twenty-two patients from regional hospitals had a confirmed diagnosis (17 UC and 5 CD patients). Eight patients required a second time remote collaborative medical care, and 1 patient required a third time remote collaborative medical care. There was no equipment failure such as communication failure or system trouble, and all patients could be examined smoothly. The maintenance cost of the telemedicine system was 2500yen/month per hospital. Among all cases receiving remote collaborative medical care, 86% were consultations for refractory or severe active cases with a confirmed diagnosis of IBD. At present, the remote collaborative medical care fee for diagnosed patients is not permitted. Since remote collaborative medical care has the potential to correct regional disparities in medical standards, there is an urgent need to review the criteria for remote collaborative medical care fees.

Smart Design of Green Hydrogen Facilities: A Digital Twin-driven approach

This work studies the potentials of Digital Twin solutions for the design of competitive and reliable green hydrogen facilities. A digital twin based on stochastic simulations is proposed to address the uncertainties associated with investment and operating costs, to increase confidence and stimulate investments. Several input assumptions are involved (i.e., capital and operational costs, energy consumption, available energy, among others) to analyse their influence on financial indicators. A set of facility designs with equipment redundancy, and thus different system availabilities, was proposed. Monte Carlo simulation method is chosen to propagate uncertainties onto the project bankability assessment. By applying the proposed methodology, the opportunity index and internal rate of return (IRR) are calculated. A sensibility analysis is also carried out. The simulations illustrate that the design of a facility can be optimized to achieve higher profits, based on a trade-off between investment and availability. This study concludes that digital twin solutions are an opportunity for reducing the uncertainties associated with green hydrogen facility design. Improvements to the proposed model can be achieved by performing a refined simulation, in relation to the calculation of system availability and maintenance costs.

Mixed-integer Modelling and Optimization of a Heat Source and a Storage System

Thermal energy storages introduce flexibility into heating systems with numerous advantages on system performance, and operational and maintenance costs. One of the most prominent advantages is the ability to use heat sources at the operating points with higher efficiency To use the full potential of a thermal energy storage, an adequate control technique is required to control the heat sources connected to it. This paper models a heating system containing a heat source and a thermal energy storage and uses this model for optimal scheduling of the heat source. The optimal schedule is obtained through application of model predictive control which takes into account the efficiency of the heat source. A PI controller is also designed by following practical optima to serve as a baseline for comparison with the MPC-based scheduler. The obtained results show that the optimal scheduler is advantageous compared to the PI controller in terms of both energy efficiency and satisfying the posed constraints.

МАТЕМАТИЧЕСКАЯ МОДЕЛЬ И АЛГОРИТМ ОЦЕНКИ ЭНЕРГЕТИЧЕСКОГО ПОТЕНЦИАЛА ВЛАЖНОГО КОКСОВОГО ГАЗА НА МЕТАЛЛУРГИЧЕСКОМ ПРЕДПРИЯТИИ

Accurate calculation of fuel consumption helps to correctly plan the operating modes of power equipment. The paper presents a mathematical model for calculating the arrival of heat with coke oven gas at a metallurgical plant. Amendments to the gas consumption for its composition have been introduced. For each consumer, the chemical and physical energy that comes with the gas is determined. This method does not require measuring the composition of the coke oven gas for each consumer; furthermore there is no need to measure the humidity of the gas. For gas metering units, it is only required to install a standard set of devices before gas-consuming equipment, which reduces the cost of system maintenance.

An Enhanced Multifeature Fusion Method for Rotating Component Fault Diagnosis in Different Working Conditions

Mechanical rotating components such as bearing and gear are widely used in various industrial occasions. Fault diagnosis of rotating component can guarantee operational reliability and reduce maintenance cost of system. Although many fault diagnosis methods have been developed based on artificial intelligence methods, most of them ignore the existing signal processing knowledge in rotating element fault diagnosis domain. Meanwhile, these methods just assume that working conditions such as load or rotating speed keep constant, which may cause low accuracy once operating condition changes. To address these problems, an enhanced intelligent fault diagnosis method for rotating component is proposed based on multifeature and convolutional neural network (CNN). The vibration signals are first transformed into angular domain by resampling technique. Then, the angular domain signals are converted to obtain corresponding envelope and squared envelope spectrum features, which are fused into red–green–blue color image form to enhance sample features and enlarge differences among various health states. Finally, a CNN is constructed to accomplish fault recognition. Experimental results show that the average diagnosis accuracies of planetary gearbox and rolling element bearing datasets can reach 96.7% and 95.65%, which demonstrate that the multifeature approach is effective in fault diagnosis of rotating components in scenarios with different rotating speeds.

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.

Transformation Of Lithuanian Road Charging

The current road user charge in Lithuania is based on a temporary system and is not connected to the actually covered mileage. The time-based charge is not considered to be socially fair; therefore, the principles 'user pays' and 'polluter pays' shall be employed. The charge to be introduced will take into account the interests of local road infrastructure users who are currently paying unreasonably high charge for a short distance covered.If the current system is retained and e-tolling system is not established, heavy vehicle drivers would continue paying aroad user charge by purchasing e-vignette. It would mean that road user charges paid by vehicle owners/holders would not cover the damages directly made by the user and the current road charging system would not guarantee sufficient financing for the maintenance and development of the road infrastructure.Legal decisions on electronic road charging system have not been taken yet; however, the project implementation preparation is underway. The latest Parliamentary approvals were received in September 2020, and it is believed that all necessary legal acts will be amended by the end of 2020.The road charging technology has not been selected yet. However, the conducted project's implementation analysis, the assessment of necessary investments and road charging system maintenance costs revealed that a GPS-based technology would be the most economical one.It is planned to implement the electronic road charging system by the beginning of 2023. Upon the project's implementation, additional financing to ensure high quality and safe main roads should be allocated.

Proposal of noninvasive failure diagnosis of electrical motor using googlenet

Fault diagnosis is a useful tool that reduces system maintenance risks and costs. However, data related to the system's nominal and fault operating behavior is often not collected and stored adequately, it is difficult to identify and suggest automated fault detection methods. This study proposes a solution to apply deep learning technique on the convolutional neural network (CNN) to identify some common errors on induction motors based on operation sound. The opreration sound signal emitted from on a 0.37 kW two-pole induction motor is collected in some cases such as normal operation, phase loss, phase difference and bearing breakage. Their 2-D scalogram images are analyzed by continuous Wavelet transformation which is used to train and evaluate the deep learning CNN (i.e. GoogLeNet) to identify the above faults. Experimental results show that this method can diagnose induction motor faults with accuracy up to 98.8%.

Architecture of GIS Solutions for Detection and Development of Wildfire Database

This research paper presents organization of the business environment for work with geographic information systems (GIS) which are based on open source. The solution is completely open source: operating system, working environment and supporting apps. The architecture consists of: server, workstations, mobile devices and sensors. Software packages for each architecture segment will be displayed. The goal is to achieve a complete business environment for work with open source GIS, thus minimizing the costs of system development and maintenance. The illustrated example shows the possibility of applying GIS within a forestry company, in the field of wildfire monitoring and data collection and registering the possibility of wildfire occurrence using IoT.

Condition-based maintenance strategies for stochastically dependent systems using Nested Lévy copulas

Nowadays, industrial systems are more and more complex and components are integrated dependently. Without consideration of dependence between components often leads to overestimate the reliability of system and high maintenance cost. In this paper, a multi-component system with hierarchical stochastic dependencies is considered. Components within subsystem are strongly correlated and dependence between subsystems is heterogeneous. Thanks to its capacity of modeling asymmetric dependence structures, the Nested Lévy copula is used in this paper. Based on the multiple sources of dependence among components and hierarchical structures, a novel condition-based maintenance policy is proposed. The inspection scheme as well as maintenance decision is dynamically planned according to the collected inspection information and the influence of stochastic dependence is investigated. The numerical results show the efficiency and robustness of proposed maintenance policy on reducing the inspection and maintenance cost.

Application of embedded soft PLC in the control system of rapier loom.

At present, the rapier loom has gradually become the mainstream equipment in the manufacturing industry. In order to make the rapier loom realize automated production and further improve the production efficiency of the rapier loom, improve the programmability of the system, and reduce the cost of system maintenance. The thesis developed a rapier loom control system based on embedded soft PLC, and carried out experiments and applications in the field. The contribution and innovation of this paper is to develop a complete low-cost control system, and through a genetic algorithm optimized PID algorithm to complete the more effective control of the loom tension system. The embedded soft PLC system proposed in this paper reduces the overall maintenance cost of the system and improves the programmability of the system. This text carries on the systematic scheme design to the embedded soft PLC from the hardware system and the software system respectively. First, according to the actual requirements, this article designs the overall scheme of the embedded software PLC hardware system with STM32F407ZGT6 as the core. Then this article is based on the embedded soft PLC hardware platform, according to the international standard of industrial control programming, writes the embedded soft PLC low-level driver software. Secondly, this article analyzes the factors that affect the warp tension during the operation of the rapier loom, and proposes the use of genetic algorithm to optimize the warp tension control method of the traditional PID algorithm. Finally, we conducted verification tests and on-site application debugging for the entire set of rapier loom embedded soft PLC control system. We controlled the warp tension as the main experimental object. The results show that this control system effectively improves the control accuracy of the warp tension of the rapier loom and meets the actual needs of industrial applications. The whole system has a good application prospect in the warp tension control of rapier looms.

Research on the Architecture of Cloud Host Autonomous Backup System in a Cloud Data Center

In order to realiaze data central control, improve resource utilization and reduce the operation and maintenance cost of information system, enterprises often use private cloud data center to provide virtual cloud host services for users. Therefore, data backup for cloud host usres is particulary important. In this paper, an appropriate technical solution is proposed according to the actual requirements of enterprise cloud host data backup. First according to the performance requirements of data backup recovery for an enterprise cloud host, the three basic elements of data backup are briefly analyzed. Then the logical architecture of the cloud host’s autonomous backup system is built. Finally, the current mainstream backup networking mode, backup strategy and snapshot strategy are analyzed in detail. This architecture research can provide effective technical support for an enterprise to build a cloud host autonomous backup system.

Remaining-useful-lifetime and system-remaining-profit based importance measures for decisions on preventive maintenance

We propose two types of importance measures for component selection in preventive maintenance. The first type evaluates the relative importance of a component in terms of how much the component restoration increases the remaining useful lifetime of the system. The second type of importance measures evaluates the contribution of a maintenance action on a component with respect to the profit that the system can generate during its remaining useful lifetime, considering system reliability, maintenance cost, and uncertain system profit over the remaining useful lifetime. The proposed importance measures take into account various maintenance actions including imperfect repair and replacement, combine the advantages of time-dependent and time-independent lifetime measures on evaluating component importance and are suitable to aid the preventive maintenance decisions on component selection at any time. A numerical example and an application in the preventive maintenance for a wind turbine system are provided to illustrate the proposed importance measures and to compare various time-dependent and time-independent lifetime importance measures.

Enhancing library performance by exploiting the potentials of disruptive innovations

PurposeThe purpose of this paper is to investigate enhancement of library performance by exploiting the potentials of disruptive innovations.Design/methodology/approachDescriptive survey research design was used for this study. The population of the study was 167 respondents, consisting of 83 professional and 84 para-professional librarians in the libraries of the public higher institutions in Ekiti and Ondo States, Nigeria. Total enumeration sampling technique was used for the study. Data were collected using the questionnaire. Descriptive statistical tools were used for data analysis.FindingsIt was found that disruptive innovation has influence on library operations, the extent of application of disruptive innovation in library operation is low, the extent of using the by-products of disruptive innovation in the libraries is low and the challenges facing the adoption of disruptive innovations in libraries include: high cost of acquiring technological infrastructure, high cost of training library personnel, high costs of internet, inadequate technical know-how and high costs of system maintenance and upgrades.Practical implicationsLibraries should embrace the influence of disruptive innovations in their operations and service delivery.Originality/valueThis study is novel, as it approaches library performance from the perspective of the disruptive innovation. Very few studies emanate from Africa in this area. Most of the previous narratives around disruptive innovation centred around the Western countries such USA, UK, France, Italy, etc., which maintain a lead in library innovation and development. The current study demonstrated that the performance of libraries in Nigeria is not immune from being boosted by disruptive innovations.

Comprehensive Review on Fuel Cell Technology for Stationary Applications as Sustainable and Efficient Poly-Generation Energy Systems

Fuel cell technologies have several applications in stationary power production, such as units for primary power generation, grid stabilization, systems adopted to generate backup power, and combined-heat-and-power configurations (CHP). The main sectors where stationary fuel cells have been employed are (a) micro-CHP, (b) large stationary applications, (c) UPS, and IPS. The fuel cell size for stationary applications is strongly related to the power needed from the load. Since this sector ranges from simple backup systems to large facilities, the stationary fuel cell market includes few kWs and less (micro-generation) to larger sizes of MWs. The design parameters for the stationary fuel cell system differ for fuel cell technology (PEM, AFC, PAFC, MCFC, and SOFC), as well as the fuel type and supply. This paper aims to present a comprehensive review of two main trends of research on fuel-cell-based poly-generation systems: tracking the market trends and performance analysis. In deeper detail, the present review will list a potential breakdown of the current costs of PEM/SOFC production for building applications over a range of production scales and at representative specifications, as well as broken down by component/material. Inherent to the technical performance, a concise estimation of FC system durability, efficiency, production, maintenance, and capital cost will be presented.

Anode-Oxidizing Critical Operating Conditions of Large Planar Solid Oxide Fuel Cell

In a solid oxide fuel cell power system, large planar cells are common central parts for electric generation. In practice, the operating conditions of a planar cell may have significant impact on the electrical efficiency and the lifespan of the cell, thus the operating and maintenance cost of the power system. Given varying electric load, the power system would dynamically adjust the operating conditions of each cell or cell module, so that the energy and heat balance in the system is maintained, the fuel consumption is minimized and the cells are protected from reactant starvation, local overheating etc. To realize this functionality, we seek a fundamental understanding of the quantitative connections among fuel cell properties, operating conditions and optimal electrical efficiency.We established a quasi-2D model for quick evaluation of fuel and oxidant concentration and current density along the flow direction. For fuel cells with very low charge transfer impedance i.e. 0.02 Ω*cm^2 operating with low fuel flow rates, the fuel concentration at the exit may reach an equilibrium where the local Nernstian potential across the cell equals the cell voltage. In such cases, the fuel utilization remains almost constant regardless of varying fuel flow rate, given a certain cell voltage. For fuel cells with local charge transfer impedance of 0.5 Ω*cm^2 operating with high fuel flow rates, such phenomenon was not observed because the fuel concentration at the exit depends strongly on the fuel flow rate. Given the fuel molar fraction at the fuel inlet, the electrical efficiency of a fuel cell has its maximum at certain cell voltage, which depends strongly on the charge transfer impedance of the fuel cell. At constant fuel flow rates, the optimal cell voltage increases with lowering charge transfer impedance. The optimal electrical efficiency appears lower with higher inlet fuel molar fraction. Given fixed and uniform fuel cell temperature, the air flow rate has little impact on the electrical efficiency for air-fuel stoichiometric ratios above 1.3.Besides the above findings, further studies are necessary on the effects of temperature distribution as well as porous electrode diffusion resistance. Figure 1

Optimal dispatch of wind power-photovoltaic-concentrating solar power combined power generation system based on improved PSO

The output power of wind power and photovoltaic is randomness and uncertainty, which brings severe challenges to power generation planning and scheduling of power system. The concentrating solar power (CSP) station with heat storage has the same scheduling as the traditional unit. Through reasonable scheduling of CSP stations, the uncertainty of wind power and photovoltaic power generation can be effectively suppressed, and new energy consumption can be promoted. This paper comprehensively considers the market power sales benefits, grid-connected environmental benefits and system operation and maintenance costs of the wind power-photovoltaic-CSP combined system, a dispatching model is established with the objective of optimizing the grid connected benefits of the combined system. Aiming at the shortcomings of particle swarm optimization (PSO) that is easy to be premature, an improved particle swarm optimization (IPSO) algorithm is formed by adding convergence factor and improving inertia weight to optimize the scheduling model. The results show that the grid connection benefit of the combined system increases by 237784yuan per day after adding CSP. The convergence speed of the IPSO used in this paper has been greatly improved.

Optimised MOPSO with the grey relationship analysis for the multi-criteria objective energy dispatch of a novel SOFC-solar hybrid CCHP residential system in the UK

In the quest to achieve home comfort with the highest possible efficiency, there is an increasing interest in combined cooling, heating and power (CCHP) systems. These can be fuelled by natural gas and potentially by hydrogen enriched natural gas and ultimately by hydrogen. The optimised designs largely depend on the energy dispatch algorithms that take into account aspects of economic and environmental impacts as well as system efficiency. This paper details a new algorithm to optimise the operation of a novel hybrid solid oxide fuel cell (SOFC)-solar hybrid CCHP residential system. The proposed algorithm is based on the multi-objective particle swarm optimization (MOPSO) and the grey relationship analysis (GRA) (named as MOPSO-GRA) with the capability of resolving the objective energy dispatch issues within the system by effectively avoiding local optimum problem. More specifically, the grey incidences are first integrated into MOPSO to analyse the degree of closeness between non-ideal solutions and the ideal solution. Then, the relationship of degree is introduced to give objective energy dispatch in order to maximise the efficiency of energy utilization while minimising the system capital cost, operating costs, maintenance costs, fuel costs and emissions. Finally, the new algorithm is validated on the proposed new design of CCHP system. Ten cases are studied to evaluate the technical, economic and environmental performance of the MOPSO-GRA algorithm when being applied to an SOFC-based CCHP system under both the grid-connected and the island modes. A comparison is made with the conventional MOPSO method and system structure, and the impact of a plug-in EV is also evaluated. Based on a detailed cost and emissions analysis, the results indicate the environmental and economic advantages, in addition to the higher efficiency of the proposed methodology and system structure. The impact of these results and observations leads to the promotion of intelligent FC-based multi-energy system technologies for residential use.

A new parallel and decomposition approach to solve the medium- and low-voltage planning of large-scale power distribution systems

The world energy demand is increasing. Currently, most electricity generation sources are fossil fuels. In recent years, the global energy matrix for power generation is changing, in order to meet the demand with minimal environmental impacts. In this context, a new approach to solve the medium- (MV) and low- voltage (LV) planning of large-scale distribution systems via parallel computing and decomposition techniques is proposed. The mathematical formulation considers the allocation of substations, distribution transformers, MV and LV circuits, support structures, poles, renewable energy sources (RES), and energy storage sources (ESS). In addition, variable costs related to the operation of RES and ESS, power losses in cables, distribution transformers and substations, energy purchased from substations, and greenhouse gas emissions are also taken into account. System reliability and maintenance costs of these devices are also considered in the planning. To evaluate the new methodology performance, tests in a large-scale distribution system with 200 nodes in MV and 1672 nodes in LV is considered. Numerical results show the proposed methodology is able to find good solutions that guarantee the minimization of planning costs considering RES and ESS allocation. Furthermore, system reliability is improved by up to 22% and greenhouse gas emissions mitigation by up to 18%.

Hydrogeochemical characterization and suitability of water for irrigation in new and old reservoirs in northern Espirito Santo, Brazil

During the water crisis of 2015–2016, the construction of small earth-filled dams grew to supply irrigated crops of the north of Espirito Santo-ES, Brazil. This paper reports the hydrogeochemical study of eight reservoirs conducted between 10/2016 to 11/2017 to assess the water suitability for agricultural purposes and its risk to irrigation systems. The reservoirs of Sao Mateus (SM) are located in large drainage basins with many impoundments upstream. Nova Venecia's reservoirs (NV) have small and circular drainage areas with few, or any, upstream dams. The results are consistent with freshwater classification and Na-Cl composition to all reservoirs. Nevertheless, canonical discriminant analysis and Spearman's coefficients revealed distinct composition and patterns of correlations between municipalities. The mean permeability index of 53 and the low risk of sodicity and salinization (C1S1) demonstrate that these waters' use is harmless to the soil and crops. However, the phosphate contents make the new reservoirs susceptible to algae blooms. The same reservoirs also presented total solids and Fe levels above the tolerable limit for safety irrigation use, imposing a severe risk of clogging. The low replenishment of SM's reservoirs reflects the dispute over water resulting from the high number of impoundments in these drainage areas. The drought that preceded the study diminished the drainage basins' vegetation cover, favoring soil particles' runoff, elevating the TS and Fe levels, especially in the recently built reservoirs. Farmers must control soil erosion to avoid water quality compromise, to reduce the risk of failure and the irrigation system's maintenance cost.