In the face of data scarcity in the optimization of maintenance strategies for civil aircraft,traditional failure data-driven methods are encountering challenges owing to the increasing reliability of aircraft design....In the face of data scarcity in the optimization of maintenance strategies for civil aircraft,traditional failure data-driven methods are encountering challenges owing to the increasing reliability of aircraft design.This study addresses this issue by presenting a novel combined data fusion algorithm,which serves to enhance the accuracy and reliability of failure rate analysis for a specific aircraft model by integrating historical failure data from similar models as supplementary information.Through a comprehensive analysis of two different maintenance projects,this study illustrates the application process of the algorithm.Building upon the analysis results,this paper introduces the innovative equal integral value method as a replacement for the conventional equal interval method in the context of maintenance schedule optimization.The Monte Carlo simulation example validates that the equivalent essential value method surpasses the traditional method by over 20%in terms of inspection efficiency ratio.This discovery indicates that the equal critical value method not only upholds maintenance efficiency but also substantially decreases workload and maintenance costs.The findings of this study open up novel perspectives for airlines grappling with data scarcity,offer fresh strategies for the optimization of aviation maintenance practices,and chart a new course toward achieving more efficient and cost-effective maintenance schedule optimization through refined data analysis.展开更多
In this article we are discussing the suggestion of planning maintenance in such situation that we have failures in database of failures and maintenance registered also according to type of failure— priority or non-p...In this article we are discussing the suggestion of planning maintenance in such situation that we have failures in database of failures and maintenance registered also according to type of failure— priority or non-priority. We are assuming that maintenance must be mainly oriented on avoiding major failures of machines. The effect of maintenance manifests with delay and is dependent on development of failures. We express this problem as linear programming task that is solvable with Solver-extension of application Excel. We demonstrate the suggested solution on example of failures of machines between years 2010 and 2012.展开更多
Civil infrastructure system maintenance planning is to determine which facility should be repaired,when and how maintenance should be carried out,and what treatment should be used under budget and other resource const...Civil infrastructure system maintenance planning is to determine which facility should be repaired,when and how maintenance should be carried out,and what treatment should be used under budget and other resource constraints.In the existing literature,various simulation and optimization models have been developed to help select the optimal maintenance plan.However,the developed models overlooked the deterioration propagation between adjacent connected facilities of the network infrastructure system.For instance,a facility receiving zero maintenance or having a failure of maintenance treatment affects not only the condition of itself,but also the deterioration rate of its neighboring facilities.This raises the call for taking the deterioration propagation into consideration when developing optimization models and capture to which extent it can affect the optimal maintenance plan.Therefore,in this paper,an infrastructure maintenance planning model considering the deterioration propagation between facilities is formulated as a mixed integer linear programming problem.A heuristic algorithm was proposed to solve the problem efficiently.Example networks were tested for the performance comparison between CPLEX and the heuristic algorithm.The proposed model performs better than models without the deterioration propagation.展开更多
This paper briefly introduced the general maintenance methods of subway vehicles, such as routine technical maintenance and unplanned technical maintenance, analyzed the problems existing in routine technical service,...This paper briefly introduced the general maintenance methods of subway vehicles, such as routine technical maintenance and unplanned technical maintenance, analyzed the problems existing in routine technical service, and introduced the optimal technical service strategy: decision-making under gray conditions, reasonable decision-making chart and so on. Studied and optimized technical service policy management, including strengthening human resource capacity, establishing scientific and technological maintenance process and implementing comprehensive technical service plan. The safety of subway vehicles has been ensured by strengthening the inspection and maintenance operation capabilities of subway vehicles and optimizing the inspection and maintenance of technology and management.展开更多
The autonomous vehicles are the future of mobility across the globe and are expected to touch the lives of every person of all ages. But this comes with certain challenges regarding safety, reliability, cost, legal fr...The autonomous vehicles are the future of mobility across the globe and are expected to touch the lives of every person of all ages. But this comes with certain challenges regarding safety, reliability, cost, legal framework, regulations, etc. however, of all the concern safety and reliability are of utmost importance for researchers and engineers. The current research is focused on the movement of the autonomous vehicle in the work zone. The work zone is one of the most challenging areas for the autonomous vehicle to drive from. This is because the work zones are very dynamic, and all the construction activities are specific to the site condition and cannot always be predefined. The study provides a concept of how pavement marking can be used for smooth <span style="font-family:Verdana;">movement through the complicated work zone. In this study, various pav</span><span style="font-family:Verdana;">ement marking signs have been designed as a concept considering the standard colors and striping width being used in the Manual of Uniform Traffic control device (MUTCD). The study assumes that the movement of the autonomous vehicle will not be exclusive and that it will move with the driver driven vehicle. It is expected that autonomous vehicles will require special pavement marking and signage for smooth movement through the work zone. These pavement marking and signage will eventually become part of standard Traffic Control Plans (TCP) and Maintenance of Traffic Plans (MOT). The research aims to study the current research being done in this area and technology being used for detecting various pavement markings and signages.</span>展开更多
The objective of this work was to enhance the product’s quality by concentrating on the machine’s optimized efficiency.In order to increase the machine’s reliability,the basis of reliability-centered maintenance ap...The objective of this work was to enhance the product’s quality by concentrating on the machine’s optimized efficiency.In order to increase the machine’s reliability,the basis of reliability-centered maintenance approach was utilized.The purpose was to establish a planned preventive maintenance strategy to identify the machine’s critical components having a noteworthy effect on the product’s quality.The critical components were prioritized using failure mode and effect analysis(FMEA).The goal of the study was to decrease the ppm time interval for a CNC machine by simulating the projected preventive maintenance time interval.For this purpose,the simulation software ProModel 7.5 was implemented for the current preventive maintenance procedure to choose the best ppm time interval which contributed better norms.Five dissimilar optimization approaches were applied,however,the first approach yielded the prominent total system cost and the shorter ppm interval.The results of the study revealed that there was an increase of USD 1878 as a result of an increase in total system cost from USD 78,365 to USD 80,243.Preventive maintenance costs were reduced from USD 4196 to USD 2248(46%).The costs associated with good parts increased from USD 8259 to USD 8294(0.4%)and the costs associated with defective parts reduced from USD 171 to USD 3(98.25%),respectively.展开更多
Predicting the future health state of a transformer can offer early warning of latent defects and faults within the transformer,thereby facilitating the formulation of power outage maintenance plans and power dispatch...Predicting the future health state of a transformer can offer early warning of latent defects and faults within the transformer,thereby facilitating the formulation of power outage maintenance plans and power dispatch strategies.However,existing prediction methods based on the structure of‘splicing prediction and diagnosis method’suffer from limitations such as inability to achieve global optimality,error accumulation,and low prediction accuracy.To fill this gap,a novel direct prediction method of a trans-former state based on knowledge and data fusion-driven model(K&DFDM)is pro-posed in this paper.Firstly,a state quantity data space is constructed to comprehensively reflect the changes in the health state of the transformer over time,encompassing online monitoring,offline testing,evaluation results,and actual operation data.After that,correlation knowledge between state quantities,fault diagnosis mechanism knowledge,current diagnosis experience knowledge,and uncertain fuzzy knowledge are extracted separately.The actual fault mechanism,existing expert experience,and other knowledge in the diagnosis process are quantified.Then,the attention model is sub-sequently optimised,leveraging quantitative knowledge to effectively constrain and guide the data prediction process.Incorporating fault diagnosis mechanism knowledge into the data prediction model enables the achievement of global optimisation in both diagnosis and prediction.The integration of traditional expert experience knowledge and the correlation knowledge between state quantities serves as constraints during the process of attaining the global optimum.The verification results,comprising 327 cases,demonstrate that K&DFDM effectively addresses the issue of error superposition encountered by existing state prediction methods,leading to a direct state prediction accuracy of 96.33%.展开更多
文摘In the face of data scarcity in the optimization of maintenance strategies for civil aircraft,traditional failure data-driven methods are encountering challenges owing to the increasing reliability of aircraft design.This study addresses this issue by presenting a novel combined data fusion algorithm,which serves to enhance the accuracy and reliability of failure rate analysis for a specific aircraft model by integrating historical failure data from similar models as supplementary information.Through a comprehensive analysis of two different maintenance projects,this study illustrates the application process of the algorithm.Building upon the analysis results,this paper introduces the innovative equal integral value method as a replacement for the conventional equal interval method in the context of maintenance schedule optimization.The Monte Carlo simulation example validates that the equivalent essential value method surpasses the traditional method by over 20%in terms of inspection efficiency ratio.This discovery indicates that the equal critical value method not only upholds maintenance efficiency but also substantially decreases workload and maintenance costs.The findings of this study open up novel perspectives for airlines grappling with data scarcity,offer fresh strategies for the optimization of aviation maintenance practices,and chart a new course toward achieving more efficient and cost-effective maintenance schedule optimization through refined data analysis.
文摘In this article we are discussing the suggestion of planning maintenance in such situation that we have failures in database of failures and maintenance registered also according to type of failure— priority or non-priority. We are assuming that maintenance must be mainly oriented on avoiding major failures of machines. The effect of maintenance manifests with delay and is dependent on development of failures. We express this problem as linear programming task that is solvable with Solver-extension of application Excel. We demonstrate the suggested solution on example of failures of machines between years 2010 and 2012.
文摘Civil infrastructure system maintenance planning is to determine which facility should be repaired,when and how maintenance should be carried out,and what treatment should be used under budget and other resource constraints.In the existing literature,various simulation and optimization models have been developed to help select the optimal maintenance plan.However,the developed models overlooked the deterioration propagation between adjacent connected facilities of the network infrastructure system.For instance,a facility receiving zero maintenance or having a failure of maintenance treatment affects not only the condition of itself,but also the deterioration rate of its neighboring facilities.This raises the call for taking the deterioration propagation into consideration when developing optimization models and capture to which extent it can affect the optimal maintenance plan.Therefore,in this paper,an infrastructure maintenance planning model considering the deterioration propagation between facilities is formulated as a mixed integer linear programming problem.A heuristic algorithm was proposed to solve the problem efficiently.Example networks were tested for the performance comparison between CPLEX and the heuristic algorithm.The proposed model performs better than models without the deterioration propagation.
文摘This paper briefly introduced the general maintenance methods of subway vehicles, such as routine technical maintenance and unplanned technical maintenance, analyzed the problems existing in routine technical service, and introduced the optimal technical service strategy: decision-making under gray conditions, reasonable decision-making chart and so on. Studied and optimized technical service policy management, including strengthening human resource capacity, establishing scientific and technological maintenance process and implementing comprehensive technical service plan. The safety of subway vehicles has been ensured by strengthening the inspection and maintenance operation capabilities of subway vehicles and optimizing the inspection and maintenance of technology and management.
文摘The autonomous vehicles are the future of mobility across the globe and are expected to touch the lives of every person of all ages. But this comes with certain challenges regarding safety, reliability, cost, legal framework, regulations, etc. however, of all the concern safety and reliability are of utmost importance for researchers and engineers. The current research is focused on the movement of the autonomous vehicle in the work zone. The work zone is one of the most challenging areas for the autonomous vehicle to drive from. This is because the work zones are very dynamic, and all the construction activities are specific to the site condition and cannot always be predefined. The study provides a concept of how pavement marking can be used for smooth <span style="font-family:Verdana;">movement through the complicated work zone. In this study, various pav</span><span style="font-family:Verdana;">ement marking signs have been designed as a concept considering the standard colors and striping width being used in the Manual of Uniform Traffic control device (MUTCD). The study assumes that the movement of the autonomous vehicle will not be exclusive and that it will move with the driver driven vehicle. It is expected that autonomous vehicles will require special pavement marking and signage for smooth movement through the work zone. These pavement marking and signage will eventually become part of standard Traffic Control Plans (TCP) and Maintenance of Traffic Plans (MOT). The research aims to study the current research being done in this area and technology being used for detecting various pavement markings and signages.</span>
基金This research is fully supported by HEC Grant of Research for publishing scientific articles.The authors fully acknowledge support from Sarhad University of Science and Information Technology for the approved fund which makes this research viable and effective.
文摘The objective of this work was to enhance the product’s quality by concentrating on the machine’s optimized efficiency.In order to increase the machine’s reliability,the basis of reliability-centered maintenance approach was utilized.The purpose was to establish a planned preventive maintenance strategy to identify the machine’s critical components having a noteworthy effect on the product’s quality.The critical components were prioritized using failure mode and effect analysis(FMEA).The goal of the study was to decrease the ppm time interval for a CNC machine by simulating the projected preventive maintenance time interval.For this purpose,the simulation software ProModel 7.5 was implemented for the current preventive maintenance procedure to choose the best ppm time interval which contributed better norms.Five dissimilar optimization approaches were applied,however,the first approach yielded the prominent total system cost and the shorter ppm interval.The results of the study revealed that there was an increase of USD 1878 as a result of an increase in total system cost from USD 78,365 to USD 80,243.Preventive maintenance costs were reduced from USD 4196 to USD 2248(46%).The costs associated with good parts increased from USD 8259 to USD 8294(0.4%)and the costs associated with defective parts reduced from USD 171 to USD 3(98.25%),respectively.
基金Research on Robust Decision and Full Stack Optimisation Techniques for Cloud Edge Intelligent Systems for Substation Inspection,Grant/Award Number:52550022001J。
文摘Predicting the future health state of a transformer can offer early warning of latent defects and faults within the transformer,thereby facilitating the formulation of power outage maintenance plans and power dispatch strategies.However,existing prediction methods based on the structure of‘splicing prediction and diagnosis method’suffer from limitations such as inability to achieve global optimality,error accumulation,and low prediction accuracy.To fill this gap,a novel direct prediction method of a trans-former state based on knowledge and data fusion-driven model(K&DFDM)is pro-posed in this paper.Firstly,a state quantity data space is constructed to comprehensively reflect the changes in the health state of the transformer over time,encompassing online monitoring,offline testing,evaluation results,and actual operation data.After that,correlation knowledge between state quantities,fault diagnosis mechanism knowledge,current diagnosis experience knowledge,and uncertain fuzzy knowledge are extracted separately.The actual fault mechanism,existing expert experience,and other knowledge in the diagnosis process are quantified.Then,the attention model is sub-sequently optimised,leveraging quantitative knowledge to effectively constrain and guide the data prediction process.Incorporating fault diagnosis mechanism knowledge into the data prediction model enables the achievement of global optimisation in both diagnosis and prediction.The integration of traditional expert experience knowledge and the correlation knowledge between state quantities serves as constraints during the process of attaining the global optimum.The verification results,comprising 327 cases,demonstrate that K&DFDM effectively addresses the issue of error superposition encountered by existing state prediction methods,leading to a direct state prediction accuracy of 96.33%.
