Comprehensive Maintenance Research Articles

Development of Pavement Maintenance Management System for Baghdad Urban Roadway Network

The road transportation system is considered as major component of the infrastructure in any country, it affects the developments in economy and social activities. The Asphalt Concrete which is considered as the major pavement material for the road transportation system in Baghdad is subjected to continuous deterioration with time due to traffic loading and environmental conditions, it was felt that implementing a comprehensive pavement maintenance management system (PMMS), which should be capable for preserving the functional and structural conditions of pavement layers, is essential. This work presents the development of PMMS with Visual inspection technique for evaluating the Asphalt Concrete pavement surface condition; common types of Asphalt Concrete distress including (bleeding of Asphalt, patching, block cracking, edge cracking, longitudinal and transverse cracking, rutting, pot holes, longitudinal and transverse deformation) with their various severity and intensity conditions have been included in the system as data base. The surface of the pavement was divided into sections, and the pavement condition is visually evaluated by the raters using specially designed forms, each type of defect was measured, classified, and rated according to type, severity, and extent. Data will be fed to the system using the computer, various types of intensity and severity of distress were analyzed by the system, the present condition rating (PCR) of the pavement section is determined, and the system suggests the required maintenance action. The developed system which is assigned (PMMS-09) was verified in evaluating the pavement surface condition at AL-Jaderiah campus roadway network. The results indicated that the system is sound in evaluation of the pavement condition and in suggestion of the proper maintenance to reserve the pavement condition.

Multi-level predictive maintenance of smart manufacturing systems driven by digital twin: A matheuristics approach

Digital twin technology is gradually being applied to smart manufacturing systems and is providing valuable information for predictive maintenance of swarms of machines, but also raises the need for more accurate and real-time decision making. However, there is still a shortage of research in this area. This paper proposes a general multi-level predictive maintenance decision-making framework driven by digital twin, considering component dependencies, the variable time scale of decisions, and comprehensive maintenance resources, in which an optimal maintenance schedule can be obtained in real time and then fed back to the physical space, so as to realize closed-loop control. A maintenance decision-making optimization model is then formulated based on integer linear programming to minimize total maintenance costs while meeting required production capacity. Further, a novel matheuristics algorithm (i.e., the interoperation of metaheuristics and mathematical programming techniques) is introduced for various maintenance decision scenarios. Finally, a case study of an offshore oil and gas production system consisting of eight subsea Christmas trees is examined, and the effects of changes in production capacity, failure thresholds, and maintenance resources on the multi-level optimization of decision-making solutions are discussed.

Impact of Life Cycle Costing in Procurement of Robotic Track-Based Central Laboratory at Apex Medical Institute in India.

Introduction Life cycle costing is an important management tool that takes into account the implications of planning, acquiring, operating, maintaining, and disposing of an asset during its complete life cycle. A major hindrance to the procurement of expensive equipment in developing countries is the lack of a reliable framework combining and integrating all the equipment life cycle aspects into procurement process. Methods The study was conducted from the data collected from the bids that were received for procurement of two robotic track-based central laboratories which were installed at All India Institute of Medical Sciences (AIIMS), New Delhi. The procurement was done as per the guidelines laid down under General Finance Rules (GFR) 2017 following the two bid systems: technical bid and price/commercial bid. Results A complete financial analysis of the robotic laboratory was done that involved gathering of all the pertinent financial information into one place and then using that data to analyze the feasibility of the bid. The life cycle costs of both the labs were calculated by assuming the life of equipment as 10 years and by factoring in cost of equipment including 5-year warranty, comprehensive maintenance from years 6 to 10, indicative cost of all reagents for 10 years, and indicative cost of all other consumables for 10 years. Conclusion Results showed that the cost of equipment alone should not be the sole predictor of making purchase decisions of equipment. Further research may additionally explore differences between processes being followed in government versus private organizations, as well as national guidelines and subnational practices.

Adoption of prescriptive analytics for naval vessels risk-based maintenance:A conceptual framework

Prescriptive analytics is a novel maintenance approach by recommending the maintainer, the right maintenance action at the right time through prioritization of maintenance based on the risk. It assists in improving the existing preventive maintenance approach by offering a dynamic maintenance plan based on risk or Risk-based Maintenance Scheduling. To date, there is no clear definition of Naval Vessels Risk-based Maintenance as well as its framework, and it has not been applied extensively in naval vessel maintenance application which is peculiar compared to its application in plant maintenance. This paper reviews Risk-based Maintenance application in industries in an approach to develop prescriptive analytics for a comprehensive and dynamic naval vessels Risk-based Maintenance decision-making framework. It aims to establish an optimal maintenance scheduling to improve naval vessels availability and reduce maintenance costs while meeting stakeholders’ expectations. Objectives and considerations are also defined for peculiarities application of naval vessels. The framework is then evaluated to improve the effectiveness of the current Preventive Maintenance practice and the inconsistency of the existing maintenance decision-making model using the expert judgement in Reliability Centered Maintenance.

Logistics and maintenance research activities for DONES facility

DONES is planned to operate on a continuous basis with only two beam stop periods per year for maintenance. The planned operational availability is 70 %, which calls for a carefully analyzed preventive maintenance. The purpose of the research is to propose a realistic and comprehensive logistics and maintenance plan. All the maintenance activities are included in a Maintenance Matrix based on the Plant Breakdown Structure of the project. This is the basis for the creation of a maintenance plan that will lead to a Work Schedule. Special mention within this matrix will be given to those Maintenance operations that must be included in order to comply with regulation. The need of replacement of components impose some requirements on the dimensions of architectural features of the main building such as doors, airlocks, corridors and shipping bays. To enable these replacements, the flow of materials has been developed and analyzed by an intralogistics simulation with AnyLogic. The results of this simulation lead to modifications on either the building or the components such that the replacements are feasible. The periodic replacement of an activated component has been analyzed using FMEA methodology resulting in proposals for the plant equipment designers as well as the remote handling equipment designers. Virtual reality simulations are used for a staged approach to the maintenance operation. The simulation of the HEBT scraper helped to define in detail each step or the maintenance operation. This tool has proven to be very useful to prompt changes in both the plant equipment design and the remote handling equipment. Also, the procedure of the operation itself can be refined and optimized. The conclusion of the research activities is the contribution to the definition of the building, plant equipment and achievement of the target availability.

БОЛЕЗНЬ ШЕГРЕНА И ОСТЕОПОРОЗ В ПРАКТИКЕ ВРАЧА-СТОМАТОЛОГА: КЛИНИЧЕСКИЙ СЛУЧАЙ

Subject. The subject of this research is Sjogren's syndrome.
 Objective. The objective of this research is to report a clinical case of Sjogren's syndrome associated with osteoporosis under hospital outpatient care provided by a dental therapist.
 Methodology. The research design includes description of one clinical case. The study is conducted by the Department of Preventive Dentistry and Propedeutics of Dental Disease, and the Department of Intermediate Level Therapy and Geriatrics of Ural State Medical University. This paper presents clinical observations of the patient developing main symptoms of Sjogren's syndrome, as well it explores somatic/dental status and describes the framework for supervision during dynamic observation.
 Conclusion. The case study allows to explore one of the multiple cases leading to development of chronic Sjogren's syndrome. The patient experiences a worsening of symptoms associated with menopausal transition and with new signs brought on by osteoporosis shows specific symptoms. Clinical manifestations of Sjogren's disease are highly variable, complicating the diagnostic process. This creates a risk of delayed treatment and provokes the development of severe complications, especially against the background of osteoporosis. Rational selection of appropriate modern medical treatment (active general drug therapy) and dynamic observation of a reumatologyst are specially important. However, being an interdisciplinary problem Sjogren's syndrome requires involvement of dental professionals, training in professional oral hygiene procedure which is the initial step of comprehensive maintenance treatment (based on clinical recommendations) and dynamic observation of patients; based on systemic manifestations, other specialists such as a reumatologyst, a gastroenterologist, an endocrinologist, an ophthalmologist may be involved.

Predictive Maintenance 4.0 for Chilled Water System at Commercial Buildings: A Methodological Framework

Predictive maintenance is considered as one of the most important strategies for managing the utility systems of commercial buildings. This research focused on chilled water system (CWS) components and proposed a methodological framework to build a comprehensive predictive maintenance program in line with Industry 4.0/Quality 4.0 (PdM 4.0). This research followed a systematic literature review (SLR) study that addressed two research questions about the mechanism for handling CWS faults, as well as fault prediction methods. This research rectified the associated research gaps found in the SLR study, which were related to three points; namely fault handling, fault frequencies, and fault solutions. A framework was built based on the outcome of an industry survey study and contained three parts: setup, machine learning, and quality control. The first part explained the three arrangements required for preparing the framework. The second part proposed a decision tree (DT) model to predict CWS faults and listed the steps for building and training the model. In this part, two DT algorithms were proposed, C4.5 and CART. The last part, quality control, suggested managerial steps for controlling the maintenance program. The framework was implemented in a university, with encouraging outcomes, as the prediction accuracy of the presented prediction model was more than 98% for each CWS component. The DT model improved the fault prediction by more than 20% in all CWS components when compared to the existing control system at the university.

Comprehensive Production Maintenance and its Role in Improving the Company Performance

The study aimed to reveal the impact of applying comprehensive production maintenance on company performance in small and medium industrial Malaysian companies. The descriptive analytical secondary data was utilised as a tool for gathering data from 135 companies as a sample from 2009 to 2017, and after conducting the analysis of the data and testing the hypotheses, the study reached a number of results among them. There is a positive significant effect of the application of comprehensive productivity maintenance on company performance in in the small and medium industrial companies. Therefore, this study recommended that the total productive maintenance is a system that is also valuable for quality administration and safety administration in rapports of keeping the integrity of equipment and operating approaches. The study recommended giving more attention to the management of the industrial companies.

Research on the Talent Training Mode of High Speed Rail Comprehensive Maintenance Technology Professional Group under the Background of "Double High"

Research on the Talent Training Mode of High Speed Rail Comprehensive Maintenance Technology Professional Group under the Background of "Double High"

풍수해생활권 범위설정에 관한 연구

This study hopes that in establishing a comprehensive improvement plan for the storm and flood disaster neighborhood unit centered on the village-level living area, and implementing the project, management guidelines that can be operated together with the improvement of the system will be prepared so that the plans, projects and construction materials established by other ministries can be used in a complementary manner so that it can be managed as a more effective and comprehensive storm and flood disaster neighborhood unit.
 In addition to more specific preliminary reviews, review criteria considering urban planning factors are utilized, and various disaster map data and disaster vulnerability analysis data are used to derive disaster-prone areas.
 It is a study to meet the effectiveness of the management guidelines for the comprehensive maintenance plan of the future storm and flood disaster neighborhood unit by presenting systematic and specific clear standards and utilizing data.

풍수해 생활권 종합정비계획 수립 시 하류경계조건의 고려

The ‘Comprehensive Maintenance Plan for Neighborhood Unit in storm and flood disaster’ is a meaningful project in that it integrates and implements all storm and flood-related maintenance plans that have been dispersed by ministries. In this paper, we examined whether the 'Comprehensive Maintenance Plan for Neighborhood Unit' can be included in the 'intensive heavy rain' in August 2022 and 'Hinnamnor' in September, and whether it can be applied appropriately in inland areas without unreasonableness. The ‘flooding by Hinnamnor in Pohang’, ‘the claim of flood damage caused by the operation of Lake Sihwa’, and ‘flooding of the Moraenae stream’ had a common cause. In order to solve this problem, 'Pohang flooding by Hinnamnor' requires a separate design that considers sea level rise due to typhoon low pressure rather than dealing with tide forecast alone. There is a need for institutional arrangements (guidelines, etc.) In addition, in the case of the 'Moraenae District', cases caused by the rise of the 'downstream boundary condition' of nearby rivers must be reflected in the design.

Children born to women in opioid maintenance treatment: Alongitudinal study of child behavioral problems and parenting stress.

In the wake of the "opioid epidemic", there is considerable concern regarding potential harmful long-term effects of prenatal opioid exposure. Opioid misuse and addiction confer increased exposure to lifestyle stressors and health burdens. Accordingly, it is challenging to disentangle effects of prenatal opioid exposure per se from factors related to maternal stress. In this study, we followed 36 women enrolled in comprehensive opioid maintenance treatment (OMT) program and their children alongside 36 age-matched mother-child dyads from a community sample (COMP) from pregnancy until child-age 8 years. Across five sessions, we used a battery of well-established questionnaires to investigate trajectories of parenting stress and mental health symptoms as well as child behavior problems. The 8-year retention was relatively high (OMT: 72%, COMP: 67%), and the OMT sample remarkably stable and well-functioning, with minimal concomitant illicit drug use. Mixed effects regressions showed significantly different trajectories of child behavior problems (F = 3.8, p = 0.024) and parenting stress (F = 3.1, p = 0.016) in the two groups. Differences in experienced stress were largely explained by more distress specifically related to the parenting role in the OMT group (F = 9.7, p = 0.003). The OMT sample also reported higher psychological distress (F = 15.6, p < 0.001) than the comparison group, but notably few participants presented with problems that warranted clinical intervention. The results underscore the benefits of tailored follow-up of children prenatally exposed to opioids and their families beyond infancy and toddlerhood. Long-term direct effects of prenatal opioid exposure on behavior problems are likely modest, given an otherwise stable caregiving environment conducive to healthy development.

Blockchain Enabled Maintenance Management Framework for Military Equipment

Maintenance of military equipment plays a vital role in achieving higher war readiness. The vast number of military equipment and their deployment on distinct locations make their maintenance a challenging task. Decision-makers are always interested in knowing the latest status of equipment, develop effective maintenance strategies, and predict mission reliability as accurately as possible. To suffice this need, maintenance data of military equipment must be maintained with high granularity and accuracy, including maintenance information about every lowest maintainable unit of every military equipment. There is a profound need for a comprehensive maintenance management framework, which addresses several military-specific issues with equipment maintenance and stores the maintenance data in the utmost secure environment. In this article, we attempt to provide a novel blockchain enabled framework to make military maintenance management comprehensive and future ready. This article first provides a representation of the maintenance scenario of military equipment and later discusses the several choices made available within the blockchain technology, along with the architecture of the proposed blockchain. The proposed framework uses smart contracts to make monitoring and validation more uncompromising and with minimum human intervention. Some pragmatic analytics are presented in this article, along with the inherent blockchain advantages.

Design and Implementation of the Remote Operation and Maintenance Platform for the Combine Harvester

To meet the needs of remotely operating and maintaining combine harvesters in view of the problems of extensive operation, inefficient operation and maintenance, and backward management of combine harvesters, a remote operation and maintenance platform for the combine harvester has been designed. The platform mainly includes modules, such as data monitoring, fault prediction, fault diagnosis, and comprehensive operation maintenance. Among them, the data-monitoring module obtains the monitoring data of the vehicle terminal. It actively transmits to the remote operation and maintenance platform to remotely monitor the operation data or status of the combine harvester system. The fault prediction module builds a fault prediction model based on the fault features and data provided by all previous stages. It predicts and evaluates the actual operation of each component of the combine harvester in the foreseeable future, Based on the fault diagnosis model, the fault diagnosis module evaluates and classifies the current abnormal state of the combine harvester. The comprehensive operation and maintenance module formulates the corresponding maintenance and repair strategies according to the output results of the fault diagnosis and prediction. Through functional field testing of the platform, the results showed that the platform could perform real-time monitoring, fault prediction, fault diagnosis, and comprehensive operation maintenance for the operation information of the combine harvester. It helped to improve the intelligent operation level, management quality and operation, and maintenance efficiency of the combine harvester.

Bridge maintenance planning framework using machine learning, multi-attribute utility theory and evolutionary optimization models

Although various tools and procedures have been developed to help transportation engineers objectively evaluate bridge maintenance needs, selecting and scoping projects still relies on engineering judgment. The present paper intends to help engineers evaluate and maintain bridges by developing a comprehensive bridge maintenance planning framework (BMPF) within financial and performance constraints. The paper's objectives are to maximize the performance condition level of bridges and to minimize the maintenance cost by optimally planning the maintenance treatments. The framework includes bridge performance impact assessment, machine learning models, multi-attribute utility theory ranking model and genetic algorithm optimization model. The study analysed 95 bridges in a network with an 84% accuracy machine learning model prediction. Decision-makers' preferences were considered to rank all bridges using Multi-Attribute Utility Theory. 19 bridges were then chosen for maintenance based on budget and performance using a genetic algorithm model. The BMPF was observed to improve project productivity, reduce down time, and improve bridge inventory condition. Future research can explore the use of other optimization approaches and also include traffic flow and construction cost analysis for a better maintenance cost estimation. The machine learning model for performance prediction can be enhanced by utilizing different techniques.

A baseline-reactive scheduling method for carrier-based aircraft maintenance tasks

Carrier-based aircraft maintenance tasks are conducted in time-critical, resource-constrained, and uncertain environments. Optimizing the scheduling allocation scheme of maintenance personnel and equipment, reasonably responding to uncertainty disturbances, and maintaining a high fleet availability are vital to the combat and training missions of carrier-based aircraft. The maintenance task scheduling problem for carrier-based aircraft is investigated in this study. First, a mathematical model for comprehensive carrier-based aircraft maintenance task scheduling that considers constraints such as maintenance personnel, equipment/shop, space, and parallel capacity is developed. Second, to generate the baseline scheduling scheme, an improved non-dominated sorting genetic algorithm II (I_NSGA-II) with local neighborhood search is proposed for the model optimization solution; I_NSGA-II uses the serial scheduling generation scheme mechanism to generate the time sequence scheduling scheme for maintenance personnel and equipment/workshop of different fleet sizes. Third, to cope with dynamic uncertainty disturbances, two reactive scheduling methods, i.e., complete rescheduling and partial rescheduling, are proposed to perform reactive scheduling corrections to the baseline schedule. Case simulation shows that the established mathematical model is reasonable and practical, and that the proposed I_NSGA-II is superior to the current mainstream algorithms. In addition, the decision maker can select between the two reactive scheduling methods flexibly based on the different forms and scales of disturbance.

SIMULATION TESTS OF FLEET VEHICLES PERIODIC INSPECTIONS TIMELINESS: A CASE STUDY

This study analyzed the case of a medium-sized workshop and the income from servicing individual customers. The management of the company observed some unused potential in the garage and plans to sign contracts with fleet customers for comprehensive maintenance of their vehicles. The key question was how many fleet vehicles could be additionally serviced without losing individual customers? In this work, a simulation model of a workshop was developed, treated as a system for queuing orders and vehicles. The model includes a subsystem of random generation of fleet vehicle mileage during the simulation. The idea of event-driven simulation and the Matlab/Simulink SimEvent environment library was used.

Research on Comprehensive Operation and Maintenance Based on the Fault Diagnosis System of Combine Harvester

In view of the difficulty in diagnosing and discriminating fault conditions during the operation of combine harvesters, difficulty in real-time processing of health status, and low timeliness of fault processing, a comprehensive operation and maintenance platform for combine harvesters was developed in this study which realized the functions of data monitoring and the full operation and maintenance of a combine harvester. At the same time, through the comprehensive operation and maintenance platform, the harvester information was obtained in real-time, the diagnosis results were obtained, and the maintenance service was effectively carried out through the platform. The IPSO-SVM fault diagnosis algorithm was proposed, and the performance of the fault diagnosis of the combine harvester was verified by the simulation test. The experimental verification showed that the system met the requirements of remote monitoring of combine harvesters, and the prediction accuracy of this method was 97.96%. Compared with SVM (87.51%), GA-SVM (89.44%), and PSO-SVM (92.56%), this system had better generalization ability and effectively improved the management level of the comprehensive operation and maintenance of the combine harvester. A theoretical basis and technical reference will be provided for the follow-up research for the comprehensive operation and maintenance platform of the combine harvester in this paper.

An Integrated Framework for Operation and Maintenance of Gas Utility Pipeline Using BIM, GIS, and AR

To maintain underground utilities in a safe condition, the need for a comprehensive management and maintenance system is becoming more prominent. There are several problems with the current operation maintenance applications in underground utilities, including the lack of a digitalized 3D model with a comprehensive database for dynamically editing data on the site. This research proposes a pipeline operation and maintenance management system (POMMS) by employing building information modeling (BIM), geographic information system (GIS), and augmented reality (AR) and integrating various project information sources through application programming interface (API) and cloud database. This system can facilitate decision-making by more realistic 3D visualizations, enhanced integration of construction, geographic and inspection information, and efficient data retrieval. The proposed system is applied to an actual project to validate its efficiency. In this research, two scenarios and one survey were conducted to investigate the performance of POMMS. The case study and survey results indicates POMMS’s efficiency in improving data collection, communication among stakeholders, and perception of as-built subsurface utility map while unfolding several crucial challenges and limitations of real-world implementation of the system.

The relationship between early weight loss and weight loss maintenance with naltrexone-bupropion therapy.

SummaryBackgroundExtended-release (ER) naltrexone/bupropion (NB) was associated with greater weight loss than placebo in four randomized, 56-week trials. The association of NB with longer-term maintenance of weight loss remains unknown.MethodsWe conducted a post-hoc analysis of four phase III, randomized, double-blind, placebo-controlled, 56-week studies (COR-I, COR-II, COR-BMOD, and COR-DM), the placebo-controlled cardiovascular outcomes trial LIGHT (208 weeks), and the randomized, open-label trial IGNITE (78 weeks). Included subjects were treated with NB 32 mg/360 mg or placebo, with baseline, week 16, and final time point data. The primary outcome was Kaplan-Meier-estimated weight loss maintenance in each study for up to 204 weeks.FindingsOur analysis included data from 10,198 particpants (NB=5412; placebo=4786). Proportions of patients with ≥5% or ≥10% weight loss maintenance were numerically higher for NB vs. placebo in all studies and time points. Differences were statistically significant for ≥5% weight loss maintenance in COR-BMOD and COR-I/-II at weeks 52 and 56 and the LIGHT study at weeks 52, 104, and 208. For ≥10% weight loss maintenance, differences were statistically significant in COR-I/COR-II at weeks 52 and 56.InterpretationThese data suggest that NB could be used as part of long-term, comprehensive weight loss and weight loss maintenance strategies.FundingOrexigen Therapeutics, Inc. and Bausch Health Canada.